ARTICLE | doi:10.20944/preprints201608.0083.v1
Subject: Earth Sciences, Environmental Sciences Keywords: deformation; interferometry; geotechnical models; non‐linear problem; synthetic aperture radar (SAR); time‐series
Online: 8 August 2016 (14:50:19 CEST)
This paper is aimed at studying the temporal evolution of the surface displacements occurred over the past few years in the ocean-reclaimed platforms of the Shanghai megacity (China), which are mainly ascribable to consolidation processes of large dredger fills and alluvial deposits. With respect to previous analyses carried out over the same area, this work provides a joint multi-platform differential interferometry synthetic aperture radar (DInSAR) analysis, based on the application of the advanced Small BAseline Subset (SBAS) algorithm. This led us to retrieve long-term deformation time-series that are helpful for a better understanding of the on-going deformation phenomena. To this aim, we have exploited two sequences of SAR data collected by the ASAR/ENVISAT and by the COSMO-SkyMed (CSK) sensors, respectively, spanning the whole time period from 2007 to 2016. Unfortunately, the large time gap (of about three years) existing between the available ASAR/ENVISAT and CSK datasets gave rise to additional difficulties for their combination. Nevertheless, this problem has been faced by benefiting from the knowledge of a time-dependent model describing the temporal evolution of the expected deformations affecting the Shanghai ocean-reclaimed platforms.
Sun, 21 June 2020
ARTICLE | doi:10.20944/preprints202003.0366.v3
Subject: Earth Sciences, Environmental Sciences Keywords: COVID-19; coronavirus; temperature; solutions
Online: 21 June 2020 (16:19:26 CEST)
This article investigated whether the atmospheric temperature had any role in the spread and vulnerability to COVID-19 worldwide and how that knowledge can be utilized to contain the fast-spreading disease. It highlighted that temperature was an important factor in transmitting the virus, and a moderately cool environment was the most favourable state for its susceptibility. In fact, the risk from the virus is reduced significantly in high temperature environment. Warm countries and places were likely to be less vulnerable. We identified various degrees of vulnerability based on temperature and specified countries for March and April. The maximum reported case, as well as death, was noted when the temperature was in the range of around 275°K (2°C) to 290°K (17°C). Countries like the USA, UK, Italy and Spain belonged to this category. The vulnerability was moderate when the temperature was less than around 275°K (2°C) and countries in that category were Russia, parts of Canada and few Scandinavian countries. For temperature 300°K (27°C) and above, a significantly lesser degree of vulnerability was noted. Countries from SAARC, South East Asia, the African continent and Australia fell in that category. In fact, when the temperature was more than 305°K (32°C), there was a unusually low number of reported cases and deaths. For warm countries, further analyses on the degree of vulnerability were conducted for the group of countries from SAARC and South East Asia and individual countries were compared. We also showed countries can switch from one vulnerability state to another based on the variability of temperature. We provided maps of temperature to identify countries of different vulnerability states in different months of the year. That influence of temperature on the virus and previous results of clinical trials with similar viruses gave us a useful insight that regulating the level of temperature can provide remarkable results to arrest and stop the outbreak. Based on that knowledge, some urgent solutions are proposed, which are practically without side effects and very cost-effective too.
Thu, 3 June 2021
SHORT NOTE | doi:10.20944/preprints202106.0117.v1
Subject: Earth Sciences, Atmospheric Science Keywords: COVID-19; Medical Waste; Sustainability; Environment.
Online: 3 June 2021 (13:22:55 CEST)
The situation in the world of pandemics is rapidly changing, and the second wave of COVID-19 has put a lot of pressure on the government and private sector, which are primarily responsible for controlling the situation. COVID-19 positive cases have increased in recent months relative to last year, and the number of patients admitted to hospitals has also increased, despite the fact that few of them were denied admission due to shortage of beds. Normal people who experience any symptoms immediately isolate themselves and begin taking the COVID medications prescribed by medical personnel and their team. During these times, all domestic people tossed the wrappers and boxes of medicines into the regular trash can, and the waste was handed over to the waste collector, who treated it like any other domestic waste and disposed of it using open dumping or other methods. The goal of this perspective is to suggest the collections of these types of waste from domestics, and protect the natural resources like water, soil, and even living beings like animals from pollution (from the effect of SARS-CoV-2). The main challenge for environmental waste management agencies is determining who has COVID positive and which houses generate these types of waste; thus, proposed strategy may be beneficial to the long-term sustainability of natural resources and animals.
Mon, 6 May 2019
ARTICLE | doi:10.20944/preprints201905.0064.v1
Subject: Earth Sciences, Environmental Sciences Keywords: tobacco product waste; framework convention; cigarette butts; tobacco control
Online: 6 May 2019 (12:21:37 CEST)
Cigarette butts, also known as tobacco product waste (TPW), are the single most collected item in environmental trash cleanups worldwide. This study used an online survey tool (Qualtrics) to assess knowledge, attitudes, and perceptions about this issue among individuals representing the Framework Convention Alliance (FCA). The FCA has about 683 members on its listserv, including non-governmental tobacco control advocacy groups that support implementation of the World Health Organization’s (WHO) Framework Convention on Tobacco Control (FCTC). Respondents (n = 65) represented countries from all six WHO regions. The majority (82%) had heard the term TPW, and all considered TPW as an environmental harm at some level. Additionally, 29% of respondents failed to identify that “cigarette filters make smoking easier.” Most (73%) correctly identified TPW components; however, fewer (60%) correctly identified the composition of cigarette butts. The majority (57%) were unfamiliar with Extended Producer Responsibility (EPR) and Product Stewardship (PS) as possible environmental intervention strategies. Respondents expressing opinions concurred that adding a litter fee to fund TPW programs will aid in reducing tobacco use and reduce the environmental impacts of TPW (100%); that prevention, reduction, and mitigation of TPW could be an important part of international tobacco control programs (98%); and that banning smoking in outdoor venues could reduce TPW (95%). Only 16% reported effective prevention or clean-up efforts in their countries. Weighted rankings revealed that respondents’ saw the national government, the tobacco industry, and state governments as most important in addressing TPW. The results of this research will inform continuing international discussions by the FCTC Conference of the Parties (COP) regarding environmental policies that may be addressed within FCTC obligations.
Mon, 6 April 2020
REVIEW | doi:10.20944/preprints202004.0069.v1
Subject: Earth Sciences, Environmental Sciences Keywords: coronavirus; SARS-CoV-2; COVID-19; respiratory diseases; air pollution
Online: 6 April 2020 (15:48:46 CEST)
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), known to cause 2019-coronavirus disease (COVID-19) pandemic is a zoonotic coronavirus and crosses species to infect human populations, where an efficient transmission of virus occurs human-to-human. Nationwide lockdown is being adopted to stop public transport, keep people at their homes and out of their work, and maintain social distancing. In turn, large geographic areas in the world (including China, Italy, Spain, and USA) has been almost halted. This temporary halt is significantly slashing down the air pollution (air pollutants and warming gases) in most cities across the world. This paper: (i) introduces both COVID-19 and air pollution; (ii) overviews the relation of air pollution with respiratory/lung diseases; (iii) compiles and highlights major data appeared in media and journals reporting lowering of air pollution in major cities those have been highly impacted by the COVID-19; and also (iv) lists the way forward in the present context. Because COVID-19 is an ongoing pandemic and currently far from over, strong conclusions could not be drawn with very limited data at present. The temporary slashed down global air pollution as a result of COVID-19 restrictions are expected to stimulate the researchers, policy makers and governments for the judicious use of resources; thereby minimise the global emissions, and maintain their economies once the pandemic eases. On the other, lifting of the nationwide lockdown and eventual normalisation of the temporarily halted sectors may also reverse the currently COVID-19 pandemic-led significantly slashed down global air pollution that could make the future respiratory health crisis grimmer.
Sun, 14 June 2020
ARTICLE | doi:10.20944/preprints202006.0186.v1
Online: 14 June 2020 (16:12:35 CEST)
The COVID-19 pandemic has obliged Governments all around the world to take confinement and social 13 distancing measures. The reduction of leisure and production activities on beaches and ports have 14 disappeared direct and indirect contamination such as plastics, hydrocarbon spill, microbiological loads, 15 noise level, etc. leading to temporary improved environmental conditions, converting the beaches 16 similar to Marine Protected Areas. Some conditions are briefly analyzed through local surveys and in situ 17 observations in the popular beaches and ports of Salinas, Manta and Galápagos. 97-99 % of surveyed 18 people agreed that beaches have notoriously improved during confinement at least from visual 19 observation. On a scale from 1 (worst) to 5 (best), the beaches were rated 2.23 and 2.83 (less than 20 acceptable) before quarantine, and 4.48 and 4.33 after it for Salinas and Manta respectively. The 21 beaches have less garbage in general and plastic, even though there has been an increase in plastic and 22 face mask production around the world. In Salinas, 72%, and 23 % of surveyed people have seen small 23 pelagic fish, whilst in Manta 75%, and 41% of people saw the same, but also 17% of people have seen 24 whales (humpback and shark-whales) and dolphins practically swimming on the beach. Manta rays, 25 turtles, and other types of species were also observed. In Galapagos beaches, turtles have been 26 observed many more times than usual. The main plausible reason is the decrease in noise level. It is 27 recommended to take this unique opportunity, to construct a baseline data and information on physical, 28 chemical, biological, microbiological coastal oceanographic science, and from them to establish a proper 29 Coastal Zone Management based on beach description, water, and beach quality, human dimension, 30 and economic value indexes. This data and information construction should ideally be done before the 31 beaches are open.
Thu, 14 September 2017
ARTICLE | doi:10.20944/preprints201709.0058.v1
Subject: Earth Sciences, Geoinformatics Keywords: GIS; image classification; LiDAR; remote sensing; wetland indicator; global wetland inventory; wetland mapping
Online: 14 September 2017 (17:25:27 CEST)
Wetlands are recognized as one of the world’s most valuable natural resources. With the increasing world population, human demands on wetland resources for agricultural expansion and urban development continue to increase. In addition, global climate change has pronounced impacts on wetland ecosystems through alterations in hydrological regimes. To better manage and conserve wetland resources, we need to know the distribution and extent of wetlands and monitor their dynamic changes. Wetland maps and inventories can provide crucial information for wetland conservation, restoration, and management. Geographic Information System (GIS) and remote sensing technologies have proven to be useful for mapping and monitoring wetland resources. Recent advances in geospatial technologies have greatly increased the availability of remotely sensed imagery with better and finer spatial, temporal, and spectral resolution. This chapter presents an introduction to the uses of GIS and remote sensing technologies for wetland mapping and monitoring. A case study is presented to demonstrate the use of high-resolution light detection and ranging (LiDAR) data and aerial photographs for mapping prairie potholes and surface hydrologic flow pathways.
Wed, 9 October 2019
ARTICLE | doi:10.20944/preprints201910.0094.v1
Subject: Earth Sciences, Palaeontology Keywords: aquatic reptiles; plesiosaurs; pliosaurs; swim kinematics; Strouhal numbers
Online: 9 October 2019 (08:05:38 CEST)
Analysis of plesiosaur swim dynamics by means of a digital 3D armature (wireframe “skeleton”) of a pliosauromorph (“Ava”) demonstrates that: 1, plesiosaurs used all four flippers for primary propulsion; 2, plesiosaurs utilized all four flippers simultaneously; 3, respective pairs of flippers of Plesiosauridae, front and rear, traveled through distinctive, separate planes of motion, and; 4, the ability to utilize all four paddles simultaneously allowed these largely predatory marine reptiles to achieve a significant increase in acceleration and speed, which, in turn, contributed to their sustained dominance during the Mesozoic.
Fri, 3 February 2017
ARTICLE | doi:10.20944/preprints201612.0091.v2
Subject: Earth Sciences, Geology Keywords: reanalysis climate data; hydrologic modeling; comparative analysis
Online: 3 February 2017 (03:50:07 CET)
Large-scale hydrological modeling in China is challenging given the sparse meteorological stations and large uncertainties associated with atmospheric forcing data.Here we introduce the development and use of the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) in the Heihe River Basin(HRB) for improving hydrologic modeling, by leveraging the datasets from the China Meteorological Administration Land Data Assimilation System (CLDAS)(including climate data from nearly 40000 area encryption stations, 2700 national automatic weather stations, FengYun (FY) 2 satellite and radar stations). CMADS uses the Space Time Multiscale Analysis System (STMAS) to fuse data based on ECWMF ambient field and ensure data accuracy. In addition, compared with CLDAS, CMADS includes relative humidity and climate data of varied resolutions to drive hydrological models such as the Soil and Water Assessment Tool (SWAT) model. Here, we compared climate data from CMADS, Climate Forecast System Reanalysis (CFSR) and traditional weather station (TWS) climate forcing data and evaluatedtheir applicability for driving large scale hydrologic modeling with SWAT. In general, CMADS has higher accuracy than CFRS when evaluated against observations at TWS; CMADS also provides spatially continuous climate field to drive distributed hydrologic models, which is an important advantage over TWS climate data, particular in regions with sparse weather stations. Therefore, SWAT model simulations driven with CMADS and TWS achieved similar performances in terms of monthly and daily stream flow simulations, and both of them outperformed CFRS. For example, for the three hydrological stations (Ying Luoxia, Qilian Mountain, and ZhaMasheke) in the HRB at the monthly and daily Nash-Sutcliffe efficiency ranges of 0.75-0.95 and 0.58-0.78, respectively, which are much higher than corresponding efficiency statistics achieved with CFSR (monthly: 0.32-0.49 and daily: 0.26 – 0.45). The CMADS dataset is available free of charge and is expected to a valuable addition to the existing climate reanalysis datasets for deriving distributed hydrologic modeling in China and other countries in East Asia.
Tue, 13 April 2021
ARTICLE | doi:10.20944/preprints202104.0327.v1
Subject: Earth Sciences, Atmospheric Science Keywords: COVID-19; Medical waste; Environmental impac; China
Online: 13 April 2021 (09:09:57 CEST)
COVID-19 greatly challenges human beings in the health sector and leaves behind a large amount of medical waste that poses many potential threats to the environment. In this paper, we compiled relevant data released by official agencies and the media, and conducted data supplementation based on previous studies to calculate the net value of medical waste production in Hubei Province during COVID-19 with the help of a neural network model. Then, we reviewed the data related to the environmental impact of medical waste per unit and designed four scenarios to estimate the environmental impact of new medical waste generated during the epidemic. The results showed that at a medical waste generation rate of\ 0.\ 5\ kg/(\ bed\ \cdot\ d) COVID-19 resulted in a net increase in medical waste volume of about 3366.99 tons in Hubei Province. In the four scenario assumptions, if the medical waste brought by COVID-19 is completely incinerated, it will have a large impact on the air quality. If it is disposed by distillation sterilization, it will produce a large amount of wastewater and waste residue. Based on the results of the study, three policy recommendations are proposed in this paper: strict control of medical wastewater discharge, reduction and transformation of the emitted acidic gases, and attention to the emission of metallic nickel in exhaust gas and chloride in soil. These policy recommendations provide a scientific basis for controlling medical waste pollution.
Mon, 5 April 2021
ARTICLE | doi:10.20944/preprints202104.0120.v1
Subject: Earth Sciences, Environmental Sciences Keywords: Pre-COVID-19; Post-COVID-19; Secondary Schools; Water Demand; Groundwater; Nigeria
Online: 5 April 2021 (12:22:37 CEST)
The prevalence of corona virus and the novel COVID-19 disease in the entire globe has exacerbated different impact on socioeconomic spectrum in the world, including water use pattern. Thus a research was conducted to examine the comparative use of water during pre- and post-COVID-19 lockdown pattern among post-primary schools in Iwo, Osun State, Nigeria. A survey was conducted among fifteen schools which were randomly selected, but with eight public and seven private schools for the investigation. Both descriptive and inferential statistical techniques were used in data analysis. The results revealed that the major source of water to the schools investigated is ground water which is obtained through hand-dug wells and boreholes. It was further discovered that there was increase in water use during post-COVID-19 lockdown era as a result of the directive by the government that clean water should be provided for hand-washing by all schools regardless of the owner to curtail the spread of COVID-19 disease in the country. One sample t-test also revealed that there was a significant difference in water use at (p<0.01) level. It is recommended that the government and other stakeholders in water sector to ensure that all-time and non-seasonal dependent source of water be provided rather than ground water source which is susceptible to variations in water yields from seasonal variations. This will enable continuous clean water supply, for all purposes, including COVID-19 protocols.
Wed, 19 October 2016
ARTICLE | doi:10.20944/preprints201610.0078.v1
Subject: Earth Sciences, Environmental Sciences Keywords: calibration; validation; optical; instrument; processing; imagery; spatial; operational
Online: 19 October 2016 (10:59:29 CEST)
As part of the Copernicus programme of the European Union (EU), the European Space Agency (ESA) has developed and is currently operating the Sentinel-2 mission that is acquiring high spatial resolution optical imagery. This paper provides a description of the calibration activities and the current status of the mission products validation activities. Measured performances, from the validation activities, cover both Top-Of-Atmosphere (TOA) and Bottom-Of-Atmosphere (BOA) products. Results presented in this paper show the good quality of the mission products both in terms of radiometry and geometry and provide an overview on next mission steps related to data quality aspects.
Sat, 30 November 2019
ARTICLE | doi:10.20944/preprints201911.0393.v1
Subject: Earth Sciences, Geoinformatics Keywords: Sentinel-1; PolSAR; synthetic aperture radar; earth observation; SNAP
Online: 30 November 2019 (11:39:51 CET)
Sentinel-1 SAR data preprocessing is essential for several earth observation applications, including land cover classification, change detection, vegetation monitoring, urban growth, natural hazards, etc. The information can be extracted from the 2x2 covariance matrix [C2] of Sentinel-1 dual-pol (VV-VH) acquisitions. To generate the covariance matrix from Sentinel-1 single look complex (SLC) data, several preprocessing steps are required. The ESA SNAP S-1 toolbox can be used to preprocess the data to generate a [C2] matrix. The polarimetric analysis in respective application fields often starts with the covariance matrix. However, due to limited availability of Sentinel-1 SLC data preprocessing workflow standards for polarimetric applications in contemporary research methods, downstream applications unable to comply with these workflows directly. In this paper, we propose a couple of generic practices to preprocess Sentinel-1 SLC data in SNAP S-1 toolbox, which would be beneficial for the radar remote sensing user community.
Tue, 11 July 2017
REVIEW | doi:10.20944/preprints201707.0020.v1
Subject: Earth Sciences, Geology Keywords: thin-skinned tectonics; thick-skinned tectonics; structural geology; structure of mountain ranges; fold-and-thrust belts; décollement; nappe stacking; continent-continent collision; subduction; basin inversion
Online: 11 July 2017 (08:12:50 CEST)
This paper gives an overview of the large-scale tectonic styles encountered in orogens worldwide. Thin-skinned and thick-skinned tectonics represents two end member styles recognized in mountain ranges. A thick-skinned tectonic style is typical for margins of continental plates. Thick-skinned style including the entire crust and possibly the lithospheric mantle are associated with intracontinental contraction. Delamination of subducting continental crust and horizontal protrusion of upper plate crust into the opening gap occurs in the terminal stage of continent-continent collision. Continental crust thinned prior to contraction is likely to develop relatively thin thrust sheets of crystalline basement. A true thin-skinned type requires a detachment layer of sufficient thickness. Thickness of the décollement layer as well as the mechanical contrast between décollement layer and detached cover control the style of folding and thrusting within the detached cover units. In subduction related orogens, thin- and thick-skinned deformation may occur several hundreds of kilometers from the plate contact zone. Basin inversion resulting from horizontal contraction may lead to the formation of basement uplifts by the combined reactivation of pre-existing normal faults and initiation of new reverse faults. In composite orogens thick-skinned and thin-skinned structures evolve with a pattern where nappe stacking propagates outward and downward.
Wed, 14 March 2018
REVIEW | doi:10.20944/preprints201803.0097.v1
Subject: Earth Sciences, Environmental Sciences Keywords: UAS; remote sensing; environmental monitoring; precision agriculture; vegetation indices; soil moisture; river monitoring
Online: 14 March 2018 (02:38:42 CET)
Environmental monitoring plays a central role in diagnosing climate and management impacts on natural and agricultural systems, enhancing the understanding hydrological processes, optimizing the allocation and distribution of water resources, and assessing, forecasting and even preventing natural disasters. Nowadays, most monitoring and data collection systems are based upon a combination of ground-based measurements, manned airborne sensors or satellite observations. These data are utilized in describing both small and large scale processes, but have spatiotemporal constraints inherent to each respective collection system. Bridging the unique spatial and temporal divides that limit current monitoring platforms is key to improving our understanding of environmental systems. In this context, Unmanned Aerial Systems (UAS) have considerable potential to radically evolve environmental monitoring. UAS-mounted sensors offer an extraordinary opportunity to bridge the existing gap between field observations and traditional air- and space-borne remote sensing, by providing not just high spatial detail over relatively large areas in a cost-effective way, but as importantly providing an entirely new capacity for enhanced temporal retrieval. As well as showcasing recent advances in the field, there is also a need to identify and understand the potential limitations of UAS technology. For these platforms to reach their monitoring potential, a wide spectrum of unresolved issues and applications specific challenges require focused community attention. Indeed, to leverage the full potential of UAS-based approaches, sensing technologies, measurement protocols, post-processing techniques, retrieval algorithms and evaluations techniques need to be harmonized. The aim of this paper is to provide a comprehensive general overview of the existing research on studies and applications of UAS in environmental monitoring in order to suggest users and researchers on future research directions, applications, developments and challenges.
Sun, 19 April 2020
ARTICLE | doi:10.20944/preprints202004.0316.v1
Subject: Earth Sciences, Environmental Sciences Keywords: Precision farming; Crop type mapping; Digital agriculture; Sentinel-2; Random Forest; SVM; Field boundaries; Canny; Simple non-iterative clustering
Online: 19 April 2020 (03:14:37 CEST)
Crop type and field boundary mapping enable cost-efficient crop management on the field scale and serve as the basis for yield forecasts. Our study uses a data set with crop types and corresponding field borders from the federal state of Bavaria, Germany, as documented by farmers from 2016 to 2018. The study classified corn, winter wheat, barley, sugar beet, potato, and rapeseed as the main crops grown in Upper Bavaria. Corresponding Sentinel-2 data sets include the normalised difference vegetation index (NDVI) and raw band data from 2016 to 2018 for each selected field. The influences of clouds, raw bands, and NDVI on crop type classification are analysed, and the classification algorithms, i.e., support vector machine (SVM) and random forest (RF), are compared. Field boundary detection and extraction are based on non-iterative clustering and a newly developed procedure based on Canny edge detection. The results emphasise the application of Sentinel’s raw bands (B1–B12) and RF, which outperforms SVM with an accuracy of up to 94%. Furthermore, we forecast data for an unknown year, which slightly reduces the classification accuracy. The results demonstrate the usefulness of the proof-of-concept and its readiness for use in real applications.
Wed, 14 March 2018
ARTICLE | doi:10.20944/preprints201803.0108.v1
Subject: Earth Sciences, Geoinformatics Keywords: Forest fire danger index; MODIS; MOD11; MOD09; MOD14
Online: 14 March 2018 (15:38:35 CET)
Forest fire is a major ecological disaster, which has economic, social and environmental impacts on humans and also causes the loss of biodiversity. Forest officials issue the warnings to the public on the basis of fire danger index classes. There is no fire danger index for the country India due to the sparsely distributed meteorological stations. Previous studies suggest that Static Fire Danger Index (SFDI) as well as Dynamic Fire Danger Index (DFDI) have been derived from the satellite datasets. In this study, we have made an attempt to integrate both the Static and Dynamic fire danger indices and also used the Near Real Time (NRT) data sets that can be available for download through NASA FTP server after one hour of the satellite overpass. In this study, DFDI has been calculated from the MODIS Terra NRT Land Surface Temperature (MOD11_L2) and MODIS TERRA NRT surface reflectance MOD09. Finally, The Forest Fire Danger Index (FFDI) has been developed from the static and dynamic fire danger indices by the additive model and the overall accuracy was around 81.27%. Thus, the FFDI has been useful to predict the fire danger accurately and can be useful anywhere, where the meteorological stations are un-available.
Tue, 4 July 2017
ARTICLE | doi:10.20944/preprints201707.0004.v1
Subject: Earth Sciences, Environmental Sciences Keywords: life cycle analysis, dogs; cats; carbon footprint; environmental pawprint
Online: 4 July 2017 (16:00:10 CEST)
Mexico´s inhabitants have approximately 7 million dogs and cats as pets, of which there is no accurate information about their environmental impacts as a result of their feeding and comfort requirements. The objective of this study is to compare the environmental footprint between a dog and a cat in a family environment. For this purpose, a life cycle analysis was performed including, among other factors, its feeding and waste management in one year of life. Different environmental indicators including the carbon footprint were considered. It was found that the equivalent CO2 emission of a dog is twice that estimated for a domestic cat and that the main contribution is due to the food production. The ecological footprint that is generated when satisfying the requirements for pet´s well-being impacts in the environment contributes primarily to the carbon footprint.
Tue, 28 August 2018
ARTICLE | doi:10.20944/preprints201808.0352.v2
Subject: Earth Sciences, Geoinformatics Keywords: artificial intelligence; color naming; color constancy; cognitive science; computer vision; object-based image analysis (OBIA); physical and statistical data models; radiometric calibration; semantic content-based image retrieval; spatial topological and spatial non-topological information components
Online: 28 August 2018 (07:57:02 CEST)
The European Space Agency (ESA) defines as Earth observation (EO) Level 2 information product a single-date multi-spectral (MS) image corrected for atmospheric, adjacency and topographic effects, stacked with its data-derived scene classification map (SCM), whose thematic map legend includes quality layers cloud and cloud-shadow. ESA EO Level 2 product generation is an inherently ill-posed computer vision (CV) problem never accomplished to date in operating mode by any EO data provider at the ground segment. Herein, it is considered: (I) necessary not sufficient pre-condition for the yet-unaccomplished dependent problems of semantic content-based image retrieval (SCBIR) and semantics-enabled information/knowledge discovery (SEIKD) in multi-source EO big data cubes. (II) Synonym of EO Analysis Ready Data (ARD) format. (III) Equivalent to a horizontal policy for background developments in Space Economy 4.0. In compliance with the GEO-CEOS Quality Assurance Framework for EO Calibration/Validation guidelines, to contribute toward filling an analytic and pragmatic information gap from multi-sensor EO big data to timely, comprehensive and operational EO value-adding information products and services, this work presents an innovative AutoCloud+ CV software toolbox for cloud and cloud-shadow quality layer detection in ESA EO Level 2 product. In vision, spatial information dominates color information. Inspired by this true-fact, the inherently ill-posed AutoCloud+ CV software was conditioned, designed and implemented to be “universal”, meaning fully automated (no human-machine interaction is required), near real-time, robust to changes in input data and scalable to changes in MS imaging sensor’s spatial and spectral resolution specifications.
Thu, 29 August 2019
ARTICLE | doi:10.20944/preprints201908.0313.v1
Subject: Earth Sciences, Environmental Sciences Keywords: community empowerment; springs; forest revegetation; Arjuna mount; soil and geographical conditions; plants vegetation profile
Online: 29 August 2019 (17:17:32 CEST)
The research objectives were (1) to examine the determinants of community empowerment towards the revegetation of Arjuna mount forests; (2) assessing the influence of geography and soil conditions on the revegetation of Arjuna mount forests; (3) reviewing the effect of Arjuna mount forest revegetation on the preservation of spring water sources and (4) formulate a model of community empowerment around the forest based on revegetation of Arjuna mount and preservation of the area around the springs. The method used was descriptive method. While based on the techniques and tools used to research, the author uses the survey method to obtain facts that occur in the research area, namely in the area around the spring of the Kedunglarangan and Gumandar Prigen watersheds, Pasuruan Regency. Data obtained in the field are then processed and analyzed using GIS, ArcView 3.3 and Google Earth programs. The study population covering the community around the forest and springs, who lived in three villages, namely Leduk, Jatiarjo and Dayurejo village, Pasuruan, East Java-Indonesia. Data obtained from respondents with questionnaires and analyzed using SEM (structural equation modeling), to find out a general description of respondents' responses about community participation in the preservation of Arjuna mount forest. The results showed that (1) human resources, economic, social, local institutional factors, facilities and infrastructure had a very significant effect on forest revegetation; (2) geography and land variables have a significant effect on forest revegetation; (3) forest revegetation variables have a significant effect on the preservation of springs; and (4) The development of human resources, economic, local institutional, facilities and infrastructure in the community around the forest was a relevant model for the success of forest revegetation and the preservation of springs in Arjuna mount.
Tue, 17 December 2019
ARTICLE | doi:10.20944/preprints201912.0226.v1
Subject: Earth Sciences, Environmental Sciences Keywords: Trend Analysis; Non-parametric trend tests; Mann-Kendall; Modified Mann-Kendall; Climate Change; modifiedmk; trendchange
Online: 17 December 2019 (10:04:35 CET)
Daily rainfall data was collected for the arid district of Ananthapuramu, Andhra Pradesh state, India from 1981 to 2016 at the sub-district level and aggregated to monthly, annual and seasonal rainfall totals and the number of rainy days. The objective of this study is to evaluate the homogeneity, trend, and trend change points in the rainfall data. After quality checks and homogeneity analysis, a total of 27 rain gauge locations were considered for trend analysis. A serial correlation test was applied to all the time series to identify serially independent series. Non-Parametric Mann-Kendall test and Spearman’s rank correlation tests were applied to serially independent series. The magnitude of the trend was calculated using Sen’s slope method. For the data influenced by serial correlation, various modified versions of Mann-Kendall tests (Pre-Whitening, Trend Free Pre-Whitening, Bias Corrected Pre-Whitening and two variants of Variance Correction Approaches) were applied. A significant increasing summer rainfall trend is observed in 6 out of 27 stations. Significant decreasing trends are observed at two stations in the south-west monsoon season and at two stations in the north-east monsoon season. To identify the trend change-points in the time series, distribution-free Cumulative SUM test and sequential Mann-Kendall tests were applied. Two open-source library packages were developed in R language namely, ‘modifiedmk’ and ‘trendchange’ to implement the statistical tests mentioned in this paper. The study will benefit water resource management, drought mitigation, socio-economic development and sustainable agricultural planning in the region.
Sun, 8 December 2019
ARTICLE | doi:10.20944/preprints201912.0106.v1
Subject: Earth Sciences, Space Science Keywords: unmanned aerial vehicle; undergraduate education; remote sensing; surveying and mapping
Online: 8 December 2019 (17:50:04 CET)
This work mainly discusses an innovative teaching platform on Unmanned Aerial Vehicle digital mapping for Remote Sensing (RS) education at Wuhan University, underlining the fast development of RS technology. Firstly, we introduce and we discuss the future development of the Virtual Simulation Experiment Teaching Platform for Unmanned Aerial Vehicle (VSETP-UAV). It includes specific topics such as the “Systems and function Design”, teaching and learning strategies, and experimental methods. This study shows that VSETP-UAV expands the usual content and training methods related to RS education, and creates a good synergy between teaching and research. The results also show that the VSETP-UAV platform is of high teaching quality producing excellent engineers, with a high international standard and innovative skill in the RS field. In particular, it develops students' practical skills with technical manipulations of dedicated hardware and software equipment (e.g., UAV) in order to assimilate quickly this particular topic. Therefore, students report that this platform is more accessible from an educational point-of-view than theoretical programs, with a quick way of learning basic concepts of RS. Finally, the proposed VSETP-UAV platform achieves high social influence, expanding the practical content and training methods of UAV based experiments, and providing a platform for cultivating high-quality national talents with internationally recognized topics related to emerging engineering education.
Wed, 3 August 2016
ARTICLE | doi:10.20944/preprints201608.0025.v1
Subject: Earth Sciences, Atmospheric Science Keywords: solar variability; NAO; ENSO; volcanic eruptions; multiple regression
Online: 3 August 2016 (05:54:22 CEST)
This work studies the role of natural factors mainly solar eleven-year cycle variability, and volcanic eruptions on two major modes of climate variability the North Atlantic Oscillation (NAO) and El Niño Southern Oscillation (ENSO) for around last 150 years period. The NAO is the primary factor to regulate Central England Temperature (CET) during winter throughout the period, though NAO is impacted differently by other factors in different time periods. Solar variability has a positive influence on NAO during 1978-1997, which is opposite before that period. Solar NAO lag relationship is also sensitive to the chosen times of reference. Such analyses raise a question about previously proposed mechanism and relationship related to the sun and NAO. The ENSO is seen to be influenced strongly by solar variability and volcanic eruptions in certain periods. This study observes a strong negative association between solar variability and ENSO before the 1950s, which is even opposite during the second half of 20th century. The period 1978-1997, when two strong eruptions coincided with active years of strong solar cycles, the ENSO, and volcanic eruptions suggested the stronger association. Here we show that the mean atmospheric state is important for understanding the connection between solar variability, the NAO and ENSO and associated mechanism.
Wed, 31 August 2016
REVIEW | doi:10.20944/preprints201608.0236.v1
Subject: Earth Sciences, Environmental Sciences Keywords: noise pollution; mechanical wood industries; equipment; control
Online: 31 August 2016 (09:03:57 CEST)
High level of noise is a disturbance to the human environment. Noise in industries is also an occupational hazard because of its attendant effects on workers’ health. Noise presents health and social problems in industrial operations, and the source is related to the machineries used in the industries. One of the unique features of the noise associated with wood machinery is the level of exposure and duration. Equipment used in a factory can be extremely loud. They can produce noise at decibels high enough to cause environmental health and safety concerns. The mechanically driven transport and handling equipment, cutting, milling, shaping and dust extractor installations in the wood industry generate noise. The sources of noise pollution have increased due to non-compliance with basic safety practices. The increased use of locally fabricated machine in the industry has increased the level of noise and vibration. The effects of industrial noise pollution as discussed include: increase in blood pressure; increased stress; fatigue; vertigo; headaches; sleep disturbance; annoyance; speech problems; dysgraphia, which means reading/learning impairment; aggression; anxiety and withdrawal. As presented in this paper, noise control techniques include; sound insulation, sound absorption, vibration damping and Vibration isolation.
ARTICLE | doi:10.20944/preprints201608.0237.v1
Subject: Earth Sciences, Environmental Sciences Keywords: AirMOSS; radar backscatter; P-band remote sensing; root zone; soil moisture profile; Richards’ equation
Online: 31 August 2016 (08:48:11 CEST)
P-band radar remote sensing applied during the Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS) mission has shown great potential for estimation of root zone soil moisture. When retrieving the soil moisture profile (SMP) from P-band radar, a mathematical function describing the vertical moisture distribution is required. Because only a limited number of observations are available, the number of free parameters of the mathematical model must not exceed the number of observed data. For example, a second order polynomial that contains 3 free parameters was presumed based on in-situ SMP data. The polynomial is currently parameterized based on 3 backscatter observations provided by AirMOSS (i.e. one frequency at three polarizations of HH, VV and HV). In this paper, a more realistic, physically-based SMP model containing 3 free parameters is derived based on a solution to Richards’ equation for unsaturated flow in soils. Evaluation of the new SMP model based on both numerical simulations and measured data revealed that it exhibits greater flexibility for fitting measured and simulated SMPs than the currently applied polynomial. It is also demonstrated that the new SMP model can be reduced to a second order polynomial at the expense of fitting accuracy.
Mon, 2 September 2019
CONCEPT PAPER | doi:10.20944/preprints201909.0016.v1
Subject: Earth Sciences, Geoinformatics Keywords: land cover; classification Spatial and temporal Analysis; forest cover; Google Earth Engine (GEE); MODIS; Landsat; NOAA AVHRR
Online: 2 September 2019 (04:51:15 CEST)
Fri, 5 October 2018
REVIEW | doi:10.20944/preprints201810.0098.v1
Subject: Earth Sciences, Environmental Sciences Keywords: flood prediction; machine learning; forecasting
Online: 5 October 2018 (11:52:28 CEST)
Floods are among the most destructive natural disasters, which are highly complex to model. The research on the advancement of flood prediction models has been contributing to risk reduction, policy suggestion, minimizing loss of human life and reducing the property damage associated with floods. To mimic the complex mathematical expressions of physical processes of floods, during the past two decades, machine learning (ML) methods have highly contributed in the advancement of prediction systems providing better performance and cost effective solutions. Due to the vast benefits and potential of ML, its popularity has dramatically increased among hydrologists. Researchers through introducing the novel ML methods and hybridization of the existing ones have been aiming at discovering more accurate and efficient prediction models. The main contribution is to demonstrate the state of the art of ML models in flood prediction and give an insight over the most suitable models. The literature where ML models are benchmarked through a qualitative analysis of robustness, accuracy, effectiveness, and speed have been particularly investigated to provide an extensive overview on various ML algorithms usage in the field. The performance comparison of ML models presents an in-depth understanding about the different techniques within the framework of a comprehensive evaluation and discussion. As the result, the paper introduces the most promising prediction methods for both long-term and short-term floods. Furthermore, the major trends in improving the quality of the flood prediction models are investigated. Among them, hybridization, data decomposition, algorithm ensemble, and model optimization are reported the most effective strategy in improvement of the ML methods. This survey can be used as a guideline for the hydrologists as well as climate scientists to assist them choosing the proper ML method according to the prediction task conclusions.
Mon, 19 December 2016
ARTICLE | doi:10.20944/preprints201612.0100.v1
Subject: Earth Sciences, Environmental Sciences Keywords: engineering barriers; bentonite clays; thermochemical treatments; montmorillonite; structure modification; adsorption properties
Online: 19 December 2016 (11:08:23 CET)
The paper discusses the mechanism of montmorillonite structure alteration and bentonites properties modification (on the example of samples from clay deposit Taganka, Kazakhstan) due to the thermochemical treatment (treatment with inorganic acid solutions at different temperatures, concentrations and reaction times). With the use of the suit of methods certain processes were distinguished: transformation of montmorillonite structure, which appears in the leaching of interlayer and octahedral cations, protonation of the interlayer and OH groups at octahedral sheets. Changes in the structure of the 2:1 layer of montmorillonite and its interlayer result in significant changes in the properties – reduction of cation exchange capacity and an increase of specific surface area. The results of the work showed that bentonite clays retain a significant portion of its adsorption properties even after the long term and intense thermochemical treatment (6M HNO3, 60°C, 108 hours)
Wed, 3 August 2016
REVIEW | doi:10.20944/preprints201608.0021.v1
Subject: Earth Sciences, Environmental Sciences Keywords: electrical and electronic waste; recycling; legislative frameworks; environmental management; landfilling
Online: 3 August 2016 (12:33:45 CEST)
Households and businesses are generating unprecedented levels of electrical and electronic wastes (e-waste), fueled by modernisation and rapid obsolescence. While the challenges imposed by e-waste are similar everywhere in the world, disparities in progress to deal with it exists; with developing nations such as South Africa lagging. The increase in e-waste generation increases the need to formulate strategies to manage it. This paper presents an overview of e-waste management on a global and South African scenarios with a specific case for Cathode Ray Tube (CRT) waste management practices in South Africa. CRTs present the biggest problem for recyclers and policy makers because they contain hazardous elements such as lead and antimony. Common disposal practices have been either landfilling or incineration. The research into the South African practices with regards to CRT waste management showed that there is still more to be done to effectively manage this waste stream. This is despite clear waste regulatory frameworks in the country. However, recent developments have placed e-waste as a priority waste stream, which should lead to intensified efforts in dealing with it. Overall, these efforts should aim to maximise diversion from landfilling and to create value-addition opportunities, leading to social and environmental benefits.
Mon, 18 July 2016
ARTICLE | doi:10.20944/preprints201607.0056.v1
Subject: Earth Sciences, Environmental Sciences Keywords: Land use change; urban sprawl; Logistic regression; Markov chain; Cellular automata; Gilan Province
Online: 18 July 2016 (11:53:16 CEST)
Although, promotion of urbanization culture in recent decades has made inevitable development of cities in the world, however, the development can be guided in a direction that leave, to the extent possible, minimum socioeconomic and environmental impacts. For this, it is required to first forecast auto-spreading orientation of cities and suburbs in rural areas over time and then avoid shapeless growth of cities. This paper is an attempt to develop a dynamic hybrid model based on logistic regression (LR), Markov chain (MC), and cellular automata (CA) for prediction of future urban sprawl in fast-growing cities. The model was developed using 12 widely-used urban development criteria, whose significant coefficient was determined by logistic regression, and validated by relative operating characteristic (ROC) analysis. The validated model was run in Guilan, a tourist province in northern Iran with a very high rate of urban development. For this, changes in the area of urban land use were detected over the period of 1989 to 2013 and then, future sprawl of the province was forecasted by the years 2025 and 2037. The analysis results revealed that the area of urban land use was increased by more than 1.7 % from 36012.5 ha in 1989 to 59754.8 ha in 2013, and the area of Caspian Hyrcanian forestland was reduced by 31628 ha. The results also predicted an alarming increase in the rate of urban development in the province by the years 2025 and 2037, during which urban land use is predicted to develop 0.9 % and 1.38 %, respectively. The development pattern is expected to be uneven and scattered, without following any particular direction. The development will occur close to the existing or newly-formed urban basements as well as around major roads and commercial areas. This development, if not controlled, will lead to the loss of 13863 ha of Hyrcanian forests and if the trend continues, 21013 ha of Hyrcanian forests and 20208 ha of Barren/open lands are expected to be destroyed by the year 2037. In general, the proposed model is an efficient tool for the support of urban planning decisions and facilitates the process of sustainable development of cities by providing decision-makers with an overview on future development of cities where the growth rate is very fast.
Wed, 30 January 2019
ARTICLE | doi:10.20944/preprints201901.0302.v1
Subject: Earth Sciences, Geoinformatics Keywords: interoperability; digital elevation model; Google Sketchup; geographical information systems-science; free and open source software
Online: 30 January 2019 (05:28:53 CET)
Data creation is often the only way for researchers to produce basic geospatial information for the pursuit of more complex tasks and procedures such as those that lead to the production of new data for studies concerning river basins, slope morphodynamics, applied geomorphology and geology, urban and territorial planning, detailed studies, for example, in architecture and civil engineering, among others. This exercise results from a reflection where specific data processing tasks executed in Google Sketchup (Pro version, 2018) can be used in a context of interoperability with Geographical Information Systems (GIS) software. The focus is based on the production of contour lines and Digital Elevation Models (DEM) using an innovative sequence of tasks and procedures in both environments (GS and GIS). It starts in Google Sketchup (GS) graphic interface, with the selection of a satellite image referring to the study area—which can be anywhere on Earth's surface; subsequent processing steps lead to the production of elevation data at the selected scale and equidistance. This new data must be exported to GIS software in vector formats such as Autodesk Design Web format—DWG or Autodesk Drawing Exchange format—DXF. In this essay the option for the use of GIS Open Source Software (gvSIG and QGIS) was made. Correcting the original SHP by removing “data noise” that resulted from DXF file conversion permits the author to create new clean vector data in SHP format and, at a later stage, generate DEM data. This means that new elevation data becomes available, using simple but intuitive and interoperable procedures and techniques which confgures a costless work flow.
Sun, 24 May 2020
ARTICLE | doi:10.20944/preprints202005.0403.v1
Subject: Earth Sciences, Environmental Sciences Keywords: zoonotic; corona virus; COVID-19; SARS; MERS; global health emergency; India; lockdown strategies
Online: 24 May 2020 (19:34:03 CEST)
Global emerge of zoonotic novel corona virus (COVID-19) became a pandemic and its effect to mankind is talk of the town now a days. This tiny, invisible enemy has affected every country in the world and almost every living directly or indirectly and nationwide complete lockdown has triggered a short-term environmental impact. Since 2003, corona virus came into existence in the form of Severe Acute Respiratory Syndrome (SARS) and more evolved Middle East Respiratory Syndrome (MERS) in 2012. This time, at the end of December 2019, outbreak of novel corona virus COVID-19 (also known as SARS-CoV2, nCoV-2019) draw attention as global health emergency. World Health Organization (WHO) report says that the outbreak of this virus is so immense, it has already affected 35,57,235 people and caused death to 2,45,150 people worldwide and 46,433 Indians got affected with 1568 death as on 5th May 2020 (2:00 am) and these numbers are increasing exponentially day by day. Virologist, micro-biologist and science community are hammering their head very hard to find out cure and vaccine against this powerful virus and to prevent mass demise of mankind. In order to curb the spread of COVID-19, Janta curfew on 22.03.2020 and nationwide complete lockdown was implemented in India for 21 days (phase-I, from 25.03.2020 to 14.04.2020) to stop community transmission of third stage, for 19 days (phase-II, 15.04.2020 to 03.05.2020) and 14 days (phase-III, 04.05.2020 to 17.05.2020) complete lockdown to minimize the community transmission effect. During complete lockdown and quarantine period a drastic change in Earth’s atmosphere, including reduction in emission of greenhouse gases, air pollution (~50% fall in air quality index), noise pollution, water pollution and solid waste pollution, have been recorded by government agencies as well as private agencies. In this paper we considered data of Janta curfew, phase-I and phase-II lockdown to link between geological and environmental aspect related to environmental impact due to emerge of COVID-19 and massive reduction in pollution level during complete lockdown in India. We propose future lockdown strategies to minimize the emission of greenhouse gas by ~100 Mt to ~200Mt (3.33% to 6.66%) of GHGtotal per year by 2-4 days per month nationwide lockdown or ~70 Mt to ~140 Mt (2.33% to 4.66%) of GHGtotal per year by 2-4 days per month complete lockdown of energy sectors only.
Mon, 7 November 2016
ARTICLE | doi:10.20944/preprints201611.0036.v1
Subject: Earth Sciences, Geoinformatics Keywords: multi-task learning; feature fusion; sparse representation; low-rank representation; scene classification
Online: 7 November 2016 (05:25:11 CET)
Scene classification plays an important role in the intelligent processing of high-resolution satellite (HRS) remotely sensed image. In HRS image classification, multiple features, e.g. shape, color, and texture features, are employed to represent scenes from different perspectives. Accordingly, effective integration of multiple features always results in better performance compared to methods based on a single feature in the interpretation of HRS image. In this paper, we introduce a multi-task joint sparse and low-rank representation model to combine the strength of multiple features for HRS image interpretation. Specifically, a multi-task learning formulation is applied to simultaneously consider sparse and low-rank structure across multiple tasks. The proposed model is optimized as a non-smooth convex optimization problem using an accelerated proximal gradient method. Experiments on two public scene classification datasets demonstrate that the proposed method achieves remarkable performance and improves upon the state-of-art methods in respective applications.
Fri, 18 November 2016
REVIEW | doi:10.20944/preprints201611.0101.v1
Subject: Earth Sciences, Environmental Sciences Keywords: biodiversity conservation, livelihood, co-management, stakeholder, law enforcement
Online: 18 November 2016 (15:20:07 CET)
Despite of being an exceptionally biodiversity rich country, the forest coverage of Bangladesh is declining at an alarming rate. Declaration and management of protected areas in this regard is one of the efforts from government side to tackle the loss of biodiversity. The limited numbers of forest-protected areas (FPA), established to conserve the dwindling forest biodiversity of the country with high pressure on them for timber, non-timber forest products, and fuelwood - makes their management challenging. Moreover, most of the FPAs of the country declared only in the recent decades with very limited infrastructure, manpower and policy support for monitoring and governance. Some people-centred approaches for the management of FPAs and alternative livelihood and income generation subsidies although made available through a few project interventions, their number are still inadequate and performance remains less than satisfactory. This chapter provides a critical review of the FPAs of Bangladesh looking at their role in biodiversity conservation, management challenges, and key lessons from previous management interventions with recommendations for the future. It has been revealed that the FPA system of Bangladesh still poorly represents the diverse forest ecosystems with relatively small forest size and lack of corridors for the movement of wildlife. There are ample opportunities to render co-management of FPAs an effective strategy to minimize the conflicts in FPAs management in the country. It is, however, important to ensure the access of local forest-dependent people to different alternative income generating options that may adequately support their livelihoods.
Tue, 1 November 2016
ARTICLE | doi:10.20944/preprints201611.0006.v1
Subject: Earth Sciences, Environmental Sciences Keywords: biomarker; environmental assessment; elemental competition; bioconcentration factor; heavy metal absorption
Online: 1 November 2016 (09:34:35 CET)
Soil pollution has been estimated using soil analysis and leaching test. These methods could show different data from reality due to effects by soil properties such as grain size and mineral composition. Therefore, this study advocates a new assessment and monitoring method of heavy metal polluted soil using fruticose lichens. Lichens growing at abandoned mine sites and unpolluted areas in southwest Japan and their substrata were analyzed using inductively coupled plasma-mass spectrometry and X-ray fluorescence spectrometry to clarify the relationships between the heavy metal concentrations in lichens and soils, and their heavy metal absorption properties. Concentrations of Cu, Zn, As, and Pb in the lichens were positively correlated with those in the soil. Variability of the relationships did not depend on the lichen species, location, habitat, or the conditions of soils. The analyzed lichens had neither competitive nor antagonistic properties in their heavy metal absorption, which make them good biomarkers of heavy metal pollution of soil. The distribution maps of average heavy metal concentrations at each sampling region detected almost all of the Cu, Zn, and As pollution of soil. Therefore, lichens could be used in practical applications to assess Cu, Zn, and As pollution of soils.
Sat, 6 August 2016
ARTICLE | doi:10.20944/preprints201608.0059.v1
Subject: Earth Sciences, Environmental Sciences Keywords: riparian zone; transitional environment; riparian forest buffer; spatial modelling; mapping; spatial ecology; ecosystem functions
Online: 6 August 2016 (06:07:11 CEST)
Riparian zones represent ecotones between terrestrial and aquatic ecosystems and are of utmost importance to biodiversity and ecosystem functions. Modelling/mapping of these valuable and fragile areas is needed for an improved ecosystem management, based on an accounting of changes and on monitoring of their functioning in time. In Europe, the main legislative driver behind this goal is the European Commission’s Biodiversity Strategy to 2020, on one hand aiming at reducing biodiversity loss, on the other hand enhancing ecosystem services by 2020, and restoring them as far as feasible. A model, based on Earth Observation data, including Digital Elevation Models, hydrological, soil, land cover/land use data, and vegetation indices is employed in a multi-modular and stratified approach, based on fuzzy logic and object based image analysis, to delineate potential, observed and actual riparian zones. The approach is designed in an open modular way, allowing future modifications and repeatability. The results represent a first step of a future monitoring and assessment campaign for European riparian zones and their implications on biodiversity and on ecosystem functions and services. Considering the complexity and the enormous extent of the area, covering 39 European countries, including Turkey, the level of detail is unprecedented. Depending on the accounting modus, 0.95%–1.19% of the study area can be attributed as actual riparian area (considering Strahler’s stream orders 3-8, based on the Copernicus EU-Hydro dataset), corresponding to 55,558–69.128 km2. Similarly depending on the accounting approach, the potential riparian zones are accounted for about 3-5 times larger. Land cover/land use in detected riparian areas was mainly of semi-natural characteristics, while the potential riparian areas are predominately covered by agriculture, followed by semi-natural and urban areas.
Wed, 25 March 2020
Subject: Earth Sciences, Environmental Sciences Keywords: 2011-2020 Strategic Plan for Biodiversity; biodiversity outcomes; indicators; management effectiveness; other effective area-based conservation measures; post-2020; protected areas
Online: 25 March 2020 (04:31:56 CET)
Work has begun in earnest to formulate a post-2020 Global Biodiversity Framework which will outline the vision and targets for the next decade of biodiversity conservation and beyond. However, the performance of the 2011-2020 Strategic Plan for Biodiversity suggests that even a meaningful target can fail to deliver if not accompanied by fit-for-purpose indicators. Here we provide a review of how ‘protected area’ effectiveness was addressed in the 2011-2020 plan and based on this, provide recommendations for fit-for-purpose indicators that will measure how such efforts contribute to the conservation of biodiversity. Indicators need to be built on quantitative data from site-level biodiversity monitoring of species and ecosystems combined with measurements of the state of nature in near-time, informed by remote-sensed products and other technologies. Additionally, indicators need to capture whether the essential elements of good management are in place including the identification of ecological values, threats, and objectives, equitable governance, and sufficient management resources and capacity. These fit-for-purpose indicators will require multilateral collaboration to galvanize support for, and resources to develop, the necessary infrastructure to collate and store information from countries.
Wed, 2 November 2016
ARTICLE | doi:10.20944/preprints201611.0019.v1
Subject: Earth Sciences, Atmospheric Science Keywords: satellite; rainfall; estimates; rain gauge; uncertainties; topography; seasonality; East Africa
Online: 2 November 2016 (09:25:04 CET)
Accurate and consistent rainfall observations are vital for climatological studies in support of better planning and decision making. However, estimation of accurate spatial rainfall is limited by sparse rain gauge distributions. Satellite rainfall products can thus potentially play a role in spatial rainfall estimation but their skill and uncertainties need to be under-stood across spatial-time scales. This study aimed at assessing the temporal and spatial performance of seven satellite products (TARCAT (Tropical Applications of Meteorology using SATellite and ground-based observations (TAMSAT) African Rainfall Climatology And Time series), Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), Tropical Rainfall Measuring Mission (TRMM-3B43), Climate Prediction Center (CPC) Morphing (CMORPH), the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks- Climate Data Record (PERSIANN-CDR), CPC Merged Analysis of Precipitation (CMAP) and Global Precipitation Climatology Project (GPCP) using gridded (0.05o) rainfall data over East Africa for 15 years(1998-2012). The products’ error distributions were qualitatively compared with large scale horizontal winds (850 mb) and elevation patterns with respect to corresponding rain gauge data for each month during the ‘long’ (March-May) and ‘short’ (October-December) rainfall seasons. For validation only rainfall means extracted from 284 rain gauge stations were used, from which qualitative analysis using continuous statistics of Root Mean Squared Difference, Standard deviations, Correlations, coefficient of determinations (from scatter plots) were used to evaluate the products’ performance. Results revealed rainfall variability dependence on wind flows and modulated by topographic influences. The products’ errors showed seasonality and dependent on rainfall intensity and topography. Single sensor and coarse resolution products showed lowest performance on high ground areas. All the products showed low skills in retrieving rainfall during ‘short’ rainfall season when orographic processes were dominant. CHIRPS, CMORPH and TRMM performed well, with TRMM showing the best performance in both seasons. There is need to reduce products’ errors before applications.
Sun, 5 February 2017
ARTICLE | doi:10.20944/preprints201702.0014.v1
Subject: Earth Sciences, Atmospheric Science Keywords: temperature; precipitation; ethiopia; mann kendall; climate variability
Online: 5 February 2017 (08:56:29 CET)
Long term Precipitation and temperature variations are one of the main determinants of climate variability of one’s area. The aim of this study is to determine trends variation in climatic elements of temperature and precipitation in the southern zone of Tigray regional state, Ethiopia. The station is assumed for the study of climatic records over southern zone of the region in detection for probable trends. The daily, monthly and annual precipitation totals and temperature observed at korem meteorological station were used for the period of 1981-2010 for Precipitation and 1985 – 2010 for minimum and maximum temperature. Summary of descriptive statistics and Mann Kendall test methods were employed for the observed data analysis to demonstrate any existence of possible trends. The main findings of the study indicated that the mean and maximum temperature had a general increasing trend; however, minimum temperature showed decreasing trend. In general annual temperature from 1985 – 2010 of the area showed a warming trend. Moreover analysis of the 30 years (1981-2010) annual precipitation showed a coefficient of variation ranging from 33.77 – 233 %. It indicated that the precipitation dissemination is not normal with large year to year variances.
Wed, 22 February 2017
ARTICLE | doi:10.20944/preprints201702.0080.v1
Subject: Earth Sciences, Environmental Sciences Keywords: ROS; snow; rain; flood; WRF; numerical weather forecast; energy balance; discharge estimation; early alert system
Online: 22 February 2017 (04:26:49 CET)
From June 18 to 19, 2013, the Ésera river in the Pyrenees, Northern Spain, caused widespread damage due to flooding as a result of torrential rains and sustained snowmelt. We estimate the contribution of snow melt to total discharge applying a snow energy balance to the catchment. Precipitation is derived from sparse local measurements and the WRF-ARW model over three nested domains, down to a grid cell size of 2 km. Temperature profiles, precipitation and precipitation gradient are well simulated, although with a possible displacement regarding the observations. Snowpack melting was correctly reproduced and verified in three instrumented sites, and according to satellite images. We found that the hydrological simulations agree well with measured discharge. Snowmelt represented 33% of total runoff during the main flood event and 23% at peak flow. The snow energy balance model indicates that most of the energy for snow melt during the day of maximum precipitation came from turbulent fluxes. This approach forecast correctly peak flow and discharge during normal conditions at least 24h in advance and could give an early warning of the extreme event 2.5 days before.
Mon, 31 October 2016
ARTICLE | doi:10.20944/preprints201610.0134.v1
Subject: Earth Sciences, Environmental Sciences Keywords: rice; water requirement; climate change; Penman-Monteith; CROPWAT
Online: 31 October 2016 (03:21:42 CET)
In this paper, Rice water requirement and irrigation water requirement in Amol agro meteorological Station in 2016-2045 are forecasted based on the projected meteorological data of Hadcm3 under A2 scenario. Rice water requirements are estimated by using crop coefficient approach. Reference evapotranspiration are calculated by FAO Penman-Monteith method. Moreover, the irrigation water requirements are simulated by calibrated CROPWAT model using the meteorological parameters. The results show that both crop water requirement and irrigation water requirement present downward trend in the future. In 2016-2045, the rice water requirement and irrigation water requirement decrease by more than 9.9% under A2 scenario, respectively. Furthermore, the precipitation rise may be the main reason for the decrease in crop water requirement, while significant decrease of irrigation water requirement should be attributed to combined action of rising precipitation and a slight increase in temperature.
Fri, 5 August 2016
ARTICLE | doi:10.20944/preprints201608.0048.v1
Subject: Earth Sciences, Geoinformatics Keywords: UAV remote sensing; power line inspection; dense matching; virtual photography; automatic detection of obstacles in power line corridor
Online: 5 August 2016 (08:07:23 CEST)
When the distance between an obstacle and a power line is less than the discharge distance, a discharge arc can be generated, resulting in interruption of power supplies. Therefore, regular safety inspections are necessary to ensure safe operations of power grids. Tall vegetation and buildings are the key factors threatening the safe operation of extra high voltage transmission lines within a power line corridor. Manual or LiDAR based-inspections are time consuming and expensive. To make safety inspections more efficient and flexible, a low-altitude unmanned aerial vehicle remote-sensing platform equipped with optical digital camera was used to inspect power line corridors. We propose a semi-patch matching algorithm based on epipolar constraints using both correlation coefficient and the shape of its curve to extract three dimensional (3D) point clouds for a power line corridor. Virtual photography was used to transform the power line direction from approximately parallel to the epipolar line to approximately perpendicular to epipolar line to improve power line measurement accuracy. The distance between the power lines and the 3D point cloud is taken as a criterion for locating obstacles within the power line corridor automatically. Experimental results show that our proposed method is a reliable, cost effective and applicable way for practical power line inspection, and can locate obstacles within the power line corridor with measurement accuracies better than ±0.5 m.
Sat, 6 August 2016
ARTICLE | doi:10.20944/preprints201608.0069.v1
Subject: Earth Sciences, Environmental Sciences Keywords: Rubber (Hevea brasiliensis) plantation; phenology; Xishuangbanna; Landsat; object-based approach; pixel-based approach
Online: 6 August 2016 (11:54:28 CEST)
Effectively mapping and monitoring rubber plantation is still changing. Previous studies have explored the potential of phenology features for rubber plantation mapping through a pixel-based approach (pixel-based phenology approach). However, in fragmented mountainous Xishuangbanna, it could lead to noises and low accuracy of resultant maps. In this study, we investigated the capability of an integrated approach by combining phenology information with an object-based approach (object-based phenology approach) to map rubber plantations in Xishuangbanna. Moderate Resolution Imaging Spectroradiometer (MODIS) data were firstly used to acquire the temporal profile and phenological features of rubber plantations and natural forests, which delineates the time windows of defoliation and foliation phases. Landsat images were then used to extract a phenology algorithm comparing three different approaches: pixel-based phenology, object-based phenology, and extended object-based phenology to separate rubber plantations and natural forests. The results showed that the two object-based approaches achieved higher accuracy than the pixel-based approach, having overall accuracies of 96.4%, 97.4%, and 95.5%, respectively. This study proved the reliability of a phenology-based rubber mapping in fragmented landscapes with a distinct dry/cool season using Landsat images. This study indicated that the object-based phenology approaches can effectively improve the accuracy of the resultant maps in fragmented landscapes.
Wed, 24 August 2016
ARTICLE | doi:10.20944/preprints201608.0202.v1
Subject: Earth Sciences, Environmental Sciences Keywords: HR satellite remote sensing; urban fabric vulnerability; UHI & heat waves; landsat & MODIS sensors; LST & urban heating; segmentation & objects classification; data mining; feature extraction & selection; stepwise regression & model calibration
Online: 24 August 2016 (10:19:40 CEST)
Densely urbanized areas, with a low percentage of green vegetation, are highly exposed to Heat Waves (HW) which nowadays are increasing in terms of frequency and intensity also in the middle-latitude regions, due to ongoing Climate Change (CC). Their negative effects may combine with those of the UHI (Urban Heat Island), a local phenomenon where air temperatures in the compact built up cores of towns increase more than those in the surrounding rural areas, with significant impact on the quality of urban environment, on citizens health and energy consumption and transport, as it has occurred in the summer of 2003 on France and Italian central-northern areas. In this context this work aims at designing and developing a methodology based on aero-spatial remote sensing (EO) at medium-high resolution and most recent GIS techniques, for the extensive characterization of the urban fabric response to these climatic impacts related to the temperature within the general framework of supporting local and national strategies and policies of adaptation to CC. Due to its extension and variety of built-up typologies, the municipality of Rome was selected as test area for the methodology development and validation. First of all, we started by operating through photointerpretation of cartography at detailed scale (CTR 1: 5000) on a reference area consisting of a transect of about 5x20 km, extending from the downtown to the suburbs and including all the built-up classes of interest. The reference built-up vulnerability classes found inside the transect were then exploited as training areas to classify the entire territory of Rome municipality. To this end, the satellite EO HR (High Resolution) multispectral data, provided by the Landsat sensors were used within a on purpose developed "supervised" classification procedure, based on data mining and “object-classification” techniques. The classification results were then exploited for implementing a calibration method, based on a typical UHI temperature distribution, derived from MODIS satellite sensor LST (Land Surface Temperature) data of the summer 2003, to obtain an analytical expression of the vulnerability model, previously introduced on a semi-empirical basis.
Thu, 4 August 2016
ARTICLE | doi:10.20944/preprints201608.0038.v1
Subject: Earth Sciences, Environmental Sciences Keywords: historical reconstruction; modeling; drinking water; water quality; VOC; epidemiological study; health study; Camp Lejeune
Online: 4 August 2016 (10:09:23 CEST)
A U.S. government health agency conducted epidemiological studies to evaluate whether exposures to drinking water contaminated with volatile organic compounds at U.S. Marine Corps Base Camp Lejeune, North Carolina, were associated with increased health risks to children and adults. These health studies required knowledge of contaminant concentrations in drinking water—at monthly intervals—delivered to family housing, barracks, and other facilities within the study area. Because concentration data were limited or unavailable during much of the period of contamination (1950s–1985), the historical reconstruction process was used to quantify estimates of monthly mean contaminant-specific concentrations. This paper integrates many efforts, reports, and papers into a synthesis of the overall approach to, and results from, a drinking-water historical reconstruction study. Results show that at the Tarawa Terrace water treatment plant (WTP) reconstructed (simulated) tetrachloroethylene (PCE) concentrations reached a maximum monthly average value of 183 micrograms per liter (ug/L) compared to a one-time maximum measured value of 215 ug/L and exceeded the U.S. Environmental Protection Agency’s current maximum contaminant level (MCL) of 5 ug/L during the period November 1957–February 1987. At the Hadnot Point WTP, reconstructed trichloroethylene (TCE) concentrations reached a maximum monthly average value of 783 ug/L compared to a one-time maximum measured value of 1,400 ug/L during the period August 1953–December 1984. The Hadnot Point WTP also provided contaminated drinking water to the Holcomb Boulevard housing area continuously prior to June 1972, when the Holcomb Boulevard WTP came on line (maximum reconstructed TCE concentration of 32 ug/L) and intermittently during the period June 1972–February 1985 (maximum reconstructed TCE concentration of 66 ug/L). Applying the historical reconstruction process to quantify contaminant-specific monthly drinking-water concentrations is advantageous for epidemiological studies when compared to using the classical exposed versus unexposed approach.
Thu, 5 January 2017
ARTICLE | doi:10.20944/preprints201701.0023.v1
Subject: Earth Sciences, Geoinformatics Keywords: Random forest classification; urban sprawl; spatial metrics; Renyi’s entropy; sustainability; land change modelling; remote sensing; urban growth model; Chennai
Online: 5 January 2017 (09:20:29 CET)
Urban sprawl propelled by rapid population growth leads to the shrinkage of productive agricultural lands and pristine forests in the suburban areas and, in turn, substantially alters ecosystem services. Hence, the quantification of urban sprawl is crucial for effective urban planning, and environmental and ecosystem management. Like many megacities in fast growing developing countries, Chennai, the capital of Tamilnadu and one of the business hubs in India, has experienced extensive urban sprawl triggered by the doubling of total population over the past three decades. We employed the Random Forest (RF) classification on Landsat imageries from 1991, 2003, and 2016, and computed spatial metrics to quantify the extent of urban sprawl within a 10km suburban buffer of Chennai. The rate of urban sprawl was quantified using Renyi’s entropy, and the urban extent was predicted for 2027 using land-use and land-cover change modeling. A 70.35% increase in urban areas was observed for the suburban periphery of Chennai between 1991 and 2016. The Renyi’s entropy value for year 2016 was ≥ 0.9, exhibiting a two-fold rate of urban sprawl. The spatial metrics values indicate that the existing urban areas of Chennai became denser and the suburban agricultural, forests and barren lands were transformed into fragmented urban settlements. The forecasted urban growth for 2027 predicts a conversion of 13670.33ha (16.57 % of the total landscape) of existing forests and agricultural lands into urban areas with an associated increase in the entropy value of 1.7. Our findings are relevant for urban planning and environmental management in Chennai and provide quantitative measures for addressing the social-ecological consequences of urban sprawl and the protection of ecosystem services.
Tue, 26 June 2018
ARTICLE | doi:10.20944/preprints201806.0414.v1
Subject: Earth Sciences, Geophysics Keywords: Montenegro; cadastre; geography; geodesy; geoinformatics; syllabus for cartography; cartographical heritage
Online: 26 June 2018 (12:07:05 CEST)
This paper deals with an analysis of cartographical studies, the real estate cadastre, and its practical implementation, as well as the introduction of cartography into different education modules in university-level studies in Montenegro. There is a discussion of the development, production, and creativity in the fields of cartography and real estate cadastre over time, cartographical projection, scientific results, and recent changes such as advanced computer- and satellite-based technologies, GIS, cartographical visualization, and digital cartography. The impact of these changes on cartographical studies at the University of Montenegro is considered. Particular attention is given to analyses of cartography and the cadastre in institutions, and their connection with the development of cartography teaching modules of Geography, Geodesy and Geoinformatics at the University of Montenegro. The integrated analysis also covers the results of the questionnaire and the significance of the geo-topographical and cartographical heritage of Montenegro, with the aim of carrying these out. It can be seen that the tasks solved by using maps have tended to become more complex and that the cartographical methods employed in this have been always directed towards Montenegro’s most prominent and most urgent problems, including those that appear in the area of education.
Wed, 29 May 2019
ARTICLE | doi:10.20944/preprints201905.0359.v1
Subject: Earth Sciences, Environmental Sciences Keywords: Adaptation; climate change; composite indices; resilience; livelihoods; adaptation
Online: 29 May 2019 (16:43:50 CEST)
The missing link between cross-sectoral resource utilisation and management, and full-scale adoption of the water-energy-food (WEF) nexus has been lack of analytical tools to support policy and decision-making. This paper defined WEF nexus sustainability indicators and developed a methodology to calculate composite indices to facilitate WEF nexus performance, monitoring and evaluation. WEF nexus indicators were integrated through the Analytic Hierarchy Process (AHP) in a multi-criteria decision-making (MCDM). Data were normalised to determine composite indices. The method established quantitative relationships among WEF nexus sectors to indicate resource utilisation and performance over time, using South Africa as a case study. A spider graph of normalised indices was used to illustrate WEF nexus indicator performance and inter-relationships, providing a synopsis of the level of interactions and inter-connectedness of WEF nexus sectors. The shape of the spider graph is determined by the level of the interdependencies and interactions among the WEF nexus sectors, whose management is viewed either as sustainable or unsustainable depending on the classification of the developed integrated index. The spider graph produced for South Africa shows an over emphasis on food self-sufficiency and water productivity at the expense of other sectors, which results from the sectoral approach in resource management. Although the calculated integrated index of 0.203 for South Africa is classified as lowly sustainable, the emphasis is on the quantitative relationships among the indicators and on how to improve them to achieve sustainability. The developed method provides evidence to decision makers, indicating priority areas for intervention. The analytical model is another niche area for the WEF nexus, as it is now capable to evaluate synergies and trade-offs in a holistic way to improve efficiency and productivity in resource use and management for sustainable development.
Thu, 17 January 2019
ARTICLE | doi:10.20944/preprints201901.0173.v1
Subject: Earth Sciences, Geoinformatics Keywords: third definition of fractal; fractal or living geometry; wholeness; head/tail breaks (ht-index); scaling law
Online: 17 January 2019 (03:30:08 CET)
As noted in the introductory quotation, an ideal map was long ago seen as the map of the map, the map of the map, of the map, and so on endlessly. This recursive perspective on maps, however, has received little attention in cartography. Cartography, as a scientific discipline, is essentially founded on Euclidean geometry and Gaussian statistics, which deal with respectively regular shapes, and more or less similar things. It is commonly accepted that geographic features – such as rivers, cities, streets and building – are not regular and that the Earth’s surface is full of fractal or scaling or living phenomena with far more small things than large ones at different levels of scale. This paper argues for a new paradigm in mapping, based on fractal or living geometry and Paretian statistics, and – more critically – on the new conception of space, conceived and developed by Christopher Alexander, that space is neither lifeless nor neutral, but a living structure capable of being more living or less living. The fractal geometry is not limited to Benoit Mandelbrot’s framework, but is extended towards Christopher Alexander’s living geometry and based upon the third definition of fractal: A set or pattern is fractal if the scaling of far more small things than large ones recurs multiple times. Paretian statistics deals with far more small things than large ones, so it differs fundamentally from Gaussian statistics, which deals with more or less similar things. Under the new paradigm, I make several claims about maps and mapping: (1) Topology of geometrically coherent things – in addition to that of geometric primitives – enables us to see a scaling or fractal or living structure; (2) Under the third definition, all geographic features are fractal or living, given the right perspective and scope; (3) Exactitude is not truth – to paraphrase Henri Matisse – but the living structure is; and (4) Töpfer’s law is not universal, but scaling law is. All these assertions are supported by evidence, drawn from a series of previous studies. This paper demands a monumental shift in perspective and thinking from what we are used to on the legacy of cartography and GIS.
Sun, 25 December 2016
ARTICLE | doi:10.20944/preprints201612.0125.v1
Subject: Earth Sciences, Atmospheric Science Keywords: human thermal comfort-discomfort; Fanger’s model; PMV; PPD
Online: 25 December 2016 (08:48:27 CET)
The Predicted Mean Vote (PMV) and the Predicted Percentage of Dissatisfied (PPD) indices are used to assess the indoor environment in terms of human thermal comfort-discomfort. In this study, an experimental combined objective and subjective investigation of thermal comfort perception has been performed in students between 16-18 years old, in a non-air-conditioned school building. The objective approach included instrumentation measurements and data processing according to ISO 7730, whereas, the subjective one was based on answers collection following ISO 10551. The study is mainly devoted to the verification of Fanger’s approach in a building, in free running conditions, under a mild (moderate) climate.The comparison between instrumentation data and questionnaire results presented an underestimation of the mean vote, predicting a cooler sensation than the actual one.
Sat, 10 December 2016
ARTICLE | doi:10.20944/preprints201612.0059.v1
Subject: Earth Sciences, Environmental Sciences Keywords: water footprint; bottled water; groundwater; Africa; water resource management; urban
Online: 10 December 2016 (08:41:51 CET)
Packaged water consumption has grown rapidly in urban areas of many low and middle income countries, but particularly in Ghana. However, the sources of water used by this growing packaged water industry and its implications for water resource management and transport-related environmental impacts have not been described. This study aimed to assess the spatial distribution of regulated packaged water production in Ghana, both in relation to demand and for natural mineral water, to hydrogeological characteristics. 764 addresses for premises licenced to produce packaged water from 2009-2015 were mapped and compared to regional sachet water consumption and beverage import/export data examined. We find evidence to suggest packaged water is transported shorter distances in Ghana than in developed countries. For natural mineral waters, producers should be able to address the most widespread water quality hazards (including high salinity, iron and nitrates) in aquifers used for production through reverse osmosis treatment. The study suggests there is scope to integrate beverage product and groundwater regulatory databases to support groundwater management.
Mon, 5 November 2018
ARTICLE | doi:10.20944/preprints201811.0113.v1
Subject: Earth Sciences, Environmental Sciences Keywords: Landsat; artisanal-scale gold mining; infrastructure; protected areas; commodity
Online: 5 November 2018 (11:58:46 CET)
While deforestation rates decline globally they are rising in the western Amazon. Artisanal-scale gold mining (ASGM) is a large cause of this deforestation and brings with it extensive environmental, social, governance, and public health impacts, including large carbon emissions and mercury pollution. Underlying ASGM is a broad network of factors that influence its growth, distribution, and practices such as poverty, flows of legal and illegal capital, conflicting governance, and global economic trends. Despite its central role in land use and land cover change in the western Amazon and the severity of its social and environmental impacts, it is relatively poorly studied. While ASGM in southeastern Peru has been quantified previously, doing so is difficult due to the heterogeneous nature of the resulting landscape. Using a novel approach to classify mining that relies on a fusion of CLASlite and the Global Forest Change dataset, two Landsat-based deforestation detection tools, we sought to quantify ASGM-caused deforestation in the period 1984-2017 in the southern Peruvian Amazon and examine trends in the geography, methods, and impacts of ASGM across that time. We identify nearly 100,000 ha of deforestation due to ASGM in the 34-year study period, an increase of 21% compared to previous estimates. Further, we find that 10% of that deforestation occurred in 2017, with 53% occurring since 2011. Finally, we demonstrate key patterns and changes in ASGM activity and techniques through time and space and discuss their connections with, and impacts on, socio-economic factors such as land tenure, infrastructure, international markets, governance efforts, and social and environmental impacts.
Thu, 31 May 2018
ARTICLE | doi:10.20944/preprints201805.0470.v1
Subject: Earth Sciences, Environmental Sciences Keywords: remote sensing; python; data management; landsat; open-source
Online: 31 May 2018 (11:12:27 CEST)
Many remote sensing analytical data products are most useful when they are in an appropriate regional or national projection, rather than globally based projections like Universal Transverse Mercator (UTM) or geographic coordinates, i.e., latitude and longitude. Furthermore, leaving data in the global systems can create problems, either due to misprojection of imagery because of UTM zone boundaries, or because said projections are not optimised for local use. We developed the open-source Irish Earth Observation (IEO) Python module to maintain a local remote sensing data library for Ireland. This pure Python module, in conjunction with the IEOtools Python scripts, utilises the Geospatial Data Abstraction Library (GDAL) for its geoprocessing functionality. At present, the module supports only Landsat TM/ETM+/OLI/TIRS data that have been corrected to surface reflectance using the USGS/ESPA LEDAPS/ LaSRC Collection 1 architecture. This module and the IEOtools catalogue available Landsat data from the USGS/EROS archive, and includes functions for the importation of imagery into a defined local projection and calculation of cloud-free vegetation indices. While this module is distributed with default values and data for Ireland, it can be adapted for other regions with simple modifications to the configuration files and geospatial data sets.
Mon, 27 February 2017
ARTICLE | doi:10.20944/preprints201702.0093.v1
Subject: Earth Sciences, Environmental Sciences Keywords: used superabsorbent polymer; disposable diapers; swelling capacity; soil conditioner
Online: 27 February 2017 (06:50:27 CET)
This study was conducted to explore the potential of superabsorbent polymers (SAPs) from used disposable diapers as soil moisture conditioner. Swelling behavior of the proposed hydrogel in response to external stimuli such as salt solutions, temperature and pH was studied. In addition, laboratory experiments were carried out to evaluate the effects of incorporation hydrogel on germination of bean (Phaseolus vulgaris L.) and pumpkin (C. pepo) seeds. The structure of the superabsorbent was characterized by Fourier transform infrared spectroscopy (FTIR). The results indicate that the proposed SAP exhibited a maximum swelling capacity of 189 g.g-1 of dry gel. It was observed that the swelling capacity decreased with an increase in the ionic strength of the swelling medium. When this SAP was mixed with sandy soil, the mixture was able to lose water more slowly. The seeds germination and seedling growth was remarkably influenced by the application of 0.5, 1.0 and 2.0 w/w% of SAP compared to the untreated soil. Therefore, it follows that it is possible to take advantage of SAPs property from used disposable diapers to retain the moisture in soil as an alternative to value the use of such waste, showing that it has potential for diverse applications in agriculture.
Thu, 30 April 2020
ARTICLE | doi:10.20944/preprints202004.0515.v1
Subject: Earth Sciences, Environmental Sciences Keywords: air pollution; MASP; human health; quarantine
Online: 30 April 2020 (03:11:40 CEST)
Social distancing policies put in place during COVID-19 epidemic in addition to helping to limit the spread of the disease also contributed to improving urban air quality. Here we show a decrease in air pollutant concentration as a consequence of mobility reduction in São Paulo during the containment measure which began on 22nd March 2020. When comparing to foregoing weeks to equivalent periods of 2019, the concentration of most air pollutants sharply decreased in the first days of mobility restriction, to then increase again after government officials downplayed the threat of the disease. This trend is also followed by a decrease in hospital admissions by SARS-influenza. Therefore, despite the great economic and social unrest caused by the pandemic, this unique situation shows that large-scale mobility reduction policy had a significant impact on air quality, benefiting, directly and indirectly, the public health system.
Thu, 3 November 2016
ARTICLE | doi:10.20944/preprints201611.0024.v1
Subject: Earth Sciences, Environmental Sciences Keywords: SWAT; model development; paddy fields; irrigation; return flow
Online: 3 November 2016 (09:42:16 CET)
The consumption of rice, which recently increases globally, leads to requirement for planning sustainable water management for paddy cultivation. In this research, SWAT model was modified to evaluate sustainability of paddy cultivation. Modifications to simulate paddy cultivation are 1) to equip with a new water balance model of impounded fields, 2) to add an irrigation management option for paddy fields, which is characterized by flood irrigation managed by farmers on a daily basis, 3) to consider puddling operation that influences water quality and infiltration rate of soil. The enhanced model, named SWAT-PADDY, was applied to an agricultural watershed in Japan as a case study. The modified model succeeded in representing paddy cultivation in the study area. However, SWAT-PADDY underestimated base flow in irrigation period. The cause of this is inferred that the modified model doesn’t represent return flow of excess withdrawal of river water. In conclusion, addition of the models of impoundment and management practices in paddy fields to SWAT improved field scale simulation of water balance and irrigation in paddy fields. However, further improvement of the model on irrigation return flow process is needed to better predict hydrology of watersheds dominated by paddy irrigation.
Sun, 22 January 2017
ARTICLE | doi:10.20944/preprints201701.0096.v1
Subject: Earth Sciences, Geology Keywords: biomineralization; calcium ions; magnesium ions; Bacillus lichemiformis; carbonates
Online: 22 January 2017 (04:58:39 CET)
Reducing the hardness of hard water is of great concern nowadays due to some adverse effects on water pipes, boilers and soap consumption. Using the method of biomineralization to precipitate calcium and magnesium ions to become carbonate minerals was one of the most important innovations for reducing the hardness of hard water. The present study sought to explore the physical and chemical conditions of carbonates bio-precipitation and the potential use of Bacillus licheniformis SRB2 strain (GenBank: KM884945.1) isolated from sludge sample of Moshui River (Shandong University of Science and Technology, Qingdao, China) in reducing the hardness of hard waters by the induction of carbonate minerals. In this study, B. licheniformis SRB2 strain was identified based on the morphological, biochemical and 16S rDNA gene sequence homology analysis. The carbonate minerals induced by B. licheniformis bacteria in the liquid culture medium with 3% NaCl and Mg/Ca molar ratio of 0, 6, 8, 10 and 12 were investigated. The culture medium was inoculated with the bacterial liquid seed was set as the experimental group and the other culture medium was inoculated with the same volume of distilled water was set as the control group. The mineral phases, micromorphologies, and crystal structures were analyzed using X-ray powder diffraction, scanning electron microscope, energy dispersive X-ray detector, high resolution transmission electron microscopy and selected area electron diffraction. The bacterial concentrations and pH values of the solution were measured by a spectrophotometer and a pH meter, respectively. The urease secreted by B. licheniformis SRB2 was found to greatly increase the pH values of the liquid medium, which favored the formation of calcium carbonate.As a result, Mg2+ and Ca2+ ion concentrations decreased greatly due to the biomineralization of calcium carbonate and nesquehonite minerals in the presence of B. licheniformis SRB2 bacterium. There were only few calcium carbonates and no nesquehonite minerals in the control groups. It was also found that the minerals of nesquehonite induced by B. licheniformis SRB2 had a phenomenon of preferred orientation. What was more, even though Mg2+ ions inhibited the precipitation of Ca2+ ions, but under the action of B. licheniformis SRB2 bacteria, the inhibition effect was significantly declined. The bio-precipitation of calcium carbonate and nesquehonite minerals may represent a new method of pretreatment for the hardness reduction of hard water. The accomplished study is of certain interest for interpretation of the carbonates biomineralization in natural environment, and maybe also has a certain application value in the former processing of hard water
Sat, 8 October 2016
ARTICLE | doi:10.20944/preprints201610.0023.v1
Subject: Earth Sciences, Geophysics Keywords: climate change; water cycle; downscaling; hydrological model; Yangtze River; Yellow River; Tibetan Plateau
Online: 8 October 2016 (11:29:05 CEST)
Climate change is a global issue that draws widespread attention from the international society. As an important component of the climate system, the water cycle is directly affected by climate change. Thus, it is very important to study the influences of climate change on the basin water cycle with respect to maintenance of healthy rivers, sustainable use of water resources, and sustainable socioeconomic development in the basin. In this study, by assessing the suitability of multiple General Circulation Models (GCMs) recommended by the Intergovernmental Panel on Climate Change, Statistical Downscaling Model (SDSM) and Automated Statistical Downscaling model (ASD) were used to generate future climate change scenarios. These were then used to drive distributed hydrologic models (Variable Infiltration Capacity, Soil and Water Assessment Tool) for hydrological simulation of the Yangtze River and Yellow River basins, thereby quantifying the effects of climate change on the basin water cycle. The results showed that suitability assessment adopted in this study could effectively reduce the uncertainty of GCMs, and that statistical downscaling was able to greatly improve precipitation and temperature outputs in global climate mode. Compared to a baseline period (1961–1990), projected future periods (2046–2065 and 2081–2100) had a slightly decreasing tendency of runoff in the lower reaches of the Yangtze River basin. In particular, a significant increase in runoff was observed during flood seasons in the southeast part. However, runoff of the upper Yellow River basin decreased continuously. The results provide a reference for studying climate change in major river basins of China.
Tue, 22 January 2019
ARTICLE | doi:10.20944/preprints201901.0227.v1
Subject: Earth Sciences, Environmental Sciences Keywords: Microplastics, Nanoplastics, Optical Tweezers, Raman Spectroscopy
Online: 22 January 2019 (18:00:37 CET)
Our understanding of the fate and distribution of micro- and nano- plastics in the marine environment and their impact on the biota compartment is limited by the intrinsic difficulties of conventional analytical techniques (light scattering, FT-IR, Raman, optical and electron microscopies) in the detection, quantification and chemical identification of small particles in liquid samples. Here we propose the use of optical tweezers, a technique awarded in 2018 with the Nobel prize, as an analytical tool for the study of micro- and nano- plastics in sea water. In particular, we exploit the combination of optical tweezers with Raman spectroscopy (Raman Tweezers, RTs) to optically trap plastic particles with sizes from tens of µm down to 90 nm and unambiguously reveal their chemical composition. RTs applications are shown on particles made of the most common plastic pollutants, including polyethylene, polypropylene, nylon and polystyrene, that are artificially fragmented and aged directly in seawater. RTs allow us to assess the size and shapes of microparticles (beads, fragments, fibers) and can be applied to investigate particles covered with organic layers. Furthermore, operating at the single particle level, RTs enable unambiguous distinction of plastic particles from marine microorganisms and seawater minerals, overcoming the capacities of standard Raman spectroscopy in liquid, limited to average measurements. Coupled to suitable extraction and concentration protocols, RTs could have a strong impact in the study of the fate of micro and nanoplastics in marine environment, as well as in the understanding of the fragmentation processes on a multi-scale level.
Sun, 29 January 2017
ARTICLE | doi:10.20944/preprints201701.0129.v1
Subject: Earth Sciences, Environmental Sciences Keywords: emissivity; land cover; land surface temperature; surface urban heat island; thermal environment; mitigation
Online: 29 January 2017 (10:38:44 CET)
In urban area, one of the great problem is the rise of temperature, which leads to form the urban heat island effect. This paper refers to the trend of the urban surface temperature extracted from the Landsat images from which to consider changes in the formation of surface urban heat island for the north of Ho Chi Minh city in period 1995-2015. Research has identified land surface temperature from thermal infrared band, according to the ability of the surface emission based on characteristics of normalized difference vegetation index NDVI. The results showed that temperature fluctuated over the city with a growing trend and the gradual expansion of the area of the high-temperature zone towards the suburbs. Within 20 years, the trend of the formation of surface urban heat island with two typical locations showed a clear difference between the surface temperature of urban areas and rural areas with space expansion of heat island in 4 times in 2015 compared to 1995. An extreme heat island located in the inner city has an area of approximately 18% compared to the total area of the region. Since then, the solution to reduce the impact of urban heat island has been proposed, in order to protect the urban environment and the lives of residents in Ho Chi Minh City becoming better
Sat, 10 September 2016
ARTICLE | doi:10.20944/preprints201609.0038.v2
Subject: Earth Sciences, Environmental Sciences Keywords: SAR offset and speckle tracking; glacier velocity; Radarsat-2 Wide Fine; Svalbard
Online: 10 September 2016 (05:03:14 CEST)
Glacier dynamics play an important role in the mass balance of many glaciers, ice caps and ice sheets. In this study we exploit Radarsat-2 (RS-2) Wide Fine (WF) data to determine the surface speed of Svalbard glaciers in the winters of 2012/2013 and 2013/2014 using Synthetic Aperture RADAR (SAR) offset and speckle tracking. The RS-2 WF mode combines the advantages of the large spatial coverage of the Wide mode (150 x 150 km) and the high pixel resolution (9m) of the Fine mode and thus has a major potential for glacier velocity monitoring from space through offset and speckle tracking. Faster flowing glaciers (1.95 m d-1 - 2.55 m d-1) which are studied in detail are Nathorstbreen, Kronebreen, Kongsbreen and Monacobreen. Using our Radarsat-2 WF dataset, we compare the performance of two SAR tracking algorithms, namely the GAMMA Remote Sensing Software and a custom written MATLAB script (GRAY method) that has primarily been used in the Canadian Arctic. Both algorithms provide comparable results, especially for the faster flowing glaciers and the termini of slower tidewater glaciers. A comparison of the WF data to RS-2 Ultrafine and Wide mode data reveals the superiority of RS-2 WF data over the Wide mode data.
Thu, 17 November 2016
REVIEW | doi:10.20944/preprints201611.0095.v1
Subject: Earth Sciences, Environmental Sciences Keywords: : Crop Water Requirements; Irrigation Requirements; crop coefficient; web-GIS; Earth Observation; evapotranspiration
Online: 17 November 2016 (15:41:52 CET)
The experiences gathered during the past 30 years support the operational use of irrigation scheduling based on frequent multi-spectral image data. Currently, the operational use of dense time series of multispectral imagery at high spatial resolution makes monitoring of crop biophysical parameters feasible, capturing crop water use across the growing season, with suitable temporal and spatial resolutions. These achievements, and the availability of accurate forecasting of meteorological data, allow for precise predictions of crop water requirements with unprecedented spatial resolution. This information is greatly appreciated by the end users, i.e. professional farmers or decision-makers, and can be provided in an easy-to-use manner and in near-real-time by using the improvements achieved in web-GIS methodologies. This paper reviews the most operational and explored methods based on optical remote sensing for the assessment of crop water requirements, identifying strengths and weaknesses and proposing alternatives to advance towards full operational application of this methodology. In addition, we provide a general overview of the tools which facilitates co-creation and collaboration with stakeholders, paying special attention to these approaches based on web-GIS tools.
Tue, 13 September 2016
ARTICLE | doi:10.20944/preprints201609.0028.v2
Subject: Earth Sciences, Environmental Sciences Keywords: VOC; technological risk; exposure to risks; DRI; risk mapping; SIG; BTEX
Online: 13 September 2016 (03:42:52 CEST)
The population’s mobility in urban areas is a necessary variable in the modeling of risk scenarios caused by atmospheric contamination. The inclusion of this concept makes static models more dynamic while considering people within a city to be an entity with complex mobility processes. We propose a conceptual and methodological tool to make the representation of the social, economic and territorial components, as well as the patterns in the population´s mobility to delimitate risk areas for human health by exposure of contaminants. In the volatile organic compounds (VOC), benzene, ethylbenzene, toluene and xylene (BTEX) are amongst the most dominant substances in fugitive vapor emissions in gas stations (GS). In urban areas, the exposure to BTEX by residential proximity and proximity to other facilities, which cause intra-urban agglomeration, can impact and affect human health. This model seeks to facilitate the focalization, identification and prioritization of risk areas by BTEX environmental contamination. This article goes beyond de conceptual framework. It suggests methodological and instrumental aspects to be applied in other cities. The government agencies must consider these results when establishing rules, permissions and procedures to reduce environmental pollution for managing the risk in a complex urban environment.
Fri, 22 July 2016
ARTICLE | doi:10.20944/preprints201607.0066.v1
Subject: Earth Sciences, Geophysics Keywords: maximum flux; midlatitude cyclones; oceanic jets; chaotic transport
Online: 22 July 2016 (05:17:29 CEST)
Eddy-driven jets are of importance in the ocean and atmosphere, and to a first approximation are governed by Rossby wave dynamics. This study addresses the time-dependent flux of fluid and potential vorticity between such a jet and an adjacent eddy, with specific regard to determining zonal and meridional wavenumber dependence. The flux amplitude in wavenumber space is obtained, which is easily computable for a given jet geometry, speed and latitude, and which provides instant information on the wavenumbers of the Rossby waves which maximize the flux. This new tool enables the quick determination of which modes are most influential in imparting fluid exchange, which in the long term will homogenize the potential vorticity between the eddy and the jet. The results are validated by computing backward- and forward-time finite-time Lyapunov exponent fields, and also stable and unstable manifolds; the intermingling of these entities defines the region of chaotic transport between the eddy and the jet. The relationship of all of these to the time-varying transport flux between the eddy and the jet is carefully elucidated. The flux quantification presented here works for general time-dependence, whether or not lobes (intersection regions between stable and unstable manifolds) are present in the mixing region, and is therefore also easily computable for wave packets consisting of infinitely many wavenumbers.
Thu, 3 September 2020
Subject: Earth Sciences, Other Keywords: El Niño; La Niña; statistical indices; climate change adaptation; Ethiopia
Online: 3 September 2020 (15:33:05 CEST)
El Niño is warming of the sea surface temperature of the Pacific Ocean. Extreme flooding, drought, lack of potable water for livestock and domestic use, food insecurity and market imbalance are associated with El Niño and La Niña in Ethiopia. Drought following El Niño caused 50 to 90% crop failure, in the eastern parts of Ethiopia. El Niño episodes are detected using different statistical indices such as Oceanic Nino Index (ONI), Agricultural Stress Index System (ASIS) and the Southern Oscillation Index (SOI), with magnitude ranging from weak to strong. Identifying the El Niño and La Niña seasons it is very important to adopt suitable adaptation strategies, which can resolve and/or reduce the negative impacts. Early warning and immediate support to the impacted areas have been carried out to minimize risks from El Niño animal feed for livestock from other areas has been transported to the vulnerable areas. Planting early maturing and drought resistant crops, supplementary irrigation, early waning information on weather and climate have been exercised as climate change adaptation strategies, early warning mechanisms by the government of Ethiopia. El Niño and La Niña are natural phenomena; however, it is necessary to study the occurrence and distribution of El Niño and La Niña episodes to enable early warning and identify suitable adaptation strategies and policy implications in the country.
Wed, 28 December 2016
ARTICLE | doi:10.20944/preprints201612.0136.v1
Subject: Earth Sciences, Environmental Sciences Keywords: HEC-HMS model; streamflow; water availability; rainfall-runoff; Tonle Sap Basin
Online: 28 December 2016 (11:22:01 CET)
Hydrologic studies on rainfall-runoff have been extensively conducted in many regions around the globe to fulfill various desirable needs with a purpose of effective and proper planning and managing water resources for present and future uses, whereas such study is not well drawn much attention to river catchments of Tonle Sap Lake Basin in Cambodia, which may prevail to water insecurity. The Stung Sreng catchment, which is one among them considered to be a significant basin for water resources management in Cambodia, is remarkably increasing under intolerable pressures in water resources development. This study was to apply HEC-HMS (Hydrological Engineering Center-Hydrological Model System) model to predict streamflow of Stung Sangker catchment, located in Tonlesap Lake Basin in Cambodia. The result showed that the calibration was good at monthly basis. The model performance was given by Nash-Sutcliffe Efficiency criteria followed by 0.44 for daily and 0.71 for monthly basis, respectively. Moreover, the Percent Bias (PBIAS) for daily and monthly simulation was 4.13% and 3.56%, indicating a satisfactory model fit. The HEC-HMS conceptual model can be used to simulate flow of Stung Sangke catchment on a continuous time scale particularly monthly basis. The result also indicated that there was a clear seasonal variation in monthly water availability, especially during both wet and dry season.
Fri, 23 September 2016
ARTICLE | doi:10.20944/preprints201609.0081.v1
Subject: Earth Sciences, Environmental Sciences Keywords: spectral reflectance; vegetation indices; vegetation; remote sensing; oil spill; mangrove forest; oil pollution; Landsat 8
Online: 23 September 2016 (06:19:49 CEST)
This study is aimed at demonstrating application of vegetation spectral techniques for detection and monitoring of impact of oil spills on vegetation. Vegetation spectral reflectance from Landsat 8 data were used in the calculation of five vegetation indices (normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), adjusted resistant vegetation index 2 (ARVI2), green-infrared index (G/NIR) and green-shortwave infrared (G/SWIR) from the spill sites (SS) and non-spill (NSS) sites in 2013 (pre-oil spill), 2014 (oil spill date) and 2015 (post-oil spill) for statistical comparison. The result shows that NDVI, SAVI, ARVI2, G/NIR and G/SWIR indicated certain level difference between vegetation condition at the SS and the NSS were significant with p-value <0.5 in December 2013. In December 2014 vegetation conditions indicated higher level of significant difference between the vegetation at the SS and NSS as follows where NDVI, SAVI and ARVI2 with p-value 0.005, G/NIR - p-value 0.01 and GSWIR p-value 0.05. Similarly, in January 2015 a very significant difference with p-value <0.005. Three indices NDVI, ARVI2 and G/NIR indicated highly significant difference in vegetation conditions with p-value <0.005 between December 2013 and December 2014 at the same sites. Post—spill analysis show that NDVI and ARVI2 indicated low level of significance difference p-value <0.05 suggesting subtle change in vegetation conditions between December 2014 and January 2015. This technique is essential for real time detection, response and monitoring of oil spills from pipelines for mitigation of pollution at the affected sites in the mangrove forest.
Thu, 15 February 2018
ARTICLE | doi:10.20944/preprints201802.0103.v1
Online: 15 February 2018 (16:49:55 CET)
An effective on-board cloud detection method in small satellites would greatly improve the downlink data transmission efficiency and reduce the memory cost. In this paper, an ensemble method combining a lightweight U-Net with wavelet image compression is proposed and evaluated. The red, green, blue and infrared waveband images from Landsat-8 dataset are trained and tested to estimate the performance of proposed method. The LeGall-5/3 wavelet transform is applied on the dataset to accelerate the neural network and improve the feasibility of on-board implement. The experiment results illustrate that the overall accuracy of the proposed model achieves 97.45% by utilizing only four bands. Tests on low coefficients of compressed dataset have shown that the overall accuracy of the proposed method is still higher than 95%, while its inference speed is accelerated to 0.055 second per million pixels and maximum memory cost reduces to 2Mb. By taking advantage of mature image compression system in small satellites, the proposed method provides a good possibility of on-board cloud detection based on deep learning.
Tue, 9 August 2016
ARTICLE | doi:10.20944/preprints201608.0089.v1
Subject: Earth Sciences, Geology Keywords: ASTER; TIR; geology; mineralogy; suture zone; quartz; feldspars; silicates; carbonates; sulfates; granitic rocks; felsic; ultramafic; mapping
Online: 9 August 2016 (10:10:41 CEST)
The mineralogical indices, e.g., Quartz Index (QI), Carbonate Index (CI), Mafic Index (MI) for ASTER multispectral thermal infrared (TIR) data have been applied to various geological materials. The indices are proved to be robust in extracting geological information at the local scale. Considering the relatively narrow spatial coverage of each ASTER scene compared to LANDSAT, many scenes are needed when mosaicking the images to be mapped at regional scales. We develop a system to search ASTER data for a target area given the vast and expanding ASTER data archive. The data is then conditioned, prioritized, and the indices are calculated before finally mosaicking the imagery. The maps of the indices covering the very wide region of the central Tibetan Plateau are produced with this system. The characteristic features of the indices relating to their geology in the study area are analyzed and discussed. Many interesting lithological and structural information that are not currently well understood in the central Tibetan Plateau, the highest and most extensive plateau in the world, with an average elevation of over 4,500 meters above sea level, for example, distributions of the mafic-ultramafic rocks along the suture zones, the quarzitic and marine sedimentology accreted to the Eurasian continent and sulfate layers related to the Tethys and neo-Tethys geological setting can be retrieved from the processed ASTER images.
Tue, 1 November 2016
ARTICLE | doi:10.20944/preprints201611.0010.v1
Subject: Earth Sciences, Atmospheric Science Keywords: millimeter-wavelength cloud radar; attenuation correction; dual-radar; data fusion
Online: 1 November 2016 (10:05:18 CET)
In order to correct attenuated millimeter-wavelength (Ka-band) radar data and address the problem of instability, an attenuation correction methodology (attenuation correction with variation trend constraint; VTC) was developed. Using synchronous observation conditions and multi-band radars, the VTC method adopts the variation trends of reflectivity in X-band radar data captured with wavelet transform as a constraint to adjust reflectivity factors of millimeter-wavelength radar. The correction was evaluated by comparing reflectivities obtained by millimeter-wavelength cloud radar and X-band weather radar. Experiments showed that attenuation was a major contributory factor in the different reflectivities of the two radars when relatively intense echoes exist, and the attenuation correction developed in this study significantly improved data quality for millimeter-wavelength radar. Reflectivity differences between the two radars were reduced and reflectivity correlations were enhanced. Errors caused by attenuation were eliminated, while variation details in the reflectivity factors were retained. The VTC method is superior to the bin-by-bin method in terms of correction amplitude and can be used for attenuation correction of shorter wavelength radar assisted by longer wavelength radar data.
Tue, 13 September 2016
ARTICLE | doi:10.20944/preprints201609.0046.v1
Subject: Earth Sciences, Environmental Sciences Keywords: NEE; backscattering coefficient; LAI; soil moisture
Online: 13 September 2016 (10:12:12 CEST)
The objectives of the study were to determine the spatial rate of CO2 flux (Net Ecosystem Exchange) and soil moisture in a wetland ecosystem applying Sentinel-1 IW (Interferometric Wide) data of VH (Vertical Transmit/Horizontal Receive—cross polarization) and VV (Vertical Transmit/Vertical Receive—like polarization) polarization. In-situ measurements of carbon flux, soil moisture, and LAI (Leaf Area Index) were carried out over the Biebrza Wetland in north-eastern Poland. The impact of soil moisture and LAI on backscattering coefficient (σ°) calculated from Sentinel-1 data showed that LAI dominates the influence on σ° when soil moisture is low. The models for soil moisture have been derived for wetland vegetation habitat types applying VH polarization (R2 = 0.70 to 0.76). The vegetation habitats: reeds, sedge-moss, sedges, grass-herbs, and grass were classified using combined one Landsat 8 OLI (Operational Land Imager) and three TerraSAR-X (TSX) ScanSAR VV data. The model for the assessment of Net Ecosystem Exchange (NEE) has been developed based on the assumption that soil moisture and biomass represented by LAI have an influence on it. The σ° VH and σ° VV describe soil moisture and LAI, and have been the input to the NEE model. The model, created for classified habitats, is as follows: NEE = f (σ° Sentinel-1 VH, σ° Sentinel-1 VV). Reasonably good predictions of NEE have been achieved for classified habitats (R2 = 0.51 to 0.58). The developed model has been used for mapping spatial and temporal distribution of NEE over Biebrza wetland habitat types. Eventually, emissions of CO2 to the atmosphere (NEE positive) has been noted when soil moisture (SM) and biomass were low. This study demonstrates the importance of the capability of Sentinel-1 microwave data to calculate soil moisture and estimate NEE with all-weather acquisition conditions, offering an important advantage for frequent wetlands monitoring.
Wed, 7 July 2021
ARTICLE | doi:10.20944/preprints202105.0151.v2
Subject: Earth Sciences, Atmospheric Science Keywords: American Carbon Registry; California Action Reserve; California Air Resources Board; VERRA; Clean Development Mechanism; net ecosystem exchange
Online: 7 July 2021 (11:54:59 CEST)
Despite the use of commercial forest carbon protocols (CFCPs) for more than two decades, claiming ~566 MMtCO2e and a market value of ~USD $15.7 billion, comparative analysis of CFCP methodology and offset results is limited. In this study, five widely used biometric-based CFCPs are characterized, and common characteristics and differences are identified. CFCP claims of net forest carbon sequestration are compared with results of directly measured CO2 by eddy covariance, a meteorological method integrating gross vertical fluxes of forest and soil carbon, and the only alternative non-biometric source of net forest carbon sequestration data available. We show here that CFCPs share a structural feature delimiting forest carbon values by zero-threshold carbon accounting (gC m-2 ≤ 0), a pattern opposite to natural emissions of forest CO2 exchange based on direct measurement and a fundamental biological constraint on net forest carbon storage (i.e., soil efflux, ecosystem respiration). Exclusion of forest CO2 sources to the atmosphere precludes net carbon accounting, resulting in unavoidable over-crediting of CFCP project offsets. CFCP carbon results are significantly different from global forest CO2 net ecosystem exchange population results (FluxNet2015 gC m-2) at the 95% to 99.99% confidence levels, inferring an annual median error of ~247% (gC m-2), consistent with over-crediting. Direct CO2 measurement provides an urgently needed alternative method for commercial forest carbon products that has the potential to harmonize global markets and catalyze the role of forests in managing climate change through nature-based solutions.
Mon, 1 August 2016
ARTICLE | doi:10.20944/preprints201608.0003.v1
Subject: Earth Sciences, Environmental Sciences Keywords: seasonally frozen soil; frost heave; soil moisture content; soil type; freezing depth; soil porosity
Online: 1 August 2016 (09:47:52 CEST)
Frost heave, which is the volumetric expansion of frozen soil, has great ecological significance, since it creates water storage spaces in soils at the beginning of the growing season in cold temperate forests. To understand the characteristics of frost heave in seasonally frozen soil and the factors that impact its extent, we investigated the frost heave rates of forest soil from different depths and with different soil moisture contents, using both lab-based simulation and in situ measurement in a broadleaved Korean pine forest in the Changbai Mountains (northeastern China). We found that frost heave was mainly affected by soil moisture content, soil type, and gravitational pressure. Frost heave rate increased linearly with soil moisture content, and for each 100% increase in soil moisture content, the frost heave rate increased by 41.6% (loam, upper layer), 17.2% (albic soil, middle layer), and 4.6% (loess, lower layer). Under the same soil moisture content, the frost heave rate of loam was highest, whereas that of loess was lowest, and the frost heave of the uppermost 15 cm, which is the biologically enriched layer, accounted for ~55% of the frost heave. As a result, we determined the empirical relationship between frost heave and freezing depth, which is important for interpreting the effects of frost heave on increases in the storage space of forest soils and for calculating changes in soil porosity.
Sat, 13 August 2016
ARTICLE | doi:10.20944/preprints201608.0137.v1
Subject: Earth Sciences, Environmental Sciences Keywords: heavy metal; contamination assessment; X-ray fluorescence; bus station dusts
Online: 13 August 2016 (09:41:18 CEST)
The objective of this study was to investigate the concentration and spatial distribution patterns of six potentially toxic heavy metal elements (Mn, Zn, Cr, Pb, Cu and Ni) in bus station dusts in the Xifeng district of Gansu province, NW China. The contents were analyzed for Mn, Zn, Cr, Pb, Cu and Ni by using S8 TIGER Brochures wavelength dispersive X-ray fluorescence spectrometry. Geoaccumulation index (Igeo ), enrichment factor (EF), pollution index (PI) and integrated pollution index(IPI) were calculated to evaluate the heavy metal contamination level of bus station dusts. The results indicate that, in comparison with the background values of local soil, bus station dusts in Xifeng have elevated metal concentrations as a whole. The concentrations of heavy metals investigated in this paper are compared with the reported data of other cities. The results show that the arithmetic means of Mn, Zn, Cr, Pb, Cu and Ni are 440.8, 137.9, 60.0, 42.8, 33.5 and 19.8mg kg−1 respectively. The mean values of Igeo reveal the order of Ni<Mn<Cr<Cu<Zn<Pb. The high Igeo and EF for Cu, Zn and Pb in bus station dusts indicate that there is a considerable Cu, Zn and Pb pollution, which mainly originate from traffic and industry activities. The Igeo and EF of Ni, Mn and Cr are low and the assessment results indicate an absence of distinct Ni, Mn and Cr pollution in bus station dusts. The assessment results of PI also support Cu, Zn and Pb in bus station dusts presented middle pollution, and IPI indicates heavy metals of bus station dusts polluted seriously.
Thu, 6 October 2016
ARTICLE | doi:10.20944/preprints201610.0008.v3
Online: 6 October 2016 (08:52:44 CEST)
The properties of the annual, semiannual and triennial oscillations (AO, SAO and TO) in the middle atmosphere have been investigated using the TIMED/SABER temperature data. The Lomb-Scargle and wavelet spectra were used to determine the dominant oscillations in the background temperature field. The AO is prominent at the mid-latitudes. The AO amplitudes present an asymmetry between the two Hemispheres, being larger in the mesosphere than in the stratosphere. The SAO dominates the tropical regions, with three amplitude maxima at altitudes of 45, 75, and 85 km. The SAOs in the upper mesosphere (75 km) are out of phase with those in the mesopause (85 km) in the tropical regions, which can generate an enhancement of 11 K at each equinox, contributing to the lower mesospheric inversion layer. The TO is significant in the tropical region, with amplitude being maximum at 35, 45 and 85 km. Result shows that there may be potential interaction by the TO with SAO at 85km at the equator. The relation between ENSO and TO has also been discussed. The ENSO signal may modulate the amplitude of the TO, mainly in the lower stratosphere. The real origin of the TO may lie in the wave-mean-flow interaction.
Fri, 13 July 2018
ARTICLE | doi:10.20944/preprints201807.0244.v1
Subject: Earth Sciences, Geoinformatics Keywords: Image Fusion, Sentinel-1, Sentinel-2, Wetlands, Object-Based Classification, Unmanned Aerial Vehicle
Online: 13 July 2018 (17:11:07 CEST)
Wetlands benefits can be summarized but are not limited to their ability to store floodwaters and improve water quality, providing habitats for wildlife and supporting biodiversity, as well as aesthetic values. Over the past few decades, remote sensing and geographical information technologies has proven to be a useful and frequent applications in monitoring and mapping wetlands. Combining both optical and microwave satellite data can give significant information about the biophysical characteristics of wetlands and wetlands` vegetation. Also, fusing data from different sensors, such as radar and optical remote sensing data, can increase the wetland classification accuracy. In this paper we investigate the ability of fusion two fine spatial resolution satellite data, Sentinel-2 and the Synthetic Aperture Radar Satellite, Sentinel-1, for mapping wetlands. As a study area in this paper, Balikdami wetland located in the Anatolian part of Turkey has been selected. Both Sentinel-1 and Sentinel-2 images require pre-processing before their use. After the pre-processing, several vegetation indices calculated from the Sentinel-2 bands were included in the data set. Furthermore, an object-based classification was performed. For the accuracy assessment of the obtained results, number of random points were added over the study area. In addition, the results were compared with data from Unmanned Aerial Vehicle collected on the same data of the overpass of the Sentinel-2, and three days before the overpass of Sentinel-1 satellite. The accuracy assessment showed that the results significant and satisfying in the wetland classification using both multispectral and microwave data. The statistical results of the fusion of the optical and radar data showed high wetland mapping accuracy, with an overall classification accuracy of approximately 90% in the object-based classification. Compared with the high resolution UAV data, the classification results give promising results for mapping and monitoring not just wetlands, but also the sub-classes of the study area. For future research, multi-temporal image use and terrain data collection are recommended.
Tue, 13 December 2016
ARTICLE | doi:10.20944/preprints201612.0070.v1
Subject: Earth Sciences, Environmental Sciences Keywords: solar energy; solar radiation; climatic data; solar radiation estimation
Online: 13 December 2016 (10:06:35 CET)
Solar radiation is the main energy source for mankind and an accurate data of solar radiation levels for a particular location is vital for the optimum operation of solar energy transducers such as photovoltaic cells and solar thermal collectors. In this work, we show that there is a linear relationship between recorded monthly average temperatures and solar radiation in Swaziland. The good correlation can be utilized to develop two mathematical models for the estimation of solar radiation: one from the measured monthly average temperatures and the other based on the square-root of the difference between measured maximum and minimum monthly average temperatures. Both models fit the data well and can be applied to estimate solar radiation in other parts of the region.
Sat, 13 August 2016
ARTICLE | doi:10.20944/preprints201608.0134.v1
Subject: Earth Sciences, Environmental Sciences Keywords: spatial resolution; interpolation method; CREST model; Qinhuai catchment
Online: 13 August 2016 (04:28:19 CEST)
Distributed/semi-distributed models are considered to be sensitive to the spatial resolution of the data input. In this paper, we take a small catchment in high urbanized Yangtze River Delta, Qinhuai catchment as study area, to analyze the impact of spatial resolution of precipitation and the potential evapotranspiration (PET) on the long-term runoff and flood runoff process. The data source includes the TRMM precipitation data, FEWS download PET data, and the interpolated metrological station data. GIS/RS technique was used to collect and pre-process the geographical, precipitation and PET series, which were then served as the input of CREST (Coupled Routing and Excess Storage) model to simulate the runoff process. The results clearly showed that, the CREST model is applicable to the Qinhuai catchment; the spatial resolution of precipitation had strong influence on the modelled runoff results and the metrological precipitation data cannot be substituted by the TRMM data in small catchment; the CREST model was not sensitive to the spatial resolution of the PET data, while the estimation fourmula of the PET data was correlated with the model quality. This paper focused on the small urbanized catchment, suggesting the influential explanatory variables for the model performance, and providing reliable reference for the study in similar area.
Wed, 29 April 2020
SHORT NOTE | doi:10.20944/preprints202004.0501.v1
Subject: Earth Sciences, Environmental Sciences Keywords: Economic recession; SARS-CoV-2; Deforestation; Climate Change; Amazonia Integrity; Green Bonds
Online: 29 April 2020 (05:05:33 CEST)
The severity of the ongoing COVID-19 outbreak demand from countries to adopt extreme measurements of social isolation to stop the spread and flatten the curve of contamination. Although social isolation measures may have negative impacts on economy, historically it has been showed to be more effective in saving lives and less damaging to economy than not adopting these measurements during a viral pandemic. In Brazil, despite the positioning of the president against social isolation due to the consequent economic recession, the rapid spread of the virus has worried the governors of the Brazilian states, which are thus managing stringent social isolation measurements to avoid the advance of the virus. Since one of the main strategies to guarantee progress and economic growth in Brazil has been the exploitation of natural resources from the Amazonia biome, here we discuss the importance of this biome to Brazilian economy during the post-pandemic recession and highlights potential strategies to burst the economy without promoting Amazonia destruction. We show that, together with the REDD+ and the Amazon Fund, the Forest bonds represents good strategies to burst Brazilian economy in a sustainable way, showing that it is possible to improve the commodities without increasing Amazonia deforestation or the greenhouse gases emissions. Amazonia is a biome of global importance for the avoidance of another global crisis, which will occur if we reach the climatic tipping point of 1.5°C. Thus, governmental actions should go towards its preservation, not exploitation and depletion. The commitment of the government with environmental conservation is paramount so that these economic strategies have positive results, especially in a post-pandemic scenario, where the economy will be extremely weakened. The COVID-19 brings us a lesson regarding how our attitudes can impact the world, and what we can expect from a global crisis. Perhaps we can apply these lessons and focus on change our economy towards a sustainable direction to avoid another global crisis in the years to come.
Thu, 13 July 2017
ARTICLE | doi:10.20944/preprints201707.0030.v1
Subject: Earth Sciences, Geoinformatics Keywords: digital elevation model; DEM; digital surface model; DSM; great barrier reef; gully erosion; multi-view stereo; point cloud; unmanned aerial vehicle
Online: 13 July 2017 (02:55:02 CEST)
Structure from Motion with Multi-View Stereo photogrammetry (SfM) is increasingly utilised in geoscience investigations as a cost-effective method of acquiring high resolution (sub-meter) topographic data, but has not been thoroughly tested in gullied savanna systems. The aim of this study was to test the accuracy of topographic models derived from aerial (via an Unmanned Aerial Vehicle, ‘UAV’) and ground-based (via a handheld digital camera, ‘Ground’) SfM in modelling a hillslope gully system in dry-tropical savanna, and to assess the strengths and limitations of the approach at different scales. A UAV survey covered an entire hillslope gully system (0.715 km2), whereas a Ground survey covered a single gully within the broader system (650 m2). SfM topographic models, including Digital Surface Models (DSM) and dense point clouds, were compared against RTK-GPS point data and a pre-existing airborne LiDAR Digital Elevation Model (DEM). Results indicate UAV SfM can deliver topographic models with a resolution and accuracy suitable to define gully systems at a hillslope scale (e.g., 0.1 m resolution with ~ 0.5 – 1.3 m elevation error), while ground-based SfM is more capable of quantifying gully morphology (e.g., 0.01 m resolution with ~ 0.1 m elevation error). Key strengths of SfM for these applications include: the production of high resolution 3D topographic models and ortho-photo mosaics, low survey instrument costs (< $AUD 3,000); and rapid survey time (4 and 2 hours for UAV and Ground survey respectively). Current limitations of SfM include: difficulties in reconstructing vegetated surfaces; uncertainty as to optimal survey and processing designs; and high computational demands. Overall, this study has demonstrated great potential for SfM to be used as a cost-effective tool to aid in the mapping, modelling and management of hillslope gully systems at different scales, in tropical savanna landscapes and elsewhere.
Tue, 9 August 2016
ARTICLE | doi:10.20944/preprints201608.0098.v1
Subject: Earth Sciences, Atmospheric Science Keywords: ET; CWR; landsat ETM+; remote sensing; SEBAL; SSEB; SSEBop
Online: 9 August 2016 (12:27:09 CEST)
Remote sensing datasets are increasingly being used to provide spatially explicit large scale evapotranspiration (ET) estimates. The focus of this study was to estimate and thematically map pixel-by-pixel basis, and compare the actual evapotranspiration (ETa) of the Wonji Shoa Sugarcane Estate using Surface Energy Balance Algorithm for Land (SEBAL), Simplified Surface Energy Balance (SSEB) and Operational Simplified Surface Energy Balance (SSEBop) algorithms on Landsat7 ETM+ images acquired on four days in 2002. The algorithms were based on image processing which uses spatially distributed spectral satellite data and ground meteorological data to derive the surface energy balance components. The results obtained revealed that the ranges of the daily ETa estimated on January 25, February 26, September 06 and October 08, 2002 using SEBAL were 0.0–6.85, 0.0–9.36, 0.0–3.61, 0.0–6.83 mm/day; using SSEB 0.0–6.78, 0.0–7.81, 0.0–3.65, 0.0–6.46 mm/day, and SSEBop were 0.05–8.25, 0.0–8.82, 0.2–4.0, 0.0–7.40 mm/day, respectively. The Root Mean Square Error (RMSE) values between SSEB and SEBAL, SSEBop and SEBAL, and SSEB and SSEBop were 0.548, 0.548, and 0.99 for January 25, 2002; 0.739, 0.753, and 0.994 for February 26, 2002;0.847, 0.846, and 0.999 for September 06, 2002; 0.573, 0.573, and 1.00 for October 08, 2002, respectively. The standard deviation of ETa over the sugarcane estate showed high spatio-temporal variability perhaps due to soil moisture variability and surface cover. The three algorithm results showed that well watered sugarcane fields in the mid-season growing stage of the crop and water storage areas had higher ETa values compared with the other dry agricultural fields confirming that they consumptively use more water. Generally during the dry season ETa is limited to water surplus areas only and in wet season, ETa was high throughout the entire sugarcane estate. The evaporation fraction (ETrF) results also followed the same pattern as the daily ETa over the sugarcane estate. The total crop and irrigation water requirement and effective rainfall estimated using the Cropwat model were 2468.8, 2061.6 and 423.8 mm/yr for January 2001 planted and 2281.9, 1851.0 and 437.8 mm/yr for March 2001 planted sugarcanes, respectively. The mean annual ETa estimated for the whole estate were 107 Mm3, 140 Mm3, and 178 Mm3 using SEBAL, SSEB, and SSEBop, respectively. Even though the algorithms should be validated through field observation, they have potential to be used for effective estimation of ET in the sugarcane estate.
Fri, 14 October 2016
ARTICLE | doi:10.20944/preprints201610.0059.v1
Subject: Earth Sciences, Other Keywords: ammonium–arsenic jarosite; characterization; chemical decomposition and thermal decomposition
Online: 14 October 2016 (11:27:36 CEST)
Arsenic, an element of environmental impact, can be incorporated into jarosite–type compounds and remain stabilised within the structure under a wide range of environmental conditions. In this study, a sample of ammonium–arsenic jarosite was synthesised by precipitation in sulphate medium at controlled pH of 1.2–1.8. The behaviour of arsenic during the thermal and chemical decomposition of jarosite was analysed; the degradation in alkaline medium of jarosite was also studied. According to the results, the synthesised jarosite is composed of joined rhombohedral crystals, forming tightly spherical shaped particles, 37–54 μm size. The ammonium jarosite produced possessed a high arsenic concentration; its calculated stoichiometry being (NH4)Fe2.45[(SO4)1.80(AsO4)0.20][(OH)4.15(H20)1.85]. It was found that arsenic is stabilised in the jarosite structure; upon heating, it remains in residual solids above 700°C, whilst in alkaline medium an incongruent dissolution takes place, with the arsenic retained in the solid phase along with iron. These solids, when exposed to high temperatures (1200°C), transform into a type of iron oxide known as hematite, so with arsenic it is retained an iron compound forming a stable compound which withstands high temperatures.
Fri, 15 July 2016
REVIEW | doi:10.20944/preprints201607.0041.v1
Subject: Earth Sciences, Environmental Sciences Keywords: natural gas hydrate; five forces model; intuitional arrangement
Online: 15 July 2016 (11:33:39 CEST)
Natural gas hydrate, also known as combustible ice and mainly composed of methane, it is identified as the potential clean energy in the 21th century. Due to its large reserves, gas hydrate can ease problems caused by energy resource shortage and has gained attention around the world. In this paper, we focus on the exploration and development of gas hydrate as well as discussing its status and future development trend in China and abroad, then we analyze its opportunities and challenges in China from four aspects: resource, technology, economy and police with five forces model and PEST method. The results show, China has abundance gas hydrate resource; however the backward technologies and inadequate investment has seriously hindered the future development of gas hydrate, so China should establish relevant cooperation framework and intuitional arrangement to attract more investment as well as breaking through technical difficulties to make gas hydrate commercialization as soon as possible.
Sat, 11 January 2020
REVIEW | doi:10.20944/preprints202001.0104.v1
Subject: Earth Sciences, Environmental Sciences Keywords: biodiversity; conserved areas; ecosystem services; effectiveness; management; protected areas; representative; targets
Online: 11 January 2020 (10:58:38 CET)
Humanity will soon define a new era for nature – one that seeks to correct decades of underwhelming responses to the global biodiversity crisis. Area-based conservation efforts, which include both protected areas and other effective area-based conservation measures, are likely to extend and diversify. But persistent shortfalls in ecological representation, management effectiveness and measurable biodiversity outcomes diminish the potential role of area-based conservation in stemming biodiversity loss. Here we show how protected area expansion by governments since 2010 has had limited success in increasing biodiversity coverage, and identify four emergent issues that –if addressed – will enhance the performance of area-based conservation post-2020. We close with recommendations for a broad biodiversity agenda that maximises the potential of area-based conservation. Parties to the Convention on Biological Diversity must recognise that area-based conservation primarily focuses on local threats to species and ecosystems, and needs enhanced emphasis on biodiversity outcomes to better track and fund its contribution to global conservation efforts.
Fri, 5 October 2018
ARTICLE | doi:10.20944/preprints201810.0109.v1
Subject: Earth Sciences, Geology Keywords: petrographic characteristics; physicomechanical properties; concrete petrography
Online: 5 October 2018 (16:27:54 CEST)
This paper examines the effect of the aggregate type on concrete strength and more specifically how the petrographic characteristics of various aggregate rocks as well as their physico-mechanical properties influences the durability of C 25/30 strength class concrete. The studied aggregate rocks are derived from Veria-Naousa and Edessa ophiolitic complexes as well as granodiorite and albitite rocks from their surrounding areas in central Macedonia (Greece). Concretes are produced with constant volume proportions, workability, mixing and curing conditions using different sizes of each aggregate type. Aggregates were mixed both in dry and water saturated states in concretes. Six different types of aggregates were examined and classified in three district groups according to their physicomechanical properties, petrographic characteristics and surface texture. The classification in groups after the concrete compressive strength test verified the initial classification in the same three groups. Group I (ultramafic rocks) presents the lowest concrete strengths, depending on their high alteration degree and the low mechanical properties of ultramafic aggregates. Group II (mafic rocks and granodiorite) presents a wide range of concrete strengths, depending on different petrographic characteristics and mechanical properties. Group III (albite rocks) presents the highest concrete strengths, depending on their lowest alteration degree and their highest mechanical properties. Therefore mineralogy and microstructure of the coarse aggregates affects the final strength of the concrete specimens.
Mon, 15 August 2016
ARTICLE | doi:10.20944/preprints201608.0149.v1
Subject: Earth Sciences, Environmental Sciences Keywords: landsat 8 OLI; Nalban Lake; East Kolkata Wetland; chlorophyll-a prediction; study points; validation points
Online: 15 August 2016 (13:51:19 CEST)
1) Landsat operational land imager (OLI) data and consequent laboratory measurements were used to predict Chlorophyll-a (Chl-a) concentration and the trophic states for an inland lake within the East Kolkata Wetland, India; 2) The most suitable band ratio was identified by performing Pearson correlation analysis between Chl-a concentrations and possible OLI band and band ratios from the study points; 3) The results showed highest correlation coefficient from the band ratio OLI5/OLI4 with an R value of 0.85. The prediction model was then developed by applying regression analysis between the band ratio OLI5/OLI4 and Chl-a concentration of the study points. The reflectance ratios of the validation points were given as input on the prediction model and the model output was considered as predicted Chl-a values of the validation points to check the efficiency of the prediction model. The regression model between laboratory-derived Chl-a value and model-fitted Chl-a value of the validation points revealed a high correlation with an R2 value of 0.78. Trophic State Index (TSI) of the lake was also calculated from laboratory-derived Chl-a value and model-fitted Chl-a value of the validation points. The study presented a high correlation of TSI determined from predicted data with TSI from laboratory reference data (R = 0.88). The TSI values of the lake ranged from 65 to 75 which indicate that the lake is appeared to be eutrophic to hypereutrophic conditions. 4) This empirical study showed that Landsat 8 OLI imagery can be effectively applied to estimate Chl-a levels and trophic states for inland lakes.
Tue, 13 December 2016
ARTICLE | doi:10.20944/preprints201612.0067.v1
Subject: Earth Sciences, Other Keywords: water in the soil; surface irrigation; water storage; irrigation modelling; soil hydrodynamics
Online: 13 December 2016 (09:55:18 CET)
An adequate representation of the water infiltration process in the soil allows improving the efficiency in application and the uniformity in surface irrigation. The Green and Ampt model has shown a good representation of the process, and researchers from the United States Department of Agriculture (USDA) determined the values of their parameters for soils of that country, which are shown in tables or through functional relationships and this information is used as reference in several parts of the world, although there is no certainty that they are representative of the soils in Mexico. In this study, the parameters of the Green & Ampt equation were determined and evaluated in some soils of agricultural importance in Mexico. The parameters were obtained in four ways: one of them applied a methodology adapted from Brooks and Corey to quantify the wetting front capillary pressure head and used an permeameter under constant hydraulic head to determine the saturated hydraulic conductivity, and the other three consisted in taking them from three studies reported by the USDA. The values of the parameters suggested in Mexico drastically underestimated the results with relative errors (RE) in a range of -49.0 to -94.0% and the most representative were those obtained with the methodology proposed in this research with RE of -15.0 to 6.0%.
Fri, 17 March 2017
ARTICLE | doi:10.20944/preprints201703.0145.v1
Subject: Earth Sciences, Environmental Sciences Keywords: SMOS, L-band, Level 3, ECMWF, SMOS-IC, soil moisture, vegetation optical depth, MODIS, NDVI
Online: 17 March 2017 (22:14:31 CET)
The main goal of the Soil Moisture and Ocean Salinity (SMOS) mission over land surfaces is the production of global maps of soil moisture (SM) and vegetation optical depth (τ) based on multi-angular brightness temperature (TB) measurements at L-band. The operational SMOS Level 2 and Level 3 soil moisture algorithms account for different surface effects, such as vegetation opacity and soil roughness at 4 km resolution, in order to produce global retrievals of SM and τ. In this study, we present an alternative SMOS product which was developed by INRA (Institut National de la Recherche Agronomique) and CESBIO (Centre d’Etudes Spatiales de la BIOsphère). This SMOS-INRA-CESBIO (SMOS-IC) product provides daily SM and τ at the global scale and differs from the operational SMOS Level 3 (SMOSL3) product in the treatment of retrievals over heterogeneous pixels. Specifically, SMOS-IC is much simpler and does not account for corrections associated to the antenna pattern and the complex SMOS viewing angle geometry. It considers pixels as homogeneous to avoid uncertainties and errors linked to inconsistent auxiliary data sets which are used to characterize the pixel heterogeneity in the SMOS L3 algorithm. SMOS-IC also differs from the current SMOSL3 product (Version 300, V300) in the values of the effective vegetation scattering albedo (ω) and soil roughness parameters. An inter-comparison is presented in this study based on the use of ECMWF (European Center for Medium range Weather Forecasting) SM outputs and NDVI (Normalized Difference Vegetation Index) from MODIS (Moderate-Resolution Imaging Spectroradiometer). A 6 year (2010-2015) inter-comparison of the SMOS products SMOS-IC and SMOSL3 SM (V300) with ECMWF SM yielded higher correlations and lower ubRMSD (unbiased root mean square difference) for SMOS-IC over most of the pixels. In terms of τ, SMOS-IC τ was found to be better correlated to MODIS NDVI in most regions of the globe, with the exception of the Amazonian basin and of the northern mid-latitudes.
Sun, 18 December 2016
ARTICLE | doi:10.20944/preprints201612.0091.v1
Online: 18 December 2016 (05:12:01 CET)
Large-scale hydrological modeling in China is challenging given the sparse meteorological stations and large uncertainties associated with atmospheric forcing data. Here we introduce the development and use of the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) in the Heihe River Basin(HRB) for improving hydrologic modeling, by leveraging the datasets from the China Meteorological Administration Land Data Assimilation System (CLDAS)(including climate data from nearly 40000 area encryption stations, 2700 national automatic weather stations, FengYun (FY) 2 satellite and radar stations). CMADS uses the Space Time Multiscale Analysis System (STMAS) to fuse data based on ECWMF ambient field and ensure data accuracy. In addition, compared with CLDAS, CMADS includes relative humidity and climate data of varied resolutions to drive hydrological models such as the Soil and Water Assessment Tool (SWAT) model. Here, we compared climate data from CMADS, Climate Forecast System Reanalysis (CFSR) and traditional weather station (TWS) climate forcing data and evaluated their applicability for driving large scale hydrologic modeling with SWAT. In general, CMADS has higher accuracy than CFRS when evaluated against observations at TWS; CMADS also provides spatially continuous climate field to drive distributed hydrologic models, which is an important advantage over TWS climate data, particular in regions with sparse weather stations. Therefore, SWAT model simulations driven with CMADS and TWS achieved similar performances in terms of monthly and daily stream flow simulations, and both of them outperformed CFRS. For example, for the three hydrological stations (Ying Luoxia, Qilian Mountain, and ZhaMasheke) in the HRB at the monthly and daily Nash-Sutcliffe efficiency ranges of 0.75-0.95 and 0.58-0.78, respectively, which are much higher than corresponding efficiency statistics achieved with CFSR (monthly: 0.32-0.49 and daily: 0.26 – 0.45). The CMADS dataset is available free of charge and is expected to a valuable addition to the existing climate reanalysis datasets for deriving distributed hydrologic modeling in China and other countries in East Asia.
Thu, 21 December 2017
ARTICLE | doi:10.20944/preprints201712.0150.v1
Subject: Earth Sciences, Atmospheric Science Keywords: Philippines; rainfall; precipitation; Gamma distribution; probability; weather risk
Online: 21 December 2017 (04:43:17 CET)
Philippines as an archipelago and tropical country, which is situated near the Pacific ocean, faces uncertain rainfall intensities. This makes environmental, agricultural and economic systems affected by precipitation difficult to manage. Time series analysis of Philippine rainfall pattern has been previously done, but there is no study investigating its probability distribution. Modeling the Philippine rainfall using probability distributions is essential, especially in managing risks and designing insurance products. Here, daily and cumulative rainfall data (January 1961 - August 2016) from 28 PAGASA weather stations are fitted to probability distributions. Moreover, the fitted distributions are examined for invariance under subsets of the rainfall data set. We observe that the Gamma distribution is a suitable fit for the daily up to the ten-day cumulative rainfall data. Our results can be used in agriculture, especially in forecasting claims in weather index-based insurance.
Wed, 22 March 2017
ARTICLE | doi:10.20944/preprints201703.0173.v1
Subject: Earth Sciences, Environmental Sciences Keywords: land use; management; woody cover determinants; human-environment; Sahel
Online: 22 March 2017 (15:55:14 CET)
Woody vegetation in farmland acts as a carbon sink and provides ecosystem services for local people, but no macro-scale assessments of the impact of management and climate on woody cover exists for drylands. Here we make use of very high spatial resolution satellite imagery to derive wall-to-wall woody cover patterns in tropical West African drylands. In arid and semi-arid Sahel, areas of more people are associated with more trees: mean woody cover is greater in farmlands (12%) than in savannas (6%), and likewise it is higher close to villages than further away. In sub-humid savannas of West Africa, woody cover is generally above 20% and decreases with increasing population density, but remains around 15% in farmlands, independent of rainfall. In the region as a whole, rainfall, terrain and soil are the most important (80%) determinants of woody cover, while management factors play a smaller (20%) role. We conclude that agricultural expansion cannot generally be claimed to cause woody cover losses, and that observations in Sahel contradict simplistic ideas of a high negative correlation between population density and woody cover.
Fri, 17 March 2017
ARTICLE | doi:10.20944/preprints201703.0134.v1
Subject: Earth Sciences, Geoinformatics Keywords: spatial-spectral feature; very high spatial resolution image; classification; Tobler’s First Law of Geography
Online: 17 March 2017 (05:06:12 CET)
Aerial image classification has become popular and has attracted extensive research efforts in recent decades. The main challenge lies in its very high spatial resolution but relatively insufficient spectral information. To this end, spatial-spectral feature extraction is a popular strategy for classification. However, parameter determination for that feature extraction is usually time-consuming and depends excessively on experience. In this paper, an automatic spatial feature extraction approach based on image raster and segmental vector data cross-analysis is proposed for the classification of very high spatial resolution (VHSR) aerial imagery. First, multi-resolution segmentation is used to generate strongly homogeneous image objects and extract corresponding vectors. Then, to automatically explore the region of a ground target, two rules, which are derived from Tobler’s First Law of Geography (TFL) and a topological relationship of vector data, are integrated to constrain the extension of a region around a central object. Third, the shape and size of the extended region are described. A final classification map is achieved through a supervised classifier using shape, size, and spectral features. Experiments on three real aerial images of VHSR (0.1 to 0.32 m) are done to evaluate effectiveness and robustness of the proposed approach. Comparisons to state-of-the-art methods demonstrate the superiority of the proposed method in VHSR image classification.
Thu, 2 March 2017
REVIEW | doi:10.20944/preprints201703.0014.v1
Subject: Earth Sciences, Environmental Sciences Keywords: PM10; TSP; pollutants; element markers; epidemiological; dispersion modeling
Online: 2 March 2017 (07:29:35 CET)
No doubt pollution is a global problem which must be holistically tackled. In doing this, adequate knowledge of the sources of pollution is important, therefore the aim of this paper is to review source apportionment with reference to top-down and bottom-up methods. In this paper, dispersion modeling, emissions inventory, and sampling methods were discussed. Also, analytical methods involved in top-down source apportionment were mentioned. The two techniques are needed to evaluate pollutants and their sources. Based on these two approaches, pollution control strategy would be developed and decisions can be made in deciding the right approach to solve or reduce the pollution problems.
Fri, 12 June 2020
ARTICLE | doi:10.20944/preprints202006.0151.v1
Subject: Earth Sciences, Environmental Sciences Keywords: topography; soil carbon sequestration; humus; earthworms; climate, vermi-compost
Online: 12 June 2020 (12:29:50 CEST)
This new study revised interlinked issues of global soil organic carbon (SOC), annual net primary productivity (NPP) and atmospheric CO2 turnover time (τ). Soil is confirmed as both the greatest sink and source for excess atmospheric CO2. Most terrestrial NPP (~218 Gt C/yr) is ultimately processed in topsoil and SOC stocks now total >10,000–12,000 Gt. More excess carbon is released into the air and water from SOC loss (>20 Gt C/yr) due to land clearance for pasture/crops, fires, agrichemical poisoning and erosion, than from fossil fuels (~10 Gt C/yr). NOAA’s Barrow bounce and isotopic analyses support high terrestrial flux up to ~800 Gt C/yr and CO2 turnover time of ~1–4 years. Earth’s re-humification via compost offers the best and only practical/time-critical fix for climate, strategy for species extinction plus remedy for human health.
Thu, 27 October 2016
ARTICLE | doi:10.20944/preprints201610.0116.v1
Subject: Earth Sciences, Atmospheric Science Keywords: solar cyclic variability; Canonical and Modoki ENSO; Indian summer monsoon
Online: 27 October 2016 (11:31:29 CEST)
A flow-chart is presented depicting atmosphere-ocean coupling, which is initiated by decadal solar variability. Possible mechanisms for Canonic ENSO, Modoki ENSO and Canonic-Modoki ENSO are proposed and their relevance to the decadal variation of Hadley, Walker circulation and mid-latitude jets are discussed. We also show subsequent teleconnections by ENSO for eg., on ISM with a special emphasis on later two decades of the last century. As there is a disruption of the usual ENSO-ISM teleconnection, we discussed on possible mechanism. The role of volcanos and the change in sun-NAO connection were discussed. The regional Hadley circulation, via NAO in the northern hemisphere and Indian Ocean Dipole in the southern hemisphere, may have a role in the change of ISM behaviour. Such flow-chart helps to improve our understanding of various types of ENSO in both temporal as well as spatial scale. It subsequently can benefit the modelling community by improved representation of ENSO in models.
Wed, 16 November 2016
ARTICLE | doi:10.20944/preprints201611.0085.v1
Subject: Earth Sciences, Atmospheric Science Keywords: Parameterization, climate, Lightning, Atmosphere, Modelling, Thunderstorm, Convection, Forest, fires.
Online: 16 November 2016 (13:50:05 CET)
We use the third version of the Canadian Local Climate Model as a diagnostic tool to study the climatology of observed CG lightning activity at Maniwaki (latitude: 46,23°N; Longitude: 75,58°W). We examine the dependence between the hourly lightning activity and the related atmospheric variables during the warm season of sixteen years (between 1984 and 2004). The goal of this research is: a) to evaluate the atmospheric static state evolution and its moisture contents for conditions having generated lightning occurrence, b) to develop a CG lightning parameterization, and c) to verify this CG lightning parameterization on other Canadian areas. The freezing level altitude and the precipitable water content are used to estimate the static air instability and its moisture content respectively. These two parameters are served to develop the CG lightning parameterization. A comparison between the observations and simulations CG lightning occurrence and frequency at Maniwaki showed a mean absolute error rate of 27% and 55% respectively. We apply this parameterization at four Canadian regions, distributed from west to east. The simulated CG lightning results are comparable to observed CG lightning at Maniwaki and tested regions. The application of the CG lightning parameterization to the daily data enabled us to find the monthly results. This application represents a preliminary stage for validation this parameterization in regional numerical models in Canada during the historic period.
Thu, 28 July 2016
ARTICLE | doi:10.20944/preprints201607.0087.v1
Online: 28 July 2016 (04:48:33 CEST)
The relations between the kinetic energy spectrum and the second order longitudinal structure function in two dimensions are derived, and several examples are considered. The forward conversion (from spectrum to structure function) is illustrated first with idealized power law spectra, representing turbulent inertial ranges. The forward conversion is also applied to the zonal kinetic energy spectrum of Nastrom and Gage (1985) and the result agrees well with the longitudinal structure function of Lindborg (1999). The inverse conversion (from structure function to spectrum) is tested with data from 2D turbulence simulations. When applied to the theoretical structure function (derived from the forward conversion of the spectrum), the result closely resembles the original spectrum, except at the largest wavenumbers. However the inverse conversion is much less successful when applied to the structure function obtained from pairs of particles in the flow. This is because the inverse conversion favors large pair separations, which are typically noisy with particle data. Fitting the structure function to a polynomial improves the result, but not sufficiently to distinguish the correct inertial range dependencies. Furthermore the inversion of non-local spectra is largely unsuccessful. Thus it appears that focusing on structure functions with Lagrangian data is preferable to estimating spectra.
Thu, 16 February 2017
ARTICLE | doi:10.20944/preprints201702.0059.v1
Subject: Earth Sciences, Environmental Sciences Keywords: fine particulate matter (PM2.5); aerosol optical depth; community multi-scale air quality (CMAQ) model; data fusion; exposure assessment
Online: 16 February 2017 (08:58:09 CET)
Estimating ground surface PM2.5 with fine spatiotemporal resolution is a critical technique for exposure assessments in epidemiological studies of its health risks. Previous studies have utilized monitoring, satellite remote sensing or air quality modeling data to evaluate the spatiotemporal variations of PM2.5 concentrations, but such studies rarely combined these data simultaneously. We develop a three-stage model to fuse PM2.5 monitoring data, satellite-derived aerosol optical depth (AOD) and community multi-scale air quality (CMAQ) simulations together and apply it to estimate daily PM2.5 at a spatial resolution of 0.1˚ over China. Performance of the three-stage model is evaluated using a cross-validation (CV) method step by step. CV results show that the finally fused estimator of PM2.5 is in good agreement with the observational data (RMSE = 23.00 μg/m^3 and R2 = 0.72) and outperforms either AOD-retrieved PM2.5 (R2 = 0.62) or CMAQ simulations (R2 = 0.51). According to step-specific CVs, in data fusion, AOD-retrieved PM2.5 plays a key role to reduce mean bias, whereas CMAQ provides all-spacetime-covered predictions, which avoids sampling bias caused by non-random incompleteness in satellite-derived AOD. Our fused products are more capable than either CMAQ simulations or AOD-based estimates in characterizing the polluting procedure during haze episodes and thus can support both chronic and acute exposure assessments of ambient PM2.5. Based on the products, averaged concentration of annual exposure to PM2.5 was 55.75 μg/m3, while averaged count of polluted days (PM2.5 > 75 μg/m3) was 81, across China during 2014. Fused estimates will be publicly available for future health-related studies.
Fri, 21 October 2016
ARTICLE | doi:10.20944/preprints201610.0091.v1
Subject: Earth Sciences, Environmental Sciences Keywords: hydrological processes; hillslope hydrological modeling; rainfall simulators; subsurface flow processes
Online: 21 October 2016 (09:30:21 CEST)
Hydrological processes are complex to compute on hilly areas when compared to the plain areas. Most of the hydrological model do not take into account the critical rainfall-runoff generation processes such as subsurface storm flow, saturation excess flow, overland flow, return flow and pipe storage. The simulations of the above processes in the soil matrix requires detailed hillslope hydrological modelling. In present study, a hillslope experimental plot is designed to study the runoff generation processes on the plot scale. The setup is designed keeping in view the natural hillslope conditions prevailing in the north western Himalayas, India where high intensity storm event occurs frequently. Using the experimental data and the developed conceptual model, the overland flow and the subsurface flow through macropore dominated area has been estimated/analyzed on the pixel basis. Over the experimental hillslope plot, a rainfall simulator was installed to generate the rainfall intensity in the range of 15 to 150 mm/hr which represented the dominating rainfall intensity range in the region. Soil moisture sensors were also installed at 100 mm and 300 mm depth at different locations of the plot to observe soil moisture variations. It was found that once the soil is saturated, it remains in the field capacity for next 24-36 hours. Such antecedent moisture conditions are most favorable for the generation of rapid stormflow from hillslopes. Dye infiltration test was also performed on the undisturbed soil column to observe the macropore fraction variability over the vegetated hillslopes. The surface runoff predicted using the developed hillslope hydrological model compared well with the observed surface runoff under high intensity rainfall conditions.
Wed, 11 January 2017
ARTICLE | doi:10.20944/preprints201701.0054.v1
Subject: Earth Sciences, Environmental Sciences Keywords: bioenergy; Camelina sativa; energy crops; agro-climatic suitability; biodiesel
Online: 11 January 2017 (04:57:16 CET)
Camelina (Camelina sativa L.) is an oilseed with potential for use as a raw material in second-generation biofuels. Camelina has a seed yield of up to 2380 kg ha-1 and contains around 45% fatty acids. Selection of a suitable site is critical for production optimization. The objective of this study was to determine Chilean agro-climatic suitability for establishing camelina as a productive alternative. Climate and soil requirements and geographical restraints were evaluated for the species, considering the climatological characteristics of its regions of origin, as well as regions where camelina is successfully grown in the rest of the world. The variables considered include factors (maximum temperatures of the warmest month, water deficits, and degree days) and limitations (altitude, geomorphology, and current land use), which permitted the evaluation of the national territory for a certain level of suitability. It was determined that 1.3% of the national territory (960,664 ha) has some degree of suitability for camelina adoption. Between the Biobío and Los Lagos regions, 49.0% of land (471,203 ha) is in the category of without thermic restrictions, with mild water restrictions, and mild soil restrictions or without information, which can be used for camelina production. The Los Ríos region had 21.4% surface area (321,176 ha) with some level of suitability for camelina, the most suitable region to establish this crop in Chile.