Great Malang region is developing rapidly with the population increase and inhabitant`s activity, like migration and urbanization. Other activities like agricultural expansion as well as an uncontrolled residential development need to be monitored to avoid any negative impact in the future. The availability of free and open-source software, spatial high-resolution satellite imagery datasets, and powerful algorithms open the possibilities to map, monitor, and predict the future trend of land use land cover (LULC) changes. However, the accuracy and precision of this model is still in doubt, especially in the Great Malang region. Research is needed to provide a foundational basis and documentation on how the changes occur, where did the changes occur, and the accuracy of the predicted model. This study tries to answer those questions using the high spatial resolution of Sentinel-2 imageries. Combination of the fuzzy algorithm, artificial neural network, and cellular automata was utilized to process the datasets. We analysed four different scenarios of simulation and the result then compared. The different number of hidden layers and iteration was used and evaluated to understand the effect of different parameters in the prediction result. The best scenario was then used to predict future land use changes. This study has successfully produced the future LULC model of Great Malang region with high accuracy level (87%). The study also found that the land use transformation from agriculture to urban built-up area is relatively low, where changes of the built-up area over three periods of analysis are below than 5%. This is due to the physical condition of Great Malang region where mountainous areas are dominated.

Land includes vegetation and water bodies and provides the basis for human livelihoods through primary production, the supply of food, freshwater, and multiple other ecosystem goods and services. The last three decades have recorded frequent drought events as well as rapid population growth, which has resulted in often negative land use and land cover change (LULCC) in the Sahel of Sub-Saharan Africa. In order to propose sustainable land management strategies, it is important to investigate the rate of LULCC and its driving factors in specific locations. This study investigated the case of Wocoro municipality in Mali using a combined approach of remote sensing, Geographical Information System, and focus group discussions. Satellite images and local people's perceptions on LULCC and drivers were collected and analyzed for the years 1990, 2000, 2010, and 2020. We found that the study area faced a severe decrease in wooded savannah with an increase in farmland and settlement directly or indirectly related to the rapid population growth, high cotton price (which encouraged cropland expansion), drought, firewood extraction, and charcoal production, which was exacerbated by poverty. There is a need to promote integrated land management strategies that consider current and future livelihoods needs and preserve the health of the environment for the benefits of future generations.

Biodiversity loss has been identified as one of the environmental impacts where humankind has been tres-passing planetary boundaries most significantly. Going beyond the pressures causing damages (calling them ‘direct drivers’) and analysing their underlying driving forces, IPBES, the Intergovernmental Sci-ence-Policy Platform for Biodiversity and Ecosystem Services, also identified a series of indirect drivers. The Montreal-Kunming Global Biodiversity Framework GBF including its suggested monitoring approach is intended to and claims to be a policy response to such analyses. However, to assess the human impact on ecosystems as a basis for planning conservation and restoration, as foreseen in the GBF, monitoring ecosystem typologies (in the GBF with reference to the UN statistical standard SEEA ES, which in turn refers to the IUCN ecosystem classification) is not enough. It needs to be complemented with data on the severity of human impacts, and on the history of places, i.e. how and when the current ecosystem status was brought about. In this conceptual paper we suggest LUI, a deliberately simple ordinal scale index for land use intensity changes, to address these two gaps. It is based on the hemeroby concept, measuring the human impact as deviation from naturalness. This makes it an information collection and presentation tool for those working in landscape planning and management. LUI’s simple and intuitively understandable structure makes it suitable for citizens’ science applications, and thus for participative monitoring when extensive statistical data gathering is not feasible, and past data are not available. Of course is can also be used as a simple too for communicating when detailed statistical data series are available. While the aggregate index is expected to communicate well, its components are more relevant to motivate and help policy makers to prioritise their decisions according to the severity of recent anthropogenic ecosystem disturabances.

The article presents the author's method of land use change assessment in the context of sustainable development and the results of its application based on the transformations that occurred in individual areas of Europe in the years 2012–2018. This method is based on data from the CORINE Land Cover program and local government units presenting the degree of urbanization (DEGURBA). The authors evaluate the transformations taking place in space, reducing them to economic, social and environmental dimensions. They then analyse the results in terms of space (covering the entire Europe) and in terms of division into: large cities, small towns as well as suburbs and rural areas. It has been shown that: development of the economic dimension most often takes place at the expense of natural resources; the higher the population density and more important function in the functional system of a given country, the greater the sustainable development differentiation level in the analysed dimensions, of which the social dimension is characterized by the lowest differentiation and the economic dimension is the highest; development of rural areas is less sustainable than in case of large urban centres. The result interpretation also leads to the conclusion that the areas of Europe are very diverse in terms of sustainable development. However, the method itself, despite the imperfections observed by the authors, may be used in further or similar studies.

Nowadays the relationship between planning land use and actual land use is not so clear in general. A lot of efforts have been put in the failures of regulation for the expansion of construction land. However, it still lacks an integrated approach to study the effectiveness of land use regulation in terms of different land use types. Furthermore, the existing evaluation of land use plan mainly focuses on a general level, a detailed research on the regulation effectiveness of each construction land use type is absent. Therefore, this research tries to evaluate regulation effectiveness of land use plan, which takes Cangwu country, Guangxi Province as an example. The finding by analysis is that the total area of construction land expansion was about 3494.73 ha, nearly 1.1 times of the plan quota. Moreover, the effectiveness differs greatly in various construction land use types. Town, industrial/mining sites can be well regulated through the quota of land use plan. While, the quota regulation system is not as effective for other type of construction land. Thus, we suggest to improve the regulation effectiveness of construction land through different plan instruments.

The natural and man-made landscape settings in the Khyber Pakhtunkhwa (KPK) province of Northern Pakistan have significantly changed in the last decade due to increasing demands of urbanized populace, migration, two major natural disasters, and climate change. The aim of this study is to analyze land possession, income and land-use diversification of KPK administered Charsadda district. Field data is collected through a sample survey. Furthermore, freely available Landsat 7 satellite images are used to classify land-use classes (e.g. vegetation, built-up) for two different years (e.g. 2005 and 2017) for cross-verification and comparison. The highest 45% of 80% land-owners occupy land-area between 1-10 hectares. Annually, the highest 57.5% of the total farmers / employed in-habitants of surveyed regions earn more than Rs. 100,000 or ~ $ 970 from agriculture activities. About 41.9% land-area covered by agricultural-land is transformed into built-up area since 2007, which is attributed to the increasing demand for buildings and commercial markets. The highest diversification is reported in Naguman area of Charsadda district followed by Rajjar and Niami. Population growth and huge migration of displaced persons from neighboring tribal areas are likely to be few factors which contributed to such a drastic change in land-use pattern since 2007 to 2017. Urgent attention of the policy makers, agricultural experts and society is required to minimize land degradation and to thwart further agricultural-land loss.

The natural and man-made landscape settings in the Khyber Pakhtunkhwa (KPK) province of Northern Pakistan have significantly changed in the last decade due to increasing demands of urbanized populace, migration, two major natural disasters, and climate change. The aim of this study is to analyze land possession, income and land-use diversification of KPK administered Charsadda district. Field data is collected through a sample survey. Furthermore, freely available Landsat 7 satellite images are used to classify land-use classes (e.g., vegetation, built-up) for two different years (e.g., 2005 and 2017) for cross-verification and comparison. The highest 45% of 80% land-owners occupy land-area between 1–10 hectares. Annually, the highest 57.5% of the total farmers / employed in-habitants of surveyed regions earn more than Rs. 100,000 or ~$970 from agriculture activities. About 41.9% land-area covered by agricultural-land is transformed into built-up area since 2007, which is attributed to the increasing demand for buildings and commercial markets. The highest diversification is reported in Naguman area of Charsadda district followed by Rajjar and Niami. Population growth and huge migration of displaced persons from neighboring tribal areas are likely to be few factors which contributed to such a drastic change in land-use pattern since 2007 to 2017. Urgent attention of the policy makers, agricultural experts and society is required to minimize land degradation and to thwart further agricultural-land loss.

Land-use planning review seems relatively lower in publication rate and in coverage of content. This review contributes its part in two dimensions. First, it assesses ability of the popularly growing bibliometric method in tracking the real contribution of publications. Then it summarizes developments in the land use planning literature in three themes - general literature path building, land use planning context, and development of methods. It is observed that bibliometric method rewards information carriage paper more than the original contributors. Key planning context gaps include detachment of the general goal-oriented objective formulations from the basic land use allocation theories and models and certain urban land use optimization objectives even contradict the original though of sustainable city. Key research frontiers include: linking basic land use allocation and utility theories in urban land use planning; shifting the current urban land use planning from spatial optimization to activities into optimizing flow resources to available spatial configurations; evaluating existing built environment for optimality; transferring knowledge from rural land-use planning to urban land use planning. In method development, the key frontier would be advancing the current loosely coupled methods into more integrated systems.

In the last two centuries, land use change (LUC) has been the most important direct changes driver for terrestrial ecosystems. To contrast the consequent ecosystems degradation, forward-looking spatial policies and target landscape and land-use planning processes, promoting a sustainable land use change, are needed. The present paper proposes a framework of action including different landscape planning and ecological approaches: from the spatial modelling to recognize the LUC and build different scenarios, to the ecosystem services (ESs) assessment to evaluate the possible environmental impacts. Three different scenarios were built: Trend, No-Tillage and Energy crops. The Sediment Delivery Ratio and Carbon Storage and Sequestration ESs were assessed and compared for each scenario. The aim of the paper is to support decision-makers and local communities into the landscape planning process. Results show that a regional development in line with past trend could lead to further land degradation. Instead, the two scenarios proposed in compliance with EU policies, could bring benefits only if related to moderate LUCs and respecting the naturally grass-vegetated land. From the local to global scale, a guided and shared LUC management allows implementing sustainable development, basing on a deep knowledge of physical-environmental but also social and economic issues.

Research Highlights: (1) Reed canary grass (RCG) is analysed in Sweden compared to willow and poplar for 2001-2020 (2) Each crop presents a different land-use and climatic profile (3) Average yield records of reed canary grass are similar to willow and poplar (4) There are divergences between trial-based and commercial yields (5) Existing LUC patterns suggest meadow>RCG and RCG>cereal (6) RCG land area is very sensitive to policy incentives. Background and objectives: RCG is an alternative crop for biomass-to-energy due to high yield and frost tolerance. We assess the cultivation in Sweden by using an extensive compilation of data, with emphasis on the extension of the cultivation, areas planted, climatic profile, land use patterns and yield levels. Material and methods: All RCG plantations are analysed for 2001-2020. A geostatistical analysis is performed to characterize where is cultivated and the land uses associated. Climatic, productivity and yield profiles are compared to willow and poplar plantations, from experiments and from commercial plantations. Results: The results show that the cultivation of reed canary grass expanded after 2005, with a maximum of 800 ha in 2009 to then decrease to the current levels of about 550 ha. It is mainly grown in colder climatic areas, with lower agricultural productivity than willow and poplar. Mean yields from trials are 6 odt ha-1 yr-1; commercial yields are 3.5 odt ha-1 yr-1. RCG replace meadow land and is replaced by cereals, when abandoned. Conclusions: Reed canary grass is an interesting alternative, growing on colder areas but on similar yield levels than other energy crops. The cultivation is more sensitive to policy incentives

Automated vehicles (AVs), which are expected to enter the market within the near future, represent the current frontiers in mobility and urban planning. AVs are assumed to bring substantial benefits to cities in many aspects. The present study attempts to investigate this broad assumption by conducting a literature review on the possible implications of AVs in cities as well as synthesizing the current state of practice of AV pilots to detect trends in their deployment. In this paper, literature findings on AVs’ implication on vehicle ownership, mobility, land use as well thirteen uses cases were synthesized to capture the big picture of them in cities. The findings showed that, in the AV pilots, the operation of AVs is limited to routes stretching less than 3.5km and an operation speed of less than 18km/h; low speed has been one of the main concerns of the participating passengers to use them for daily trips. The results also revealed that although shared AVs are expected in urban mobility, private ownership will stay competitive since vehicle ownership has been a socio-cultural identity in the history of automobiles. The findings also underlined that the potential influence of AVs on active mobility is still unclear as the AVs have not been introduced on a larger scale. Regarding AVs’ impact on land use, their introduction results in the effective use of space, but they will cause suburbanization in the long term.

Land Use Land Cover (LULC) changes analysis is one of the most useful methodologies to understand how the land was used in the past years, what types of detections are to be expected in the future, as well as the driving forces and processes behind these changes. In Ethiopia, the rapidly changing of LULC is mainly due to population pressure, resettlement programs, climate change, and other human and nature-induced driving forces. Anthropogenic activities are the most significant factors adversely changing the natural status of the landscape and resources, which exerts unfavourable and adverse impacts on the environment and livelihood. The main goal of the present work is to review previous studies, discussing the spatio-temporal LULC changes in Ethiopian basins, to find out common points and gaps that exist in the current literature, to be eventually addressed in the future. Seventeen articles, published from 2011 to 2020, were selected and reviewed, focusing on LULC classification using ArcGIS and ERDAS imagine software by unsupervised and maximum likelihood supervised classification methods. Key informant interview (KII), focal group discussions (FGDs) and collection of ground truth data using ground positioning systems (GPS) for data validation were the major approaches discussed in most of the studies. All the analysed research showed that, during the last decades, Ethiopian lands changed to agricultural land use, waterbody, commercial farmland and built-up/settlement. Some parts of forest land, grazing land, swamp/wetland, shrubland, rangeland and bare/ rock out cropland cover class were changed to other LULC class types, mainly as a consequence of increasing anthropogenic pressure. In summary, these articles confirmed that LULC changes are a direct result of both natural and human influences. However, most of the study provided details of LULC for the past decades within a specific spatial location, while they did not address the challenge of forecasting future LULC changes at the basin scale.

Developing countries like Pakistan is among those where lack of adoption to science and technology advancement is a major constraint for Satellite Remote Sensing use in crops and land use land cover digital information generation. Exponential rise in country population, increased food demand, limiting natural resources coupled with migration of rural community to urban areas had further led to skewed official statistics. This study is an attempt to demonstrate the possible use of freely available satellite data like Landsat8 under complex cropping system of Okara district of Punjab, Pakistan. An Integrated approach has been developed for the satellite data based crops and land use/cover spatial area estimation. The resultant quality was found above 96% with Kappa statistics of 0.95. Land utilization statistics provided detail information about cropping patterns as well as land use land cover status. Rice was recorded as most dominating crop in term of cultivation area of around 0.165 million ha followed by autumn maize 0.074 million ha, Fallow crop fields 0.067 million ha and Sorghum 0.047 million ha. Other minor crops observed were potato, fodder and cotton being cultivated on less than 0.010 million ha. Population settlements were observed over an area of around 0.081 million ha of land.

Abstract: Increasing population and urbanization are affecting human health and comfort. In order to get rid of these affects, mankind is changing its enviroment and looking for new life areas. This study investigates the influence of Land Cover Change (LCC) and Normalisied Densly Vegetation Index (NDVI) on Land Surface Temperature (LST) of Fethiye-Göcek Specially Protected Area (SEPA) in easterm mediterranean basin. In the study LCC, NDVI and LST were drived from landsat 5, 7 and 8 satellite image of resolation at 30x30 m acquired between 1995-2020. LST were computed based on Land Use/Land Cover (LULC) types. The Corine Index were used for determination of land uses. The results indicated that water, forest and maquia lands decreasing while urban fabric and bare lands are increasing depend upon the urbanization and forest fires in the basin. These changes in LULC widened the temperature differences between the urban and rural areas. The change in LST is associated with changes in constructional materials in urban land and in vegetation abundance both in the urban and rural areas. Vegetation has an important factor in the temperature of different land covers. That produces warming trend in temperetaure in built-up areas it causes to keep other lands warmer in cold weather. Another important result is affective Urban Heat Island (UHI) on climate change based on the impact of urbanization and land cover changes. Significantly possitive correlation were found between the urbanization rate, population and built-up area and warming rate of average air temperature and so the LST.

In the future, the pursuit of high-quality economic development and a focus on ecological environmental protection in China will inevitably result in significant conflicts between land use and ecological land use. The challenge lies in achieving sustainable high-quality development while simultaneously protecting the ecological environment, optimizing the land use structure, and promoting a harmonious relationship between humans and the land. These challenges are faced by all regions. Land use conflicts primarily occur in peri-urban areas characterized by prominent economic development and urban agglomeration. Previous studies have mainly focused on analyzing the effects of land use on habitat quality during intense urbanization. However, it is important to recognize that land pressure encompasses economic, ecological, and social aspects. To gain a comprehensive understanding of the spatial conflict of land use and the impact on habitat quality in Ankang, a city that has been advocating ecological protection for the past two decades, this study aims to objectively analyze the spatial trends in land use changes in such cities. Additionally, it aims to provide insights for the harmonious development of land use in eco-region-oriented cities. Using the SSP-RCP scenarios provided by CMIP6, this paper employs a system analysis method, PLUS model, InVEST model, and land use conflict measurement model to dynamically simulate the future habitat quality and spatial conflict patterns of land use in Ankang City. The study explores the spatial coupling effect of both factors under different scenarios. The results indicate the following:(1) Under different future shared socio-economic path scenarios, land use intensity and land conflict levels follow the order of SSP585 (high forcing scenario), SSP370 (medium to high forcing scenario), SSP245 (medium forcing scenario), and SSP126 (low forcing scenario), with intensity and conflict decreasing accordingly. (2) The overall development trend in Ankang City reveals an intensification of land use conflicts and a decrease in habitat quality. The expansion rate of construction land is increasing and exhibiting aggregation, while agricultural land area is expanding and forest land area is continuously decreasing. (3) Land use intensity exhibits a significant positive correlation with land conflict levels, while land conflict levels demonstrate a significant negative correlation with habitat quality. These findings suggest that land use has had some impact on the ecological environment, with indications of habitat degradation. Even in Ankang, where ecological development is highly valued, the city will gradually face conflicts between ecological protection and economic development in future scenarios. The study highlights that Ankang's future development space will be constrained within the context of environmental protection, leading to greater land use conflicts in urban and surrounding areas. Consequently, the quality of habitats will inevitably decline. Therefore, it is crucial to allocate sufficient space for economic development while simultaneously prioritizing ecological protection. This approach will ensure a healthy economic development trajectory and foster a harmonious relationship between humans and the land.

Deforestation brings vast and detrimental impact on the environment, economy, and social aspects of community. Thus, it is important to assess and analyze deforestation to inform the decision maker that oversees issued policy and development strategies. The present study aims to characterize deforestation in Central Kalimantan between 2006 - 2020. Utilized land cover map issued by Indonesian Ministry of Environment and Forestry, we analyzed the change in natural forest cover using Remote Sensing and Geographical Information System (GIS) to find the rate the trend, location, and land cover replacement of deforestation in Central Kalimantan Province, Indonesia. The research found that during the period Central Kalimantan lost 1.5 million ha of natural forest with the rate of deforestation 117,000 ha/year. In general, the deforestation shown decrease trend and fluctuated during the period. Deforestation majority takes place at secondary swamp and dry forest that are located at south part of the island. Most of deforestation resulted shrubs, plantations, and agriculture land. The finding of this research could be used as a base to determine the target location for rehabilitation strategy and approach to prevent further deforestation.

The rapid increase in population along with the economic activities led to rapid depletion of natural resources. Land use studies help us analyze the impacts of urban development on environment. Given the political upheavals in Afghanistan, this study aims to analyze how urban development evolved from 1978 to 2018 in six major cities- Kabul, Kandahar, Kunduz, Herat, Mazar-e Sharif and Jalalabad- in Afghanistan using Landsat Satellite Images. This study is based on quantitative approach. ArcGIS 9.4 software was used to synchronize the Landsat Satellite Images within the area of study. The results of the study show that the Annual rate of urban land expansion in Afghanistan was the lowest (average 1.07 square kilometers per year) during the military presence of Soviet Union in Afghanistan while it was the highest (3.35 square kilometers per year) from 2001 to 2018 due to the military presence of US-led NATO forces, relative security and rapid economic activities in Afghanistan. The authors believe that this study could be further explored if other inter-connected factors, e.g., the role of culture, literacy, immigration etc., are incorporated into the study of urban development processes in Afghanistan.

Urban cities are the major drivers of economic growth and development. Economic growth and development however results in considerable land cover land use dynamics. This study assessed the dynamics in land cover land use that have occurred in New Braunfels, Texas in the last 7 years (2013 - 2020) to observe areas in the city that had experienced considerable shifts in land cover and land use. A 30-meter resolution Landsat images were used to examine possible changes in land cover land use. New Braunfels was observed to have experienced significant changes in land use especially in developed areas. This change can be attributed to the influx of people into the city, contributing to the need for increased urban development. Analysis of this study shows that about 16% (about 553 hectares) of forest land cover class and 28% (about 1,139 hectares) of grassland class in time 1 (August 31, 2013) changed to built-up land use class in time 2 (November 5, 2020). A limitation to this study was that of the spatial resolution of images used. Higher spatial resolution images could impact the producers, users, and overall accuracy assessment. Results from this study can aid in supporting better decision-making for sustainable urban development and climate change mitigation.

The information on the land use and soil conservation practice based on year 2006, 2010 and 2014, hence offering an opportunity to model the impacts of land use change on erosion, deposition and surface water runoff. Limitation in the use of hydrological models had been their inability to handle the large amount of input data that describe the heterogeneity of the natural system. In this study, a procedure that takes into account soil conservation practice based on the land use change, the response of soil erosion and sediment export from the George Town Conurbation catchment area, and average annual sediment yields were estimated for each grid cell of the watershed to identify the critical erosion areas of rural and urban planning proposes. Average annual sediment yield and data on a grid basis estimated using Universal Soil Loss Equation (USLE) and an emerging technology represented by Geographic Information System (GIS) used as a tool to produce a map for erosion rate. The changing of the land use from forest to agriculture and then to an urban area is a challenging task to research on land use demand for population, and environmental impact assessment is important for the planning of natural resources management, allowing research the modification of land use properly and implement more sustainable for long term management strategies. The challenge is to formulate strategies that would promote an integrated approach to the land use planning at an appropriate level as to address the issues that arose. Modelling for creating urban growth boundary for the George Town Conurbation must have to be controlled surface runoff and soil loss and sediment export from land use of the George Town Conurbation catchment.

LULC changes are major environmental challenges in many parts of the world which are adversely affecting ecosystem services. This study was aimed to analyze LULC changes in the ecological landscape of Ethiopia CRV areas from 1985 to 2015. Satellite images were accessed and pre-processing and classification is done. Major LULC types were detected and change analysis was executed. Nine LULC changes were successfully evaluated. The classification result revealed that in 1985, 44.34% of the land was covered with small scale farming followed by mixed cultivated/acacia (21.89%), open woodland (11.96%), and water bodies (9.77%). Whereas for the same study year open grazing land, forest, degraded savannah and settlements accounted the smallest proportion. Though the area varied among land use classes, the trend of share occupied by the LULC types in the study area remained the same in 1995 and 2015. Increase in small and large scale farming, settlements and mixed cultivation/acacia while a decrease in water bodies, forest, and open woodlands is noted. About 86.11% of the land showed major changes in land use/cover. Lastly, DPSIR framework analysis was done and integrated land use and development planning and policy reform are suggested for sustainable land use planning and management.

The suppression of natural spaces due to the urban sprawl and increase of the built and agricultural environments has impacted the water resources quality, especially in areas with high population density, as the metropolitan regions. Considering the advance in Brazilian environmental legal framework, the present study aims to verify whether land use has still significantly affected water quality, through a case study in the Stones River watershed, a peri-urban river basin at a metropolitan region, Brazil. Analysis of physical-chemical indicators, collected at several sample points with different land-use (urban areas, commercial forestry, riparian forestry, mixed vegetation, pasture, and sugar cane plantation) at different seasons of the year (dry and rainy) were carried out. As a result, it was verified some statistically significant spatiotemporal effects on the of water quality caused associated to the land-use. In conclusion, in spite of the advances in the Brazilian law, land-use has still significantly affected the water quality, demanding public policies and decisions, so that effective compliance with legal guidelines is ensured.

Quantity-intensity characteristics are among conventional approaches for studying potassium dynamics and its availability; this was assessed to determine availability in four districts: namely, Sodo Zuria, Damot Gale, Damot Sore, and Boloso Sore at three different land use type viz., enset-coffee, crop land, and grazing land. There was water soluble, ammonium acetate, nitric acid extractable potassium, exchangeable potassium, and non-exchangeable potassium studied in soil samples, which were collected from 0-20 cm depth of each land type. The study revealed that water soluble and ammonium acetate extractable potassium concentrations ranged from 0.04 to 0.42 cmolKg-1 soils enset-coffee and grazing land use types, respectively. The study showed that exchangeable potassium constituted the highest proportion of available potassium, while the proportion of water soluble potassium was found to be the lowest. In this study, non-exchangeable potassium concentrations varied from 0.10 to 0.04cmolKg-1soils for enset-coffee, and crop and grazing land use type. Furthermore, available potassium and exchangeable potassium concentrations were positively correlated with OC(r=0.95***), cation exchange capacity, and sand and clay(r=0.98***). In addition, the K dynamics as impacted by land use types found that the highest change in exchangeable potassium (0.31cmolkg-1soils) and potential buffering capacity (1.79cmolkg-1soils) were noted in crop land use types, whereas the lowest change(1.26cmolkg-1 soils) was observed in the enset-coffee system, The varying properties, potassium status, dynamic and land use type of soils identified in the study areas provided adequate information to design soil potassium management options and further research about the soil in each site. Therefore, application of site specific soil fertility management practices and research can improve soil potassium status and quantity intensity parameters to sustain crop productive soils.

This paper aims to build up a preference function to evaluate the public benefits of the type of agricultural farming, biodiversity, water provisions, land use type, ecotourism modes, and a monetary attribute (environmental trust fund and willingness to contribute) associated with an ecosystem service and land use program in a forest park. This study used the choice experiments to build a random utility model, analyze the average preference for the above land use attributes based on the conditional logit and used a latent class model to test the resident’s heterogeneous preferences for land use planning in the forest park. We also estimated the welfare derived from various land use programs. The empirical result had shown that: (1) increasing organic farming area, maintaining the status quo of species biodiversity, increasing the surface water provision, increasing the area of custom flora, increasing the wetland area, and setting up an integrated framework for ecotourism increase the public’s preference for the land use program; (2) we found that farmer and non-farmer haven’t the same land use preferences; (3) the ecotourism development program incorporating biodiversity, organic farming, ethnobotany, and wetland area with integrated ecotourism are more preferred than other land use program scenarios.

Although urbanization has contributed to improving living conditions, it has had negative impacts on the natural environment in the urbanized areas. Urbanization has changed the urban landscape and resulted in increasing land surface temperature (LST). Thus, studies related to LST in various urban environments have become a popular research topic. However, few LST studies focusing on the mountain landscapes (i.e. hill stations) have been carried out. The primary objective of this study is to investigate changes in the landscape and their impacts on LST intensity (LSTI) in the tropical mountain city of Nuwara Eliya, Sri Lanka. The study utilized annual median temperatures extracted from Landsat data collected from 1996 to 2017 based on the Google Earth Engine (GEE) interface. The fractions of built-up (BL), forest (FL), and agricultural (AL) land were calculated using land use and cover maps based on the urban-rural zone (URZ) analysis. The urban-rural margin was demarcated based on the fraction of BL (<10%) and LSTI was measured using the mean LST difference in the urban-rural zone. In addition, the mixture of land use types was calculated using the AL/FL and BL/FL fraction ratios, and grid-based density analysis. The result shows that the BL in all URZ rapidly developed, while AL decreased during the period 1996 to 2017. There was minimal change in the forest area of the Nuwara Eliya owing to the government forest preservation policies. The fraction of the BL increased from 32.4% in 1996 to 58.7% in 2017 in the city center zone (URZ₁) resulting in increased mean LST by 4.7 °C. Furthermore, the increase of the BL/FL fraction ratio and the decrease of the AL/FL fraction ratio were positively correlated with the mean LST. Grid-based analysis showed an increasing positive relationship between mean LST and density of BL. This indicated that BL density has been a crucial element in increasing LST in the study area. The results of this study will be a useful indicator to introduce improved landscape and urban planning in the future to minimize the negative impact of LST on urban sustainability.

Keywords: Lightning; Land Cover and Land Use; Topographic Effects, Itacaiúnas River Hydrographic Basin

The rapid growth of urban areas is a major challenge facing cities around the world. This growth can have a significant impact on the local climate, leading to higher temperatures and other changes. In desert climates, the effects of urban expansion can be particularly pronounced. This study investigated the impact of urban expansion on land surface temperature (LST) in Baghdad, Iraq. Notably, this study employs a sophisticated artificial intelligence method known as Random Forest for Land Use Land Cover (LULC) classification, utilizing three Landsat images spanning the temporal spectrum from 1985 to 2021 to meticulously monitor land use transformations and associated LST variations. The results showed that vegetated areas declined by 46.8% during the study period, while built-up areas increased by 124.7%. This decline in vegetation was accompanied by an increase in LST, with bare soil recording the highest temperatures. The study also found that LST has a strong inverse relationship with vegetation and moisture. This means that areas with more vegetation and moisture tend to have lower LSTs. These findings suggest that urban expansion can lead to higher LSTs in desert climates, which can have implications for the health and wellbeing of residents. The study has important implications for urban planners and policymakers in Baghdad and other cities in desert climates. By identifying the main factors that control LST, the study provides insights into strategies for mitigating the effects of urban expansion on temperature.

In Nigeria, desertification has become one of the most pronounced ecological disasters, with the impacts mostly affecting eleven frontline States. This has been attributed to a range of both nat-ural and man-made factors. This study applied a remote sensing-based change detection and indicator analysis to explore land use/land cover changes and detect major conversions from ecologically active land covers to sand dunes. Results indicate that areas covered by sand dunes (a major indicator of desertification) have doubled over the 25 years under consideration (1990 to 2015). Although about 0.71 km2 of dunes have been converted to vegetation, indicative of the success of various international, national, local, and individual afforestation efforts, conversely about 10.1 km2 of vegetation were converted to sand dunes, implying around 14 times more de-forestation compared to afforestation. Juxtaposing the progression of sand dune with climate records of the study area and examining the relationship between indicators of climate change and desertification suggested a mismatch between both processes as increasing rainfall and lower temperatures observed in 1994, 2005, 2012, and 2014 did not translated into positive feedbacks for desertification in the study area. On average, our results reveal that sand dune is progressing at a mean annual rate of about 15.2 km2 in the study area. Based on this study’s land cover change, trend and conversion assessment, visual reconciliation of climate records with land cover data, statistical analysis, observations from ground-truthing, as well as previous literature, it can be inferred that desertification in Nigeria is less a function of climate change, but more a product of human activities driven by poverty, population growth and failed government policies. Further projections by this study also reveal a high probability of more farmlands being converted to sand dunes by the year 2030 and 2045 if current practices prevail.

Land use land cover (LULC) changes are highly pronounced in African countries, as they are characterized by an agriculture-based economy and a rapidly growing population. Understanding how land use/cover change (LULCC) influence watershed hydrology will enable local governments and policymakers to formulate and implement effective and appropriate response strategies to minimize the undesirable effects of future land use/cover change or modification and sustain the local socio-economic situation. The hydrological response of the Ethiopia Fincha’a watershed to LULCC happened during the last 30 years was investigated comparing the situation in three reference years: 1994, 2004 and 2018. The information was derived from Landsat sensors, respectively Landsat 5 TM, Landsat 7 ETM and Landsat 8 OLI/TIRS. The various LULC classes were derived via ArcGIS using a supervised classification system, and the accuracy assessment was done using confusion matrixes. For all the years investigated the overall accuracies and the kappa coefficients were higher than 80%, with 2018 as the more accurate year. The analysis of LULCC revealed that forest decreased by 19.99% between the years 1994-2004, and it decreased by 11.85% in the following period 2004-2018. Such decline in areas covered by forest is correlated to an expansion of cultivated land by 16.4% and 10.81%, respectively. After having evaluated the LULCC at the basin scale, the watershed was divided into 18 sub-watersheds, which contained 176 Hydrologic Response Units (HRUs), having a specific LULC. Accounting for such a detailed subdivision of the Fincha’a watershed, the SWAT model was firstly calibrated and validated on past data, and then applied to infer information on the hydrological response of each HRU on LULCC. The modelling results pointed out a general increase of average water flow, both during dry and wet periods, as a consequence of a shift of land coverage from forest and grass towards settlements and build-up areas. The present analysis pointed out the need of accounting for past and future LULCC in modelling the hydrological responses of rivers at the watershed scale.

Land price sustainability issues have been addressed by many authors in the past. Most of these researchers used land prices (from land price maps) as the primary data source in their studies. Only a few papers analysed official land price maps, which are available very rarely. For this reason, we studied the spatial and temporal changes of land prices in the city of Olomouc based on an analysis of official land price maps from 1993 to 2017. We proposed several research hypotheses to confirm some general statements about land price development. We concluded that some macroeconomic indicators had a significant impact on changes in land prices. In the residential and commercial areas and historical centre, land prices are significantly higher than in other monitored aspects (land-use types). We also concluded that no link existed between land-use stability and land price stability. Surprisingly, no long-term stable areas were found in the area of interest. The analysis also confirmed that land price and its change over time varied in different spatial aspects. Surprisingly, the smallest influence was reflected in the economic aspect. Regarding natural events in recent decades, we observed a significant drop in land prices in the vicinity of watercourses threatened by flooding. These findings can assist in better understanding local development and changes in land price.

Affem Boussou community forest (AFC) abounds in important biological resources. This study, which contributes to its better management, examines the spatiotemporal dynamics of the vegetation and its ecological and structural characteristics to propose a zoning plan for the said forest. The analysis of the spatiotemporal dynamics of land use in the AFC from Google Earth images of 2015, 2018, and 2021 revealed a regressive trend of formations: crops and fallows (-33.98%), dense dry forests (-7.92%), gallery forests (-3.46%), plantations (-100%), grassy savannahs and meadows (-18.84%) except for tree/shrub savannahs (484.23%). The floristic inventory identified 163 species divided into 129 genera and 55 families. Fabaceae (14.02%), and Combretaceae (10.55%) are the most represented families. Anogeissus leiocarpa (5.19%) and Vitellaria paradoxa (4.72%) are the most frequent species. We note the dominance of individuals of small diameters. The regeneration potential of the AFC is 64 feet/ha due to 21 feet/ha of suckers, 29 feet/ha of seedlings, and 14 feet/ha of shoots. As a zoning plan, the AFC was subdivided into four series: the agroforestry zone (18.80%), the sustainable production forest zone (42.22%), the buffer zone (11%), and the biological conservation zone (28%). These results constitute a scientific basis for testing ecological indicators of sustainable management of community forests in Togo.

While the scientific community has focused on documenting environmental degradation and developing scenarios that help identify the operational margins for system Earth, less attention has been given to the mental models of decision-makers that underpin environmental policies. We suggest that global efforts to stop deforestation and biodiversity loss are failing in part due to a critical blind spot in the analysis—human agency. To address this weakness, we propose to formulate mental models and translate them into strategy games. This will increase the representation of agency in scenario development and create spaces for deliberation between different worldviews. We claim that personal transformation can be achieved through transparent democratic dialogues that identify, challenge, and respond to the human and social limitations inherent to decision-making and we present empirical examples that validate that claim. Their transformation through gaming gives decision-makers access to the experience of consciousness: “what is it like being a stakeholder?”. Such experience will help to break free of established norms in science and political processes.

Changes in agricultural policy may have rapid impact even on landscapes which have taken millennia to form. Here we explore the potential of UK leaving the EU as a catalyst for profound changes in pastoral landscapes in Wales. Impending change of the trading regime governing agricultural produce, concurrent to public pressure to use agricultural subsidies for environmental goals, may lead to unforeseen consequences for Welsh natural environment. We employ a combination of change demand modelling and ‘story and simulation approach’ to predict the effect of five hypothetical scenarios on land use and land use change in Wales by 2030. We show that the most extreme trade scenario would result in a near-uniform distribution of broadleaf woodland across most of Wales. Abandonment of marginal and low productivity grazing would likely give way to afforestation, initiating a return to forested landscapes not seen in Wales for several thousands of years.

Leclère et al.¹ have outlined the possibility of a biodiversity transition for the 21^st century, a line of thinking equivalent to the Forest Transition theory and what it says about forest cover globally². The authors use a suite of global models to explore the impacts on global biodiversity of interventions on land-use, consumption and production patterns. They outline six strategies that have the potential to stop the downfall of global terrestrial biodiversity by 2050 and redress it to a pre-1970 level by 2100. Although robust, sophisticated and well-illustrated, the conclusions of this paper cannot alone be used to frame a post-2020 biodiversity strategy.

The aim of this paper is to study changes in land use and the evolution of vegetation in Cacheu River Mangroves Natural Park in the Republic of Guinea-Bissau. To do this, we will study variations in the NDVI, Normalized Difference Vegetation Index. In order to perform the calculations and subsequent analysis, images from three years— 2010, and 2017—were used, all corresponding to the same time of year so that the phenological stage is the same. To perform a more reliable analysis, the park was divided into five classes based on the main use of the land: mangals, palm forest, paddy fields, savannahs and others. Using a statistical sample, same areas were selected for each class and the corresponding NDVIs were calculated for the years in which ASTER images were available. The study made it possible to conclude that at present, management of the park is not the most suitable, given that the changes in land use observed represent a decrease in mangrove swamps, despite the fact that these forests constitute the most important ecological area of all those that make up the park. Mangals are being replaced by other land uses.

The coordination planning between land use and transportation system is an important premise of solving urban transportation problems and realizing land use integration. This study investigates the interactive and feedback relationship between land use and transportation system from the perspective of access management. By integrating the land use and traffic data from Las Vegas Metropolitan area with the system dynamics model, the causal relationship and causal loop diagrams (CLDs) are introduced to analyze the cause-and-effect relationship and quantitative relationship between the factors of the combined system of land use and transportation, and then sub-models partition and system simulation are performed. The systems dynamics model is established by analyzing the relationship between a series of access management techniques, traffic characteristics, and land use features. The results show that system dynamics model can be used as an effective alternative to model the symbiosis relationship of land use and transportation system for urban planning and construction.

Pekalongan is one of several cities that lies in the northern coast of Java island which is often flooded due to sea level rise. This condition impacted its urban development characteristic and increase in the future. In this research both Geographical Information System based and Spatial Metric approach are used. The spatial pattern is analyzed by using spatial metric based on the exploration of land use change that occurred. In this research, the spatial pattern is focused on aggregation pattern and diversity in coastal area. The result shows that the land use of coastal area are dominated with swamp, then followed by settlement and fishpond. It is also shown that the greatest land use change occurred on paddy field and swamp areas. Based on the spatial metric calculation, the aggregation level of land use decrease periodically and has a small growth level. It is indicated from its metric value aggregation and diversity from two periods: 2003-2009 and 2009-2016. Overall the land use of Pekalongan experienced large dynamics, especially in its coastal area. The spatial pattern trend in those area tend to be more sprawl as defined by the decrease of aggregation pattern and low level of land use growth pattern.

Pekalongan is one of several cities that lies in the northern coast of Java island which is often flooded due to sea level rise. This condition impacted its urban development characteristic and increase in the future. In this research both Geographical Information System based and Spatial Metric approach are used. The spatial pattern is analyzed by using spatial metric based on the exploration of land use change that occurred. In this research, the spatial pattern is focused on aggregation pattern and diversity in coastal area. The result shows that the land use of coastal area are dominated with swamp, then followed by settlement and fishpond. It is also shown that the greatest land use change occurred on paddy field and swamp areas. Based on the spatial metric calculation, the aggregation level of land use decrease periodically and has a small growth level. It is indicated from its metric value aggregation and diversity from two periods: 2003-2009 and 2009-2016. Overall the land use of Pekalongan experienced large dynamics, especially in its coastal area. The spatial pattern trend in those area tend to be more sprawl as defined by the decrease of aggregation pattern and low level of land use growth pattern.

Global croplands, pastures, plantations, and human settlement areas have expanded in recent decades, accompanied by large increases in energy, water, and fertilizer consumption, along with considerable losses of biodiversity. In sub-Saharan Africa, policies are implemented without critical consideration e.g., agricultural expansions impair ecosystem services of the several river basins. The current study has studied landuse/cover and associated rate of change for four-time epochs i.e., 1991, 2001, 2011 and 2021. This employed remote sensing and GIS techniques for LULC analysis while future projection was modelled using cellular automata and Markov chain. The Kappa coefficient statistics were used to assess the accuracy of final classified image while reference images for accuracy assessment were developed based on ground truthing. Overall change results between 1991 and 2021, showed that major percentage loss in area were experienced by water, forest, woodland and wetland which decreased by 8,222Ha (44.11%), 426,161Ha (35.72%), 399,584Ha (35.01%) and 105,186Ha (34.82%). On the other hand, percentage increase in area during the same period were experienced in cultivated land, built up areas and grasslands which increased by 659,346Ha (205.28%), 11,894Ha (159.93%) and 33,547Ha (98.47%). However, even with the expanding thirsty sectors water discharged out of the catchment is on increment at a rate of 498.6 m3/s/year. For dualistic benefits, agroforest practices are recommended along with participatory law enforcement and capacity building of local communities through their institutions.

Detecting abrupt transitions in ecosystems, known as regime shifts, holds immense implications for conservation and management endeavors. This research aims to investigate the feasibility of developing an early warning system capable of identifying an upcoming critical transition within Mangrove Forest ecosystems. Employing a fusion of remote sensing analysis, time series analysis, and the critical slowing down theory, Mangrove Forests' state change was explored across two distinct study sites. One site has been adversely affected by disturbances stemming from land use and land cover changes, while the other serves as an unaffected reference ecosystem. The study uses data from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite, quantifying three remotely sensed indices: the Normalized Difference Vegetation Index (NDVI), the Modified Normalized Difference Water Index (MNDWI), and the Modified Vegetation Water Ratio (MVWR). Furthermore, temporal alterations in land-use and land cover are scrutinized using Landsat data from 1996, 2002, 2008, and 2014. To identify early warning signals of critical transitions, indicators such as autocorrelation, skewness, and standard deviation are applied. The results show the robust capabilities of remote sensing in generating early warning signals of critical transition in Mangrove Forests. NDVI outperformed MVWR and MNDWI as ecosystem state indicators. This study not only highlights the potential of remote in identifying the approaching regime shifts in Mangrove Forest ecosystems but also adds knowledge on ecosystem dynamics. This is the first report of the successful application of remote sensing in generating early warning signals for imminent critical transitions within Mangrove forests in the Middle East.

In several Indonesian tropical cities, such as Makassar City, frequent flooding during the peak rainy season poses a significant challenge. This study seeks to address this issue by devising effective policies to reduce flood exposure. The main obstacle lies in accurately determining the flood inundation area. To overcome this, the study utilizes multiple satellite data sources on a cloud platform, integrating them with land use data, and DEM data, aligning these with the local government's urban land use plan and existing drainage networks. The research aims to quantify the affected area, identify the predominant inundated land cover, and assess the efficiency of Makassar's drainage system and urban land use plan. The study reveals that an uncoordinated drainage system in the Tamalanrea, Biringkanaya, and Mangala sub-districts results in severe flooding, encompassing a total area of 35.28 km². The most affected land use type is cultivation, constituting approximately 43.5% of the flooded area. Furthermore, 82.26% of the urban land use plan, covering 29.02 km², is submerged. It is imperative for the local government and stakeholders to prioritize the enhancement of drainage systems and urban land use plans, particularly in low-lying and densely populated regions

Land use and land cover (LULC) datasets for Jinan in 1992, 1998, 2002, 2006, 2011, 2017, and 2022 were developed from Landsat images using the Random Forest (RF) classification approach. The relationships between social-economic, political factors and time-series LULC data were exam-ined for the periods between 1992 and 2022. The results showed the effectiveness of using the RF classification method for LULC classification with time series of Landsat images. Combined with driving forces analysis, our research can effectively explain the detailed LULC change tra-jectories corresponding to different stages and give new insights into Jinan LULC change pat-terns. The results show a significant increase in impervious surface which opposite change to bare land which experienced a huge decline declined by 95%, due to urbanization and rapid in-crease of population. The driving forces behind these changes are related to population growth, economic development, and climate change. Moreover, the present research employed Principal Components Analysis (PCA) methodology in order to understand the relative significance of disparate driving factors. The analysis results prove that the economy (population, GDP) and climate change were the primary factors that have an obvious impact on land use/land cover changes and that the driving factors for impervious surface, bare land, woodland, farmland, and water were distinct. Government policies also have a substantial impact on LULC change as well, such as the Construction of Harmonious Jinan (COHJ). The results were helpful for better understanding the mechanisms of LULC change and can provide useful knowledge for effective land resource management and planning.

Satellite-based data classification performance remains a challenge for research community in the field of land use/land cover mapping. Here we investigated supervised per-pixel classifications performance under different scenarios, based on single and seasonal multispectral data combi-nations of different sensors (Landsat-8 OLI and Sentinel-2 MSI). In case of Landsat, seasonal spectral indices (EVI and NDMI) were included. A typical Mediterranean watershed with a complex landscape comprised of various forest and wetland ecosystems, crops, artificial surfaces, and lake water was selected to test our approach. All available geospatial data from national databases (Forest Map, LPIS, Natura2000 habitats, cadastral parcels, etc.) are used as ancillary data for clas-sification training and validation. We examined and compared the performance of ML, RF, KNN and SVM classifiers under different scenarios for land use/land cover mapping, according to Copernicus Land Cover (CLC2018) nomenclature. In total, eight land use/land cover classes were identified in Landsat-8 OLI and nine in Sentinel-2a MSI for an acceptable overall accuracy over 85%. A comparison of the overall classification accuracies shows that Sentinel-2a overall accuracy was slightly higher than Landsat-8 (96.68% vs. 93.02%). Respectively, the best-performed algorithm was ML in Sentinel-2 while in Landsat-8 was KNN. However, machine-learning algorithms have similar results regardless the type of sensor. We concluded that best classification performances achieved using seasonal multispectral data. Future research should be oriented towards inte-grating time-series multispectral data of different sensors and geospatial ancillary data for land use/land cover mapping.

Land use land cover change analysis is one of the most particular techniques to understand how land was used in the past, what types of changes are to be expected in the future, as well as the forces and processes behind the changes. Thus, the objective of this study was to investigate the land use land cover changes and its driving forces in Mago National Park, southern Ethiopia. Satellite image of Landsat5 TM (1988, 1998 and 2008) and Landsat8 OLI/TIRS (2018) with a time span of 30 years were employed. In addition, field observation, and social survey were conducted to study the drivers of land use land cover changes. QGIS 3.2 and SPSS (for social data analysis) software’s’ were used for satellite image processing, accuracy assessment, map preparation and descriptively analyze the driving forces of LULCC respectively. Supervised classification with maximum likelihood algorithm was conducted for satellite image analysis and generation of information using Quantum GIS 3.2 Post classification change detection method was applied to quantify the land use/land cover change. The result of the study indicated riverine forest, woodland, grassland, water body, degraded land and bare land as a major land use land cover class in the park. The result of land use land cover classification showed that in 1988 most of the study area was covered by woodland and grass land. In the first period (1988-1998), woodland, riverine forest, water body and bare land decreased by 6.76%, 37.98%, 22.37% and 70.14% respectively, while grass land, and degraded land increased by 16.11% and 85.67% respectively. In the second period, (1998 -2008), woodland, riverine forest and degraded land were decreased by 5.44%, 4.61%, and 80.74% respectively, while grass land, water body and bare land is increased by 14.74%, 3.76% and 52.58% respectively. From 2008-2018 riverine forest, grassland, water body and bare land decreased by 1.33%, 15.16% and 4.82% and 25.02% respectively, while woodland increased by 11.84%, and degraded land increased by 85.49% respectively. Riverine forest, water body, grass land and bare land showed decrement and that of woodland, degraded land indicated increment during study period. From 1988-2018, woodland, riverine forest, water body and bare land indicated decrement and the remaining grass land and bare land cover types indicated increment during study period. The result of social survey indicated that expansion of agriculture, human induced fire, overgrazing and hunting are proximate driving forces of the change in Mago National Park. Population pressure from a different area, poverty, decreased farmlands productivity; education, weak law enforcement and cultural factors are the major underlying causes of the observed changes. Therefore, proper land use planning, legal support, and strong law enforcement are the key recommendations to sustain natural resources of the study area.

There are many new land use and land cover (LULC) products emerging yet there is still a lack of in-situ data for training, validation, and change detection purposes. The LUCAS (Land Use Cover Area frame Sample) survey is one of the few authoritative in-situ field campaigns, which takes place every three years in European Union member countries. More recently, a study has considered whether citizen science and crowdsourcing could complement LUCAS survey data, e.g., through the FotoQuest Austria mobile app and crowdsourcing campaign. Although the data obtained from the campaign were promising when compared with authoritative LUCAS survey data, there were classes that were not well classified by the citizens, and the photographs submitted through the app were not always of sufficient quality. For this reason, in the latest FotoQuest Go Europe 2018 campaign, several improvements were made to the app to facilitate interaction with the citizens contributing and to improve their accuracy in LULC identification. In addition to extending the locations from Austria to Europe, a change detection component (comparing land cover in 2018 to the 2015 LUCAS photographs) was added, as well as an improved LC decision tree and a near real-time quality assurance system to provide feedback on the distance to the target location, the LULC classes chosen and the quality of the photographs. Another modification was the implementation of a monetary incentive scheme in which users received between 1 to 3 Euros for each successfully completed quest of sufficient quality. The purpose of this paper is to present these new features and to compare the results obtained by the citizens with authoritative LUCAS data from 2018 in terms of LULC and change in LC. We also compared the results between the FotoQuest campaigns in 2015 and 2018 and found a significant improvement in 2018, i.e., a much higher match of LC between FotoQuest Go Europe and LUCAS. Finally, we present the results from a user survey to discuss challenges encountered during the campaign and what further improvements could be made in the future, including better in-app navigation and offline maps, making FotoQuest a model for enabling the collection of large amounts of land cover data at a low cost.

Analysis of the hourly Canadian Prairie data for the past 60 years has transformed our quantitative understanding of land-atmosphere-cloud coupling. The key reason is that trained observers made hourly estimates of opaque cloud fraction that obscures the sun, moon or stars, following the same protocol for 60 years at all stations. These 24 daily estimates of opaque cloud data are of sufficient quality that they can be calibrated against Baseline Surface Radiation Network data to give the climatology of the daily short-wave, longwave and total cloud forcing (SWCF, LWCF and CF). This key radiative forcing has not been available previously for climate datasets. Net cloud radiative forcing reverses sign from negative in the warm season to positive in the cold season, when reflective snow reduces the negative SWCF below the positive LWCF. This in turn leads to a large climate discontinuity with snow cover, with a systematic cooling of 10°C or more with snow cover. In addition, snow cover transforms the coupling between cloud cover and the diurnal range of temperature. In the warm season, maximum temperature increases with decreasing cloud, while minimum temperature barely changes; while in the cold season with snow cover, maximum temperature decreases with decreasing cloud and minimum temperature decreases even more. In the warm season, the diurnal ranges of temperature, relative humidity, equivalent potential temperature and the pressure height of the lifting condensation level are all tightly coupled to opaque cloud cover. Given over 600 station-years of hourly data, we are able to extract, perhaps for the first time, the coupling between cloud forcing and the warm season imbalance of the diurnal cycle; which changes monotonically from a warming and drying under clear skies to a cooling and moistening under cloudy skies with precipitation. Because we have the daily cloud radiative forci, which is large, we are able to show that the memory of water storage anomalies, from precipitation and the snowpack, goes back many months. The spring climatology shows the memory of snowfall back through the entire winter, and the memory in summer goes back to the months of snowmelt. Lagged precipitation anomalies modify the thermodynamic coupling of the diurnal cycle to the cloud forcing, and shift the diurnal cycle of mixing ratio which has a double peak. The seasonal extraction of the surface total water storage is a large damping of the interannual variability of precipitation anomalies in the growing season. The large land-use change from summer fallow to intensive cropping, which peaked in the early 1990s, has led to a coupled climate response that has cooled and moistened the growing season, lowering cloud-base, increasing equivalent potential temperature, and increasing precipitation. We show a simplified energy balance of the Prairies during the growing season and its dependence on reflective cloud.

Overcoming the issue of land value and cost in urban areas will not provide a miraculous solution to the problems there. Appropriate land use cost, especially for residential and commercial land, is just one of the issues to be settled in the debate. Therefore, this study aims to build a new urban land price determination model by investigating the urban syntactical analysis, street width, and their economic effects on land value. The study attempts to determine the impact of syntactic analysis of streets and street width on land prices; it also seeks to identify the factor most affected by the land cost. Ultimately, the study built a model for urban land price prediction. The case selected is evaluated and compared in three aspects of the analysis, including; the urban axial assessments and urban street width, to find out their impacts on the real estate’s land price in the context of the land use distributions, which are predominantly residential and commercial types of uses. Depth map X8, SPSS, and QGIS 3.16 were used for the study evaluations and assessments. The result showed a significant impact of the urban street network on the price of land; this result can be used to enhance future urban design regarding urban economy improvements.

The central coast is one of the importantly livable regions in China, and green land plays a meaningful role in improving human settlements through regulating ecosystem services. However, the research on spatiotemporal heterogeneity of green land in different urbanized areas are still lacking in this region, which limits the timeliness of reporting on the land-surface thermal properties of residential environment from green land perspective. To address this issue, the synergistic methodology of “artificial numerical technology -- urban interior mixed pixel classification -- surface radiation energy balance model” was applied to investigate the green land change and its impact on human settlements in Rizhao region, which is known for its coastal ecology and greenery in China and obtained the United Nations habitat award. Main conclusions of this study are below: (1) Although total green land decreased by 474.05 km2, resulting in a decrease of 9.17% in its share of the entire study area from 2000-2022 during the urbanization process, but the greening levels improved within the built-up area, with the greening proportion of 25.34% in 2000 and 42.98 km2 in 2022. (2) Differences in green land at different urbanized regions were first observed, namely, urban greening rate was 37.78% in the old urban areas of 2022, while it was up to 46.43% in new urban areas. More attention was paid to the construction of urban green space during urban expansion, which will inevitably bring better visual and comfort experience to residents. (3) Thermal comfort indicators for urban residents were evaluated in latent heat flux (0-457.83 W/m2), sensible heat flux (0-645.09 W/m2), total available energy (254.07-659.42 W/m2) and others. (4) The lowered cooling temperature effect in the middle, high green land density region was 1.05 ℃ and 2.12 ℃ compared to the low-density region, and the average air temperature was 25.86 ℃. Also, spatial patterns of hot and cold uncomfortable areas were displayed in this study. Overall, this study provides the meaningfully practical reference for exploring the spatiotemporal heterogeneity of green land and its impact on residents' environments from the perspective of land-surface thermal properties in coastal areas of China and around the world.

The water quality of the river is becoming deteriorated due to human interference. It is essential to understand the relationship between human activities and land-use types to assess the water quality of a region. GIS has the latest tool for analyzing the spatial correlation. Land use land cover and change detection is the best illustration to show the human interactions on land features. The study assessed water quality index of upper Ganga River near Haridwar, Uttarakhand and spatially correlated them with changing land use to reach a logical conclusion. At the upper course of Ganga along 78 Km long from Kaudiyala to Bhogpur, water samples were collected from five stations. For water quality index the physicochemical parameters like pH, EC, DO, TDS, CaCO3-, CaCO3, Cl¯, Ca++, Mg++, Na+, K+, F-, Fe2+ were considered. The result of the spatial analysis was evaluated through error estimation and spatial correlation. The root mean square error between spatial land use and water quality index of selected sampling sites was estimated as 0.1443. The spatial correlation between land-use change and site-wise differences in water quality index has also shown a high positive correlation with R² = 0.8455. The degree of positive correlation and root mean square error has strongly indicated that the water quality of the river at the upper course of Ganga is highly impacted through human activities.

In response to the problem of increasing climate change and energy security, investment in renewable energy sources has increased significantly both in Europe and globally. Wind and solar power plants are expected to be the largest contributors to global decarbonization, ranking first and second in projected capacity by 2050. Since all power plants have some impact on the environment, this also applies to photovoltaic power plants. Because of the large capacities projected for PV installed capacity, their environmental impacts should be evaluated. The environmental impacts of PV power plants change over time. Improving the manufacturing technology of PV system components, increasing the efficiency of solar cells, and using materials that are less harmful to the environment will reduce these impacts. Manufacturing PV system components is a highly energy-intensive process that involves greenhouse gas emissions. As new renewable energy capacity is built, the amount of "green" electricity on the grid increases, reducing CO2 emissions per kWh consumed. The objective of this paper is to analyze the current status of the environmental impact of PV power plants under these changing conditions in terms of CO2 emissions, land use, pollutant and noise emissions, and water consumption. The capacity installed to date will reach the end of its lifetime by 2050, which means that the amount of waste associated with it will increase over time. This can have a significant impact on the environment, which is why part of the work is dedicated to this problem. In addition to the available information from the literature, in the part related to land use, the authors also made their own estimates based on data on newly installed PV power plants and PV modules available on the market. The results of the analysis show that there is enough land both in Europe and worldwide to install the planned capacities of rooftop and ground-mounted PV power plants. CO2 emissions are at the same level as for concentrated solar power, with a decreasing trend. Pollutant emissions, noise and water consumption are not a major problem compared to other types of power plants. Overall, it can be concluded that the expansion of PV capacity has a very positive impact on the environment.

The major industrial cities of Bangladesh are heavily experiencing air pollution-related problems due to the increased trend of Particulate Matter (PM2.5) and other pollutants. This paper aimed to investigate and understand the relationship between PM2.5 and land use and climatic variables and to identify the riskiest area and population groups using a Geographic information system and regression analysis. The results show that about 41% of PM2.5 concentration increased within 19 years (2002-2021) in the study area, while the highest concentration of PM2.5 was found from 2012 to 2021. The concentrations of PM2.5 were higher over barren lands, forests, croplands, and urban areas. About 64%, 62.7%, 57%, and 55% concentrations were increased annually over barren lands, forests, cropland, and urban regions, respectively, from 2002-2021. The highest concentration level of PM2.5 (84 mg m-3) among other land use classes was found in urban areas in 2021. The regression analysis shows that air pressure (r2= - 0.26), evaporation (r2= - 0.01), humidity (r2= - 0.22), rainfall (r2= - 0.20), and water vapor (r2= - 0.03) were negatively correlated with PM2.5. On the other hand, air temperature (r2= 0.24), ground heat (r2= 0.60), and wind speed (r2= 0.34) were positively correlated with PM2.5. More than 60 Upazilas were the most polluted areas, with 1,948,029 populations (ages 0-5), 485,407 (ages 50-69), and a total population of 11,260,162 were in the high-risk/hotspot zone. The government line department may use the main results paper's key results, policymakers, stainable development practitioners, academicians, and others for integrated air pollution mitigation and management in Bangladesh and other geographical settings worldwide.

According to this study, approximately half of Africa's forests are utilized primarily or partially for the production of wood and non-wood commodities. Aims to evaluate Africa's forestry and forest products, namely Wood Forest Products (WFPs) and Non-wood Forest Products (NWFPs) in the sixteen (16) West African countries. While adhering to the following guidelines: wood extraction and preparation, analyzing wood primarily used as an energy source in Africa, identifying non-wood forest products in Africa, the state of export, trade, and customs procedures in West Africa, and examining the role of forests and forest stakeholders in Africa's low-carbon economy transition. An exploratory literature review of selected wood forest products and non-wood forest products (plants and animals) in West Africa identifying the country, the natural land area with the natural habitat issues of the forest, the species most harvested and traded in the West African sub-region. The study reemphasized some government legislation, policies, and market trade failures and limitations while also stating that trees may help in the low-carbon revolution through interventions aimed at maintaining, improving, and restoring natural capital have demonstrated that high environmental requirements of sustainable forest management (SFM) may be met in both natural and planted forests. The study identified a systematic assessment of the most common forest products (wood and non-wood forest products) considering the available data on the national forest reserves of the selected countries in West Africa. The study also revealed the need for biodiversity conservation of the available forest reserves to help mitigate the impact of global warming targeting the United Nation’s Sustainable Development Goal 13- Climate Action. Which is focused on integrating climate change mitigation, adaptation, impact reduction, and early warning signs into the national policies, improving forest planning and management education, awareness-raising, and institutional capacity within the sub-region.

Remote sensing/GIS techniques are a versatile tool for x-raying serial forest structural changes in retrospect. It would be impossible to evaluate past occurrences and changes in forest extents in past decades at Effan Forest Reserve without non-conventional means. Therefore, we adopted remote sensing technology using Landsat images to evaluate land-use change and degradation rates in the area with a view to ascertaining causal factors for possible minimization of forest degradation in Effan Forest Reserve. Land-use/land-cover changes were analyzed using USGS-Landsat TM and ETM images of 1987, 2002, 2014 and 2019. Field-data were collected using handheld GPS receiver and spatial statistical analyses were conducted using the ground control points (GCPs). For inventory data, a systematic sampling technique was adopted using ten 1.05 km-transects at 500 m intervals. A total of 50 sample plots of 50 × 50 m were used. All tree species with Dbh ≥10 cm were enumerated. Nineteen tree species in ten families were encountered with Vitellaria paradoxa as the most-frequently occurring species in the area. IUCN-listed endangered Pterocarpus erinaceus, hitherto abundant in the area, was rarely encountered during the survey, while Vitellaria paradoxa is gradually shrinking, going the relative abundance in the area. The result further showed that primary and secondary forests decreased considerably by 258.03 ha (46.72%) and 9.18 ha (3.63%), respectively, with a total forest loss of 50.3% in 32 years (8.4 hayr-1, 1.6% per annum). While forest plantation size doubled by 369.72 ha within the period. This is worrisome as the remaining fragmented forests appeared to be on the decline, except the riparian vegetation, due to inaccessibility to the riparian by loggers. It thus appeared that forest protection approaches were ineffective. Increased protection efforts could save this forest reserve, and the concerned authority should consider a focused-enrichment planting involving indigenous species for ecosystem-repair.

Based on the recorded watershed characteristics, the future conditions on the basin system can be predicted using a different method. In this study, dynamic land-use change and its impacts on the streamflow for the Dabus watershed were predicted using ANN-CA based method. The model performance for accurate prediction of the future land-use change on the Dabus River watershed has been checked by validation of the simulated value with the actual value, hence the overall kappa value (k) = 0.83 for the simulated 2016-LULC validated with actual 2016-LULC. Then, 2026-LULC was predicted based on the 2004 and 2009-LULC. The streamflow for the case of 2004 and 2009-LULC has been simulated using the SWAT model. The value of NSE = 0.87 and 0.90 was attained during validation of simulated streamflow for 2004 and 2009-LULC data cases, respectively. The agreement of simulated value of streamflow with the observed data is indicated as R2 = 0.91 and 0.96 for 2004-LULC and 2009-LULC. The effects of the dynamic land-use change on streamflow for the predicted land use(2026-LULC) catchment were evaluated by T-test analysis. Hence, T-stat =0.04 and -0.002 in the case of simulated streamflow used 2004-LULC and 2009-LULC, respectively compared with simulated value using 2026-LULC.

The stormwater drainage problem is one of the major challenges facing in Shire Endaslasse town, Ethiopia. In a town, Street flooding and overtopping drainage system problems are occurring during the rainy season. This causes ponding which poses difficulties in ease of transportation and it hinders the day-to-day activity of the people. So, the study focuses on the performance of the stormwater drainage system in Shire Endaslasse town using Arc GIS and SWMM5.1. For this study, the primary data were collected by field surveys and interviews with the council body. Simulation results for storm events show that in some of the drainage systems in different regions of Shire Endaslasse town have flooded. During the field observation, the drainage structures are filled with solid wastes, inadequate inlet and outlet structures and some of the top element of the manhole have been broken this may cause a problem of aesthetic and healthy at large it may increase flood risk. The flooding risk in the drainage systems is very high due to the drainage system is undersized to cope with the current rainfall rates, but also is very limited to face the upcoming predicted rainfall.

In-cloud ice mass accretion on wind turbines is a common challenge faced by energy companies operating in cold climates. On-shore wind farms in Scandinavia are often located in regions near patches of forest, the heterogeneity length scales of which are often less than the resolution of many numerical weather prediction (NWP) models. The representation of these forests--including the cloud water response to surface roughness and albedo effects related to them--must therefore be parameterized in NWP models used as meteorological input in ice prediction systems, resulting in an uncertainty that is poorly understood and to present date not quantified. The sensitivity of ice accretion forecasts to the subgrid representation of forests is examined in this study. A single column version of the HARMONIE-AROME 3D NWP model is used to determine the sensitivity of the forecast of ice accretion on wind turbines to the subgrid forest fraction. Single column simulations of a variety of icing cases at a location in northern Sweden were examined in order to investigate the impact of vegetation cover on ice accretion in varying levels of solar insulation and wind magnitudes. In mid-winter cases, the wind speed response to surface roughness was the primary driver of the vegetation effect on ice accretion. In early season cases, the cloud water response to surface albedo effects plays a secondary role in the impact of in-cloud ice accretion, with the wind response to surface roughness remaining the primary driver for the surface vegetation impact on icing. Two different surface boundary layer (SBL) forest canopy subgrid parameterizations were tested in this study that feature different methods for calculating near-surface profiles of wind, temperature, and moisture, with the ice mass accretion again following the wind response to surface vegetation between both of these schemes.

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.

Land Surface Temperature (LST) and Land Use Land Cover (LULC) are the principal aspects of climate and environment studies. The object of the study is to assess spatial relationship between LST and remote sensing LULC indices at the global and continental scale. Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua daytime LST and eight LULC MODIS indices of 2018 prepared and processed using Earth Engine Code Editor. R squared and significance of the relationship values of randomly selected points computed in R program. The research observed the relationship between examined indices and LST is significant at the 0.001 level. Normalized Difference Water Index (NDWI) and Normalized Difference Snow Index (DSI) are the dominant drivers of LST in the world, Asia and North America. In Australia and Africa, Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) are the dominant drivers of LST. Albedo and Normalized Difference Soil Index (NDSI) have superior in Central America. In South America and Europe, the dominant driver of LST is NDWI. Relationship between albedo and LST is moderate inverse on a global scale. Observed relationship between LST and examined vegetation indices is positive in Europe and North America while inverse in Australia and Africa. All observed relationship between Normalized Difference Built-up Index (NDBI) and LST are positive. Association observed between NDSI and LST is positive in Australia, Africa and Central America.

Natural ecosystem of Islands and coastal region are vulnerable to climate change phenomena such as increasing temperature, fluctuating rainfalls, ocean acidification and tsunami. Andaman and Nicobar group of islands lies in Bay of Bangal facing such extreme climate phenomena. A spatial-temporal analysis of forest cover of middle Andaman region of the Andaman and Nicobar group of islands was done from 1990 to 2019 with an interval of 5-10 years. Support vector machine classifier, spectral indices such as Normalized Difference Vegetation Index, Normalized Difference Water Index, and Normalized Difference Built-up Index were used for the analysis of greenery, water resources, and urban land. Land surface temperature was estimated using split window algorithm for Landsat 8 and mono window algorithm for Landsat 5. The data showed relative contribution of forest region toward rising temperature in the island region. The research also showed that subsurface hydrology linked to interconnected lineaments provides a stable zone for forest cover. The open forest showed maximum fluctuation while minimum change was observed in Evergreen Forest. The spectral characteristics analysis using indices showed significant change except in 2005 due to Tsunami occurred in 2005. The land surface temperature showed fluctuation near to 30° C from 1990 to 2019.

Mediterranean coastal lagoons and their peripheral areas often provide a collection of habitats for many species, and they often face significant threats from anthropogenic activities. Diverse human activities in such areas directly affect the spatio-temporal dynamic of surface water and its ecological characteristics. Monitoring the surface water dynamic, and understanding the impact of human activities are of great significance for coastal lagoon conservation. The Regional Natural Park of Narbonne includes a typical Mediterranean lagoon complex where surface water dynamic and its potential link with local diverse human activities has not yet been studied. In this context, based on all the available Landsat images covering the study area during 2002-2016, this study identified the water and non-water classes for each satellite observation by comparing three widely used water indices (i.e., NDVI, NDWI and MNDWI) and using the Otsu method. The yearly water frequency index was then computed to present the spatio-temporal dynamic of surface water for each year, and three water dynamic scenarios were also identified for each year: permanent water (PW), non-permanent water (NPW) and non-water (NW). The spatial and inter-annual variation in the patterns of the three water scenarios were characterized by computing the landscape metrics at scenario-level quantifying area/edge, shape, aggregation and fragmentation. Finally, the quantitative link between different land use and land cover (LULC) types derived from the LULC maps of 2003, 2012 and 2015 and the surface water dynamic scenarios was established in each of the 300 m x 300 m grid cells covering the study area to determine the potential impact of human activities on the surface water dynamic. In terms of the inter-annual variation during 2002-2016, PW presented an overall stability, and NPW occupied only a small part of the water surface in each year and presented an inter-annual fluctuation. NPW had a smaller patch size, with lower connectivity degree and higher fragmentation degree. In terms of spatial variation during 2002-2016, NPW often occurred around PW, and its configurational features varied from place to place. Moreover, PW mostly corresponded to natural lagoon, and salt marsh (as a part of lagoons), and NPW had a strong link with arable land (agricultural irrigation) and salt marsh (salt production), sand beach/dune, coastal wetlands and lagoon for the LULC maps of 2003, 2012 and 2015. However, more in-depth analysis is required for understanding the impact of sand beach/dune, coastal wetlands and lagoon on surface water dynamics. This study covers the long-term variations of surface water patterns in a Mediterranean lagoon complex having intense and diverse human activities, and the potential link between LULC types and the water dynamic scenarios was investigated on different dates. The results of the study should be useful for environmental management and protection of coastal lagoons.

The consequences of growing urbanization can be perceived in multiple levels around the globe: overpopulated living conditions, water and air pollution, loss of open space, costly transportation infrastructure, food shortages, fires and floods. The Houston metropolitan area is an example of fast urban growth, with a population increase of more than sixteen percent in seven years, going from 5.8 million people in 2010 to 6.9 million in 2017 [1]. By 2045, the robust growth of the region is projected to lead to the addition of approximately five hundred square miles of developed area, including an estimated six million parking spaces, seven hundred eighty million square feet of non-residential uses, and three and a half billion square feet of residential use [2]. The accelerated development, in addition to physical features, geomorphic processes and human activities in the region are believed to have caused Houston to suffer through over fifty devastating floods since its settlement, despite some successful flood damage reduction projects. The present study focused on the potential outcomes of an increased use of green infrastructure in comparable urban areas, and its effects on flooding volume. Results from the research revealed that not only these measures would likely improve the performance of existing urban drainage systems and attenuate flood incidence in the area, but would also promote connectivity between areas otherwise detached or only accessible by car, improving walkability and incentivizing engagement in outdoor activities.

Rapid urbanization has dramatically spurred the economic development over the past three decades, especially in China, but has nevertheless had negative impacts on natural resources since it is an irreversible process. Thus, it is essential to timely monitor and quantitatively analysis the changes in land use over time and to identify the landscape pattern variation related to growth mode in different period. This study aims at inspecting spatiotemporal characteristics of landscape pattern respond to land use changes in Xuzhou city during the period from 1985 to 2015. In this connection, we proposed a new spectral index, named the Normalized Difference Enhanced Urban Index (NDEUI), which combines data from NTL (Nighttime light) from the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) with annual maximum Enhanced Vegetation Index (EVI) to reduce the detection confusion between urban areas and barren land, as well as follows. NDEUI-assisted Random Forests algorithm was implemented to obtain the land use/land cover (LULC) maps of Xuzhou in 1985, 1995, 2005 and 2015, respectively. Here, four different periods viz. 1985–1995, 1995–2005, 2005–2015 and 1985–2015 are chosen for the change analysis of land use and landscape pattern. The results indicated that the urban area has increased by about 30.65%, 10.54%, 68.77%, and 143.75% during the four periods mentioned above at the main expense of agricultural land, respectively. The spatial trend maps revealed that continuous transition from other land use types into urban land has appeared a dual-core development mode throughout the urbanization process, located at the new city region and the Jiawang district, mainly affected by the construction of new city region, freeway and the high railway station. Furthermore, we quantified the patch complexity, aggregation, connectivity and diversity of landscape employing a number of landscape metrics to represent the changes of landscape pattern at both class and landscape level, affected by urbanization during the study period. The results showed that with regard to the four aspects of landscape pattern, there were considerable differences among the four years, mainly owing to the increasing dominance of urbanized land. Spatiotemporal variation of landscape pattern was also conducted on the basis of subgrids in 900 m × 900 m. Combined with the land use changes and spatiotemporal variation of landscape pattern, it can be concluded that different urbanization modes and intensity result in variously the spatiotemporal evolution of landscape patterns. For Xuzhou city, the urban growth mainly appeared a leapfrog mode alone both sides of the roads during the period of 1985 to 1995, and then shifted into edge-expansion mode during the period from 1995 to 2005, whereas the edge-expansion and leapfrog modes coexisted for the period from 2005 to 2015. The high valuable spatiotemporal information generated utilizing RS and GIS in this study may give assistance to urban planners and policymakers to well understand urban dynamics and evaluate their spatiotemporal and environmental impacts at a local level for the sake of sustainable urban planning in the future.

Abstract: Changes in forest landscapes have been connected with human activity for centuries, which can be considered as one of the main driving forces of change in the global perspective. The spatial distribution of forests changes along with the geopolitical situation, demographic changes, intensification of agriculture, urbanization or changes in the land use policy. However, due to the limited availability of historical data, the driving forces of changes in forest landscapes are most often considered in relation to recent decades, without taking into account long-term analyzes. The aim of this paper is to determine the impact of natural and socio-economic factors on changes in forest landscapes within the protected area – Ślęża Landscape Park and its buffer zone in the aspect of long-term analyzes covering the period of 140 years (1883-2013). The comparison of historical and current maps, demographic data on 4 different periods as well as natural and location factors by using the ArcGIS software allowed analyzing selected driving forces of forest landscape transformations. We took into account natural factors like altitude, slope, exposure of the hillside and socio-economic drivers like population changes, distances to centers of municipalities, main roads and built-up areas.

The watershed hydrologic conditions in the Madre de Dios (MDD) basin in the Peruvian Amazon have been irreversibly impacted by deforestation and changes in land use cover. These changes have also had detrimental effects on the geomorphology, water quality, and aquatic habitat within the basin. However, there is a scarcity of hydrological modeling studies in this area primarily due to the limited availability of hydrometeorological data. The primary objective of this study was to examine how deforestation impacts the hydrological conditions in the MDD basin. By implementing the Soil and Water Assessment Tool (SWAT) model, this study determined that replacing 12% of the evergreen broadleaf forest area with bare land resulted in an significant increase in surface runoff by 38% monthly, a reduction of evapotranspiration by 1% annually, and an average monthly streamflow increase of 12%. Changes in spatial patterns reveal that the primary impacted watershed is the Inambari River subbasin, a significant tributary of the Madre de Dios River. This area experiences an annual average surge of 187% in surface runoff generation while witnessing an annual average reduction of 8% in evapotranspiration.These findings have important implications, as they can contribute to instances of flooding and extreme inundation events, which have already occurred in the MDD region.

In its Nationally Determined Contribution (NDC) to the United Nations Framework Convention on Climate Change, Brazil committed to reducing greenhouse gas emissions and restoring its forests. This study examines the challenges of fulfilling these commitments in Brazilian Amazonia. We carry out a detailed assessment of the current status of land tenure in the region and its relation to deforestation. After dealing with conflicts and overlaps between data from various sources, we produce a new map of public and private land tenure in Amazonia. Combining this map with Brazil's official data on deforestation, we find out how much natural vegetation has been preserved in each public or private area. The result is used to estimate how much deforestation is illegal. We also establish how much deforestation is associated with each land tenure type. Our results show that most deforestation inside rural properties is done by a few landowners, a finding that has important consequences for law enforcement. We then assess the challenges for reforestation in detail. To do so, we consider how much forest needs to be rehabilitated according to Brazil's Forest Code. Our analysis provides a comprehensive appraisal of the potential opportunity costs for forest restoration in the biome, considering farm size and land use. This analysis provides insights into targeted land use policies that can meet Brazil’s forest restoration goals.

Land resources have been under tremendous anthropogenic pressure with the consequence of their degradation. It is therefore necessary that the land resources must be managed effectively for sustainable development. Different from the developed countries, carbon inventories and data bank to monitor carbon sequestration potential of different ecosystems are unavailable in India. Micro-level studies are essential for sustainable land use management for a land scarce nation like India. To achieve the desirable goal of the present study, a total of 33 tree-based land uses were identified from forested and agricultural landscapes. Of these total land uses, five were in forest landscapes and rest in agricultural landscapes categorized into forest tree plantations (8 land uses), agroforestry (nine land uses), commercial crop plantations (six land uses) and fruit orchards (five land uses). A stratified random nested quadrate sampling method was adopted for vegetation analysis of the different land uses. The SOC, biomass and carbon accumulation in the tree-based land uses were significantly different from each other. Mixed forest soil had the highest amount of SOC, primary nutrients, standing biomass carbon, and ecosystem carbon. Positive correlations were observed between SOC, total standing biomass, litter production, and ecosystem carbon. The sequence of best tree based land uses in terms of total SOC (up to 60 cm depth), total plant biomass, total plant biomass carbon and ecosystem carbon was mixed species forest (126.67, 781.21, 390.61 and 517.27) > sole tree species stands in forest landscape (109.71, 192.56, 96.28 and 205.98) > tea plantations (103.19, 77.07, 38.54 and 141.74) > homegardens (90.34, 97.38, 48.69 and 139.02) > mixed plantation of Anthocephalus cadamba + Swietenia macrophylla (60.07, 111.86, 55.93 and 116.02) > Swietenia macrophylla based agroforestry (62.49, 83.82, 41.91 and 104.40) > mixed plantation of Tectona grandis + Milvus migrans (60.0, 85.97, 42.99 and 102.90). Similarly, the order of the major land uses was forest > commercial crop plantation > forest tree plantations > agroforestry > fruit orchards. The overall average ecosystem carbon accumulation in forests was 3.24 times more than the land uses in agricultural landscapes. The ecosystem carbon accumulation in the tree-based land uses in both forest and agricultural landscape was highly variable and was significantly different from each other. Land use conversion from forest to agriculture can reduce more than half of the carbon stock, but converting into homegardens, tree plantations or agroforestry enhanced carbon storage of the land use systems. The present findings can be used as baseline information for developing prediction models for probable effects of different land use, future intervention and sustainable management of land use systems.

Solar energy (SE) is essential for decarbonization of our economy and for energetic transition. Solar energy can be a sustainable economic activity as long as a balance is struck between the benefits it brings to climate change mitigation and the damage it can cause to biodiversity and ecosystems. Here we study this balance in an area with high biodiversity under pressure for installation of numerous photovoltaic plants (PPs). Our results show that developers give priority to the cheapest land close to connection points, while other values (e.g., environmental, landscape) are secondary. The regulatory process carried out by the Administration does not ensure the preservation of natural values, as several PPs with a high impact on important conservation areas have been approved. Experts' allegations provide quality information to the Administration to evaluate and demand changes to the projects presented. Such demands show that companies are willing to relocate plants to land occupied by olive groves. In this way, greater efficiency is achieved in land occupation, as well as shorter evacuation lines, water savings and less environmental impact. Prior strategic territorial planning could have avoided the impact of PPs already built, made the deployment of new PPs compatible with biodiversity conservation, and contributed to improving the management of key resources, such as subway aquifers. The proposed regulatory changes to the environmental assessment procedure (exclusion of renewables and public participation from the procedure) are detrimental, as they will make SE unable to meet the requirements of the Taxonomy Regulation.

In Ethiopia, bamboo thickets and woodlands play an important role in soil-water conservation and climate change mitigation in arid and semi-arid regions. However, bamboo mass flower-ing, rapid demographic changes and expansion of agricultural investments to bamboo domi-nated areas have led to deforestation and land degradation. In this study, we determined the effects of deforestation and subsequent cultivation on soil physical and chemical properties along a chronosequence of closely located agricultural lands with different ages (1, 3, 5 and 7 years) since converted from natural lowland bamboo forest. Hence, soil samples (n = 90) have been taken from both natural bamboo forests and adjacent agricultural lands at two soil depths (0-20 cm and 20-40 cm). Our result showed that CEC, K+, Ca+, Mg+ and available P were varied significantly with respect to cultivation periods and soil depth, while soil pH and Na+ varied with soil depth (P < 0.001). Soil C and total N contents (g/kg) in 0-20 cm soil layer declined significantly and exponentially with increasing years under cultivation. Conversion of natural bamboo forest to cropland during the past seven-year period significantly increased soil pH with soil depths, while CEC was declined throughout the cultivation period and soil depth. In general, the result revealed that conversion of natural lowland bamboo and subsequent cultivation of soil had negative effects on measured soil physicochemical properties.

The reconstruction of land use practices in hyper arid Saharan Africa is often hampered by the accuracy of the available tools and by unconscious biases that see these areas as marginal and inhospitable. Considered for a long time the living space of pastoral mobile communities, new research is showing of agriculture might have been more important in these areas than previously thought. In this paper, after a review of present-day land use strategies in Saharan Africa, we show how ethnographic and ethnoarchaeological data can offer us a different point of view and help in better defining land use and food production strategies in this area. Ultimately, these insights can be integrated into the ongoing effort of reconstructing past land use globally.

Abstract: The air pollution dispersion modelling via spatial analyses (Land Use Regression – LUR) is an alternative approach to the air quality assessment to the standard air pollution dispersion modelling techniques. Its advantages are mainly much simpler mathematical apparatus, quicker and simpler calculations and a possibility to incorporate other factors affecting pollutant’s concentration. The goal of the study was to model the PM10 particles dispersion modelling via spatial analyses v in Czech-Polish border area of Upper Silesian industrial agglomeration and compare results with results of the standard Gaussian dispersion model SYMOS’97. Results show that standard Gaussian model with the same data as the LUR model gives better results (determination coefficient 71% for Gaussian model to 48% for LUR model). When factors of the land cover and were included into the LUR model, the LUR model results were significantly improved (65% determination coefficient) to the level comparable with Gaussian model. The hybrid approach combining the Gaussian model with the LUR gives superior quality of results (65% determination coefficient).

With the accelerating urbanization process, the population increasingly concentrates in urban areas. In view of the special situation in China and a series of problems in the process of rapid urbanization, there were no reasonable measures for optimizing the population pattern. This study explored the distribution pattern of the Chinese population and proposed an optimization plan for the population distribution using GIS analysis. The main findings were as follows. (1) From 2010 to 2015, the distribution of population density in China presented a pattern of high in the southeast and low in the northwest based on the county-level administrative regions. The population still showed a tendency to migrate to the southeast of the country based on the “Hu Huanyong Line”. (2) There was a great difference in the land use efficiency in terms of population and economic production in China. The economic concentration in China was higher than the population concentration. In the areas where population and economic production were aggregated, GDP per capita and land use efficiency were higher. (3) Based on the land use efficiency in terms of population and economic production, the optimized urbanization plan of “1+4+11” for China’s urbanization was put forward, namely, one national-level aggregated area of population and economic production, 4 regional-level aggregated areas of population and economic production, and 11 local regionally aggregated areas of population and economic production. This optimization plan for urbanization represents an attempt to explore the direction of China’s urbanization, and it can be used to optimize the spatial development pattern and provide scientific guidance for the new urbanization plan.

Bamboo agroforestry is currently being promoted as a viable land use option to reduce dependence on natural forest for wood fuels in Ghana. To align the design and introduction of bamboo agroforestry in conformity with farmers’ needs, perceptions, skills and local cultural practices, information on its acceptability and adoption potential among farmers is necessary. It is therefore the objective of this study to (1) describe bamboo ethnobotany and (2) assess socioeconomic factors that affect the acceptability and adoption of bamboo and its integration into farming practices. Accordingly, information has been collected from 200 farmers in the dry semi-deciduous forest zone of Ghana. The study identified the socioeconomic risks and uncertainties as well as biophysical factors that are likely to influence the potential adoption of bamboo agroforestry in the study region. Gender, age, farmers’ known uses of bamboo, the practice of leaving trees on farmlands, farmers’ networking and access to extension services, land availability and ownership by farmers were identified as suitable predictor variables for the adoption of bamboo agroforestry. It is envisaged that bamboo agroforestry is a good bet in the DSFZ though there is the need to explore domestic energy (fuelwood) provision and substitution potential in order to have a broader picture of the technology.

Nicaragua is preparing the construction of an interoceanic canal that will be the longest and largest canal on earth. An environmental and social impact assessment has been published in 2014 supporting a general viability of the canal. Nonetheless, several scientist and societal actors raised serious concerns regarding the social, economic and ecological sustainability. Despite an open dispute within the Nicaraguan society, no independent, transparent and scientifically sound assessment has been carried out. Only the environmental and social impact assessment, charged by the canal constructor, has so far been realized. The aim of this study is to contribute to an open scientific debate through an objective and independent quantification of land use and hydrological impacts. This article presents a transparently documented and comprehensible impact assessment investigation of the West Canal Segment of the Nicaragua Canal. Based on publically available data and scientifically sound and recognized methods land use, hydrological (water availability) and socio-economic impacts (streets, population) are described, quantified and compared with official declarations in the impact assessment. While some results support official declarations other do not. The number of affected population and the water use of the Brito Lock resulted much higher in this study, for instance. Hence, society and water availability could be affected much higher than estimated in the impact assessment.

We evaluated the potential of using fish species and functional traits as indicators of land use impacts to fish assemblages. We used environmental data collected at multiple spatial scales (local, reach, and upstream catchment) for 19 tributary and main stem sites in the Nolichucky River watershed in Tennessee. Canonical correspondence analyses showed that temperature, elevation, specific conductivity, sediment yield, impervious surfaces, and row crop cover at the catchment scale were strongly associated with fish assemblage structure, as well as forest cover from all three spatial scales. Blocked indicator species analysis, with stream size as the block, showed that significantly strong indicators of the least-impacted riparian land use condition (≥60% forest cover) were Saffron Shiner (Notropis rubricroceus), Rainbow Trout (Oncorhyncus mykiss), Longnose Dace (Rhynichthys cataractae), Creek Chub (Semotilus atromaculatus), and Mottled Sculpin (Cottus bairdi). Traits indicative of the least-impacted sites were the herbivorous trophic guild, mean female age-at-maturity, longevity, rock-gravel spawners, montane geology and pelagic swimmers. Specific conductivity was strongly related to multiple catchment-scale land use variables, and was a strong local-scale influence on fish assemblage structure. Our results show promise for using a relatively common but endemic southern Appalachian fish species, the Saffron Shiner, as an indicator for land-use related impacts to these streams.

The assessment and prediction of drought risk under future climate change and land use land cover (LULC) scenarios is critically important for drought prevention and mitigation, as it enables a clearer understanding of potential shifts in drought patterns. The primary aim of this study is to evaluate sub-seasonal and seasonal meteorological and hydrological drought hazards across the Yellow River Basin (YRB) under projected future climate conditions and LULC patterns. The BCC-CSM1-1 climate model projections from the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset are utilized to represent future climate for 2025-2060 under RCP 4.5 and 8.5 scenarios. The CA-Markov model is employed to predict future LULC distributions. Meteorological and hydrological drought risks across different YRB zones are evaluated through a copula-based risk assessment approach, based on the joint probability distribution of drought duration and severity. The results indicate that sub-seasonal meteorological and hydrological droughts will likely be the primary concern moving forward. Specifically, the upper YRB (zones A, B, C) exhibits greater vulnerability to sub-seasonal meteorological drought, while the Loess Plateau (zones C, E) shows higher susceptibility to sub-seasonal hydrological drought. Moreover, zone F in the downstream region may experience increased seasonal hydrological drought risk due to projected urban expansion in the middle and lower portions of the YRB.

The changing of land use and land cover (LULC) are both affected by climate and human activity and affect climate, biological diversity, and human well-being. Accurate and timely information about the LULC pattern and change is crucial for land management decision-making, ecosystem monitoring, and urban planning, especially in developing economies undergoing industrialization, urbanization, and globalization. Biodiversity degradation and urban expansion in eastern China are research hot-spots. However, the influence of LULC changes on the region remains largely unexplored. Here, an object-based and multi-temporal image analysis approach was developed to detect how LULC changes during 1985-2015 in the Tiaoxi watershed (Zhejiang province, eastern China) using Landsat TM and OLI data. The main objective of this study is to improve the accuracy of unsupervised change detection from object-based and multi-temporal images. To this end, a total of seven LULC maps are generated with multi-temporal images. A random stratified sample design was used for assessing change detection accuracy. The proposed method achieved an overall accuracy of 91.86%, 92.14%, 92.00%, and 93.86% for 2000, 2005, 2010, and 2015, respectively. Nevertheless, the proposed method, in conjunction with object-oriented and multi-temporal satellite images, offers a robust and flexible approach to LULC changes mapping that helps with emergency response and government management. Urbanization and agriculture efficiency are the main reasons for LULC changes in the region. We anticipate that this freely available data will improve the modeling for surface forcing, provide evidence of changes in LULC, and inform water-management decision-making.

Agriculture and farming worldwide are responsible for numerous environmental threats, including degradation of land and water resources depletion. Underlining the dynamic interaction between bio-physical and socio-economic drivers is the key towards a more sustainable land and water management. With regard to a highly developed agricultural area in southern Italy, multi-regression models were developed to interpret the observed inter-annual variability of cropped land. Main drivers related to Common Agricultural Policy support, product market prices, crop yield and irrigation water availability were investigated. The adopted models revealed the different weighs of each driver. The findings reported the role that direct payments played in supporting the extension of irrigated crops, such as processing tomato. Likewise, the models pointed to decoupled payment scheme as the most important driver of change in the crop pattern over the last years.

Our work is regarding the analysis of land use changes, in the light of “saving soil” against the expansion due to unearned plus value of land: The loss of natural and agricultural surface in front of the expanding urban environment is a critical aspect of unsustainability of urban development, especially in the way it was carried out in the past decades. The measure of the physical transition of land use and characters from a more natural condition of land surface to a new artificial one, joint with a parallel analysis of the increase of land value due to such change is nowadays a major land-policy tool. The interplay of urban economics regulation with planning, reveals new key issues in urban governance and environmental preservation. In this paper it will be shown some experiment about the impact assessment of soil take, related with the seek of valorization of property inside the planning process. Our paper reports as well about the experimental activity carried out inside the MITO Lab of the Polytechnic of Bari, where reports about property values and environmental values have been produced, specially looking at the reality of the Apulia, a southern Italian Region, that is rich of farmlands and coastlines, often invaded by constructions with a severe loss of nature, landscape and ecosystems services.

Supervised land-use/land-cover (LULC) classifications are typically conducted using class assignment rules derived from a set of multiclass training samples. Consequently, classification accuracy varies with the training data set and is thus associated with uncertainty. In this study, we propose a bootstrap resampling and reclassification approach that can be applied for assessing not only the uncertainty in classification results of the bootstrap-training data sets, but also the classification uncertainty of individual pixels in the study area. Two measures of pixel-specific classification uncertainty, namely the maximum class probability and Shannon entropy, were derived from the class probability vector of individual pixels and used for the identification of unclassified pixels. Unclassified pixels that are identified using the traditional chi-square threshold technique represent outliers of individual LULC classes, but they are not necessarily associated with higher classification uncertainty. By contrast, unclassified pixels identified using the equal-likelihood technique are associated with higher classification uncertainty and they mostly occur on or near the borders of different land-cover.

A multi-decadal change analysis of the irrigation ponds in Taoyuan, Taiwan was conducted by using multi-source data including digitized ancient maps, declassified single-band CORONA satellite images, and multispectral SPOT images. Supervised LULC classifications were conducted using four textural features derived from the single-band CORONA images and spectral features derived from SPOT images. Post-classification analysis revealed that the number of irrigation ponds in the study area decreased during the post-World War II farmland consolidation period (1945 – 1965) and the subsequent industrialization period (1970 – 2000). However, efforts on restoration of irrigation ponds in recent years have resulted in gradual increases in the number (9%) and total area (12%) of irrigation ponds in the study area.

Climate and land use changes are major factors affecting runoff in regional basins. Understanding variation by considering interactions among hydrological components is an important process for water resource management. This study aimed to assess the variation of future runoff in the Upper Chi Basin, Northeastern Thailand. QSWAT hydrological model was integrated to 3 CMIP6 GCMs including ACCESS-CM2, MIROC6, and MPI-ESM1-2-LR under SSP245 and SSP585 scenarios during 2023 – 2100. Land Change Modeler (LCM) was also used for future land use simulation. The results revealed that future average of long-term precipitation and temperature tended to increase while forest land tended to decrease and be replaced by sugarcane plantations. The accuracy assessment of baseline year runoff calculation by QSWAT during 1997 – 2022 showed acceptable result as can be seen from R2, NSE, RSR, and PBIAS indices. This result could lead to temporal and spatial simulation of future runoff. Likewise, runoff of 2 SSPs scenarios tended to increase consecutively, especially in SSP585 scenario. In addition, in case of long-term spatial changes in the subbasins scale, over 90% of the area, from upstream to outlet point, tended to get higher due to 2 major factors including future increased precipitation and changes in cultivation, which would be influential to groundwater and interflow components respectively. Methodology and result of this study can be useful to stakeholders in understanding changes in hydrological system so that they can apply it to develop a strategy for water resource management and handling factors affecting different dimensions properly and sustainably.

Water scarcity is a key challenge to global development. In Brazil, the Sao Francisco River Basin (SFB) has experienced water scarcity problems because of decreasing streamflow and increasing demands from multiple sectors. However, the drivers of decreased streamflow, particularly the potential role of surface-groundwater interaction, have not been yet investigated. Here, we assess long-term trends in baseflow, quickflow, and streamflow of the SFB during 1980–2015 and constrain the most likely drivers of observed decreases through trend analysis of precipitation (P), evapotranspiration (ET), and terrestrial water storage change (TWS). We found that over 82% of the observed decrease in streamflow can be attributed to a significant decreasing baseflow trend (< -20 m3 s-1 y-1) along the SFR with spatial agreement between decreased baseflow, increased ET, and irrigated agricultural land. We also noted a decrease in TWS across the SFB with trends exceeding -20 mm y-1. Overall, our findings indicate that decreasing groundwater contributions (i.e., baseflow) is providing the observed reduction in total SFR flow. A lack of significant P trends indicates that only P variability likely has not caused the observed baseflow reduction, mainly in the Middle and Sub-middle SFB. Therefore, groundwater and surface withdrawals may be likely a driver of water scarcity over the SFB.

Background: There are major air pollution monitoring gaps in sub-Saharan Africa. Developing capacity in the region to conduct air monitoring in the region can help estimate exposure to air pollution for epidemiology research. The purpose of our study is to develop a land use regression (LUR) model using low-cost air quality sensors developed by a research group in Uganda (AirQo). Methods: Using these low-cost sensors, we collected continuous measurements of fine particulate matter (PM2.5) between May 1, 2019 and February 29, 2020 at 22 monitoring sites across urban municipalities of Uganda. We compared average monthly PM2.5 concentrations from the AirQo sensors with measurements from a BAM-1020 reference monitor operated at the US Embassy in Kampala. Monthly PM2.5 concentrations were used for LUR modeling. We used eight Machine Learning (ML) algorithms and ensemble modeling; using 10-fold cross validation and root mean squared error (RMSE) to evaluate model performance. Results: Monthly PM2.5 concentration was 60.2 µg/m³ (IQR: 45.4-73.0 µg/m³; median= 57.5 µg/m³). For the ML LUR models, RMSE values ranged between 5.43 µg/m³ - 15.43 µg/m³ and explained between 28% and 92% of monthly PM2.5 variability. Generalized additive models explained the largest amount of PM2.5 variability (R²=0.92) and produced the lowest RMSE (5.43 µg/m³) in the held-out test set. The most important predictors of monthly PM2.5 concentrations included monthly precipitation, major roadway density, population density, latitude, greenness, and percentage of households using solid fuels. Conclusion: To our knowledge, ours is the first study to model the spatial distribution of urban air pollution in sub-Saharan Africa using air monitors developed from the region itself. Non-parametric ML for LUR modeling performed with high accuracy for prediction of monthly PM2.5 levels. Our analysis suggests that locally produced low-cost air quality sensors can help build capacity to conduct air pollution epidemiology research in the region.

The relationship between city size, coastal land use and air temperature rise with distance from coast during summer day is analyzed using the meso-scale Weather Research & Forecasting (WRF) model in five coastal cities in Japan with different sizes and coastal land use (Tokyo, Osaka, Nagoya, Hiroshima and Sendai) and inland cities in Germany (Berlin, Essen and Karlsruhe). Air temperature increased as distance from the coast increased, reached its maximum, and then decreased slightly. In Nagoya and Sendai, the number of urban land use in coastal areas is less than the other three cities, where air temperature is a little lower. As a result, air temperature difference between coastal and inland urban area is small and the curve of air temperature rise is smaller than those in Tokyo and Osaka. In Sendai, air temperature in the inland urban area is the same as in the other cities, but air temperature in the coastal urban area is a little lower than the other cities, due to about one degree lower sea surface temperature influenced by the latitude. In three German cities, the urban boundary layer may not develop sufficiently because the fetch distance is not enough.

Abstract: A two-year study of pearl millet-groundnut cropping systems across two fertilizer levels was conducted at the INRAN/TARNA research station in Maradi, Niger in the Sahelian zone of West Africa. The objective of this study was to identify the best cropping system with and without fertilizer application to optimize pearl millet and groundnut yields, land use efficiency, and economics as measured by value-to-cost ratio. The experiment was conducted with three replications, and ten treatments combination of five pearl millet and groundnut cropping systems (pearl millet and groundnut sole crops, and three pearl millet – groundnut intercrops), and two fertilizer levels. Sole cropping produced the highest pearl millet grain by over 300 kg ha-1 and groundnut pod yields by over 500 kg ha-1, but all the intercropping systems had a LER above 1.0 with land use efficiency increased by 19 to 41%, also intercropping increased diversity, and reduced risk. Fertilizer application increased yields in all cropping systems by 200 to 600 kg ha-1. Government subsidy increased the value-to-cost ratio by 0.5 to 2, 5 units, and was required for economic response for pearl millet sole and intercrops in 2022. The groundnut sole cropping system had the greatest economic response to fertilizer application. Based on the risky environment and multiple end uses needed by producers, the intercrop system M-G: 1:3:1 with fertilizer application is usually the best option to optimize pearl millet and groundnut production.

One of the most problematic forms of nature protection in Poland relates to landscape parks. On the one hand, they include the most valuable landscapes; on the other hand, the areas within the landscape park still have economic uses. Therefore, the monitoring of landscape changes within landscape parks is necessary in order to properly manage these forms of protection. The main objective of the study was to monitor the scale and nature of landscape transformations within the boundaries of landscape parks in Poland during the period 2000–2018 and to assess the possibility of using the landscape change index (LCI) to monitor the intensity of landscape transformations within this type of protected area. Filling a gap in the research on landscape changes, I developed and verified the possibility of using LCI for monitoring the intensity of landscape changes using the example of 12 landscape parks in the Lower Silesia region. Preliminary analyses of the transformations within all landscape parks in Poland showed an upward trend, both in terms of the number of types of identified landscape changes as well as their area. In spite of the large diversity and degree of transformation in landscape parks, several dominant processes can be observed. The largest number and area of changes during each of the analyzed periods were found in transformations within forest landscapes (temporary and permanent deforestation and forest maturation), which constitute the dominant type of land cover within most of the landscape parks. In open landscapes, changes mainly relate to afforestation and natural succession in meadows, pastures and arable land, as well as the transformation of arable land into mining areas. Twelve case studies, covering all landscape parks of the Lower Silesia, have shown that the LCI is an excellent tool for monitoring the intensity of landscape changes, but it is dependent on the accuracy of the source data. The analyses confirmed that, during the study periods, the changes in all 12 Lower Silesian landscape parks were at a low level, but their particular intensification took place in the years 2012–2018. The highest LCI was found in the area where a natural disaster had occurred (air tornado), which destroyed huge areas of forest in landscape parks. After changes in the forest landscape, the most frequently identified type of change in 2006–2012 is the transformation of non-forest landscapes into forest landscapes. The main reason for such changes was the expansion of forest into abandoned arable land, meadows and pastures. The use of the Corine Land Cover database to calculate LCI and monitor the intensity of landscape change revealed a low usability of the database for the year 2000 and a high usability for data from 2006–2018.

Human disturbances can have severe environmental impacts on freshwater ecosystems. The main aim of this study was to detect the influences of physiochemical variables, land-cover characteristics, and river connectivity on fish assemblages in Lake Chaohu Basin, China. A cluster analysis of the river connectivity variables identified four groups of sites that characterized by significantly different connectivity gradients in local scale. These four groups of sites showed increasing connectivity from the upper reaches to the lower reaches. At the same time, among the four groups, the values of the environmental variables generally increased from the upper reaches with less human activity towards the lower reaches with more human activities. For instance, some main physiochemical variables (e.g., river width, water depth, nitrate, phosphate) significantly increased among the four groups. In contrast, fish taxa richness and diversity indices were not significantly different among the four connectivity groups. However, fish assemblages showed significant variation among the connectivity groups (p=0.026). In addition, the study determined that upper riparian land uses (e.g., woodland and grassland), flow velocity, and elevation were environmental variables regulating the variance in the fish communities, and for the connectivity variables, only river order and number of branches along a path to the left of the main stem affected the variance in the fish communities. Therefore, new practices aimed at maintaining and even increasing the riparian canopy coverage and the flow velocity of rivers should be integrated into local conservation planning for freshwater ecosystems, especially in the upper reaches of the basin.

Anthropogenic disturbances interacting with natural disturbances, ecological and socio-economic factors can provoke forest degradation and modulate ecosystem resilience. In Haiti, protected areas recently created to reduce forest loss, require studies about forest dynamics and land use to assure the development of sustainable management policies. We combine field interview with Landsat satellite images of the Macaya National Park collected between 1985 and 2021 to investigate: 1) how much of the original forest area has been converted into agricultural or logged area since 1985; and 2) how do elevation and slope influence the expansion of human-induced land-use changes. Our results indicate an increase of 11.36% in forest cover and a reduction of 75.34% in agriculture class cover, despite the passage of seven hurricanes in the region. Forest recovery was apparently unrelated to elevation and slope, and likely reflected the implementation of new environmental laws and policies with the creation of the Macaya National Park in 1983. Restoration and protection programs contributed to ensure access to financial resources, technical assistance and new technology, thus promoting a shift into a more resilient forest system. This study brings hope for forest conservation in Haiti by showing that positive results can be achieved through inclusive collaboration.

South rear-edge populations of widely distributed temperate and boreal tree species such as birches (Betula pubescens and B. pendula) are considered particularly vulnerable to climate warming, and at the same time they constitute genetic reservoirs of drought-adapted ecotypes. Here, we compared radial growth patterns and responses to climate, river or dam flows and a drought index of rear-edge (southernmost) populations (Toledo Mountains, central-southern Spain) with populations located in northern Spain of B. pubescens and B. pendula. Then, we per-formed a comparative analysis across Europe of B. pendula populations. The main climatic con-straint of birch growth was high summer water deficit, although the effect of local hydrological conditions was particularly important in rear-edge populations. We found declining growth trends in rear-edge stands since the early 21st century, related to decreasing water availability and increasing aridity. Our results also suggested distinct growth patterns and climate-growth associations of B. pendula across Europe that show how populations further south and in warmer locations were more sensitive to the drought. In conclusion, drought-induced growth decline can be exacerbated by local human land uses leading to reduced river inflow, thus endangering birch populations at their southern distribution limit. Protection of endangered rear-edge birch populations requires adequate management of local water resources.

Deforestation is an important environmental problem in México and a key promoter of regional climate change through modifying the surface albedo. The objective of this research was to characterize the impact of deforestation and land use changes on surface albedo (α) and climate patterns in the Municipality of Tapalpa, Jalisco, México between the years 2014 and 2021. The main land cover types are coniferous forests (CF), oak and gallery woodlands (OGW), and annual agriculture (AA); which represent more than 88% of the regional territory (1066.03 km2). We used 2014 and 2021 Landsat 8 OLI images with topographic and atmospheric correction, in order to develop an inventory of albedo values for each land cover type in both time scenarios. Albedo images were generated by using the equation proposed by Liang in 2001, which is based on the reflectance of the bands 2, 3, 4, 5, and 7. Differences in albedo values were calculated between the years 2014 and 2021, and those differences were correlated with variations in climate parameters, for which we used climate data derived from the WRF model. In addition, the different land use changes found were classified in terms of triggers for increasing or decreasing surface albedo. Results showed that between 2014 and 2021, at least 38 events of land use change or deforestation occurred, with albedo increments between 1 and 11%, which triggered an average increment of 0.57% of the regional surface albedo in comparison to 2014 scenario. From 2014 to 2021, the albedo for CF, OGW, and AA, increased significantly (p&lt;0.001; Mann-Whitney U Test) by 79, 12, and 9%, respectively. In addition, the regional albedo increment was found to be significant and negatively correlated (p&lt;0.01 Spearman’s coefficient) with relative humidity (RH), maximum temperature (Tmax), minimum temperature (Tmin), and diurnal thermal range (DTR). The decrease in the regional values of relative humidity in 2021, occurred even when in that year the annual precipitation levels were higher than those of 2014, hence, reinforcing the fact of a possible climatic effect of the regional albedo changes. Conversion of CF and OGW into AA, perennial agriculture (PA), or grassland (GR) always yielded an albedo increment, whilst the conversion of AA to irrigation agriculture or PA triggered a decrease in albedo, and finally, the pass from GR or AA to protected agriculture caused albedo increase or decrease, depending on the greenhouse covers materials. Reducing deforestation of CF and OGW, conversion of AA or GR into PA, and selecting adequate greenhouse covers could help to mitigate regional climate change.

Conventional methods of crop mapping need ground truth information to train the classifier. Thanks to the frequent acquisition allowed by recent satellite missions (Sentinel 2), we can identify temporal patterns that depend on both phenology and crop management. Some of these patterns are specific to a given crop and thus can be used to map it. Thus, we can substitute ground truth information used in conventional methods with agronomic knowledge. This approach was applied to identify irrigated permanent grasslands (IPG) in the Crau area (Southern France) which play a crucial role in groundwater recharge. The grassland is managed by making three mows during the May-October period which leads to a specific temporal pattern of leaf area index (LAI). The mowing detection algorithm was designed using the temporal LAI signal derived from Sentinel 2 observations. The algorithm includes some filtering to remove noise in the signal that might lead to false mowing detection. A pixel is considered a grassland if the number of detected mows is greater than 1. A data set covering five years (2016-2020) was used. The detection mowing number was done at the pixel level and then results are aggregated at the plot level. A validation data set including 780 plots was used to assess the performances of the classification. We obtained a Kappa index ranging between 0.94-0.99 according to the year. These results were better than other supervised classification methods that include training data sets. The analysis of land-use changes shows that misclassified plots concern grasslands managed less intensively with strong intra-parcel heterogeneity due to irrigation defects or year-round grazing. Time series analysis, therefore, allows us to understand different management practices. Real land-use change in use can be observed, but long time series are needed to confirm the change and remove ambiguities with heterogeneous grasslands.

Current species’ range displacements are mostly triggered by climate change but European landscapes are largely dominated by human activities. In this study we identify the most promising spatial adaptive trajectories (SATs) for the thirty most threatened non volant mammal species in Europe up to 2080 (under three climate and land change scenarios) and where/when SATs of each species synchronically converge. We found large contrasts on the persistence of species in SATs, with some species largely reliant on the functionality of areas where many SATs converge. Overall, SATs and convergence centers are not adequately covered by existing conservation areas and coincide with crop and arable lands, compromising species persistence. It is important to invest in the protection of SATs and convergence centers through a mix of conventional instruments and new collaborative forms with the socio-economy. Anticipative plans at long-term coupled with risk analysis offer decision–makers templates to prevent negative surprises.

Pollinators are being threatened globally by urbanisation and agricultural intensification, driv-en by a growing human population. Understanding these impacts on landscapes and pollinators is critical to ensuring a robust pollination system. Remote sensing data on land use attributes have previously linked honeybee nutrition to land use in the Western Honeybee (Apis mellifera L.). Here, we instead focus on the less commonly studied Apis cerana japonica – the Japanese Honeybee. Our study presents preliminary data comparing forage (honey and pollen) with land use across a rural-urban gradient from 22 sites in Kyushu, southern Japan. Honey samples were collected from hives between June 2018 and August 2019. Pollen were collected and biotyped from hives in urban and rural locations (n = 4). Previous studies of honey show substantial vari-ation in monosaccharide content. Our analysis of A. cerana japonica honey found very little varia-tion in glucose and fructose (which accounted for 97% of monosaccharides), despite substantial differences in surrounding forage composition. As expected, we observed temporal variation in pollen foraged by A. cerana japonica, likely dependent on flowering phenology. These prelimi-nary results suggest that the forage and nutrition of A. cerana japonica may not be negatively af-fected by urban land use. This highlights the need for further comparative studies between A. cerana japonica and A. mellifera as it could suggest a resilience in pollinators foraging in their na-tive range.

Rapid peri-urbanization has resulted in increasing demand for and pressure on peri-urban lands at the expense of agricultural lands. Households’ decision to convert from agricultural land uses to residential and commercial land uses is driven by a myriad of factors, ranging from social to economic, in the Asante-Akim South district of the Asante region, Ghana. The paper examined the effects of agricultural land use trade-off on food production in the district. Using a triangulation of qualitative and quantitative methods, 115 household respondents were proportionately sampled from three selected communities in the district, for the collection of data through the administration of questionnaires. The data were subjected to the Pearson’s chi-square, embedded in the SPSS V.16, to test for association among the variables. We report that the increasing rate of agricultural land uses conversions was as a result of increasing demand for residential and commercial land usage at the expense of agricultural land uses. Converting prime agricultural lands into other land uses was seen as profitable to agricultural expansion. A re-examination of the district land use plans by the Ghanaian Physical (Town and Country) Planning Department in tandem with the Lands Commission is therefore recommended.

Land use and cover change (LUCC) is an important method to investigate the causes of global environment change. We utilized the emergy ecological footprint (EEF) model to construct a land-use change model to be used as a systematic measuring tool for monitoring sustainable development trends. In particular, we estimated the eco-security of the Cing-jing region as a case study so that responsible agencies can use it to maintain a balance between ecological preservation and tourism development. The results indicated the following: First, the ecological environment of the Cing-jing region satisfied the safety standard in 2008–2014; however, the related indices increased considerably. Second, the grey model predicted a decrease in 2015–2024 ecological carrying capacities of Cing-jing and a large increase in capita EFs, resulting in a larger ecological deficit and higher EFI. The eco-security from 2015–2024 was higher compared to 7 years ago and is predicted to reach the Grade 2 intermediate level in 2022; thus the Cing-jing region is gradually becoming ecologically unsustainable. Strengths of our study included the use of EEF theory in a quantitative analysis of slope lands for the effective evaluation of ecological security. Finally, we expanded our research to include ecological security issues.

The most extensive urban growths in the next 30 years are expected to occur in developing countries. Lagos, Nigeria - Africa’s second most populous megacity- is a prime example. To achieve more sustainable and resilient cities, there is a need for modeling the urban growth patterns of major cities and analyzing their implications. In this study, the urban growth of Lagos state was modeled using the Multi-Layer Perceptron (MLP) neural network for the transition modeling and the Markov Chain analysis for the change prediction, achieving a model accuracy of 81.8%. An innovative visual validation of the model results using the ArcGIS was combined with kappa correlation statistics. The results show that by 2031, built-up areas will be the most spatially extensive LULC class in the study area with percentage coverage of 34.1% as opposed to 9% in 1986. The coverage of bare areas is also expected to increase by 53% between 2016 and 2031. Conversely, 24.9% and 68.3% loss of forestlands and wetlands respectively, are expected between 2016 and 2031. In view of the 11^th goal of SDGs which focuses on achieving sustainable cities and communities, the objectives of African Union’s Agenda 2063, and based on the urban growth trends observed, the study recommends a prioritization of vertical expansion as opposed to the current horizontal urban growth trends in the study area.

The meaning of a good social outcome in land use transport policy/planning has been relatively underdeveloped, compared to economic and environmental sustainability goals, but this is now changing. Cities are increasingly prioritizing reducing social exclusion, with the allied intent of providing all residents with equitable access to the benefits of their city. However, in jurisdictions that use cost-benefit analysis to guide government decision-making, this poses a challenge: monetization of the benefits of reducing social exclusion is poorly developed. An evaluation gap thus confronts benefit-cost based assessment of initiatives intended to reduce social exclusion, compared to initiatives directed towards societal economic and environmental goals. This is a particular problem for public transport services that primarily enable people at risk of mobility-related social exclusion to access more opportunities in their society (social transit). The benefits of reducing social exclusion associated with these services have not been monetized, so social transit initiatives are poorly placed to argue their merits against competing initiatives where benefit monetization is more advanced (e.g., mass public transport and roads). The paper summarizes Australian research that has developed monetized measures for the value of increased trip making, bridging/bonding social capital, sense of community and several conceptions of wellbeing, and of reducing neighbourhood disadvantage, as these contribute to reducing social exclusion. New Singaporean research on the value of trip making to support reduced exclusion is also presented, affirming the Australian trip values. Trip values are then used in case study examples to show they can make a material difference to the societal worth of initiatives intended to reduce exclusion. Using these trip values, and other pathway values linked to reducing social exclusion, closes or at least substantially reduces the evaluation gap confronting social goal achievement in land use transport policy and planning, strengthening the case for reducing exclusion. These values will assist jurisdictions that are seeking to provide their residents with more equitable access to the benefits of their city.

This study examined carbon footprint as an indicator of soil health at spatiotemporal scales with different land use types and varying soil depths in Morogoro, representing the eastern agroecological zone of Tanzania. Soils are highly weathered and acidic. The specific objectives were twofold: (1) To quantify soil organic carbon (SOC) at varying soil depths (0–15 cm, 15–30 cm) in contrasting land use types, including tractor cultivated, hand-hoe cultivated, ranch land, and reserved/bare land type; (2) To predict carbon management indices (CMI) of the studied land use types through regresses SOC, carbon pool index (CPI), and lability index (LI) at varying soil depths. Composite soil samples were based on transects of three main plots each (replicates) of 20 m by 50 m. Results showed that land use types and soil depths significantly (P <0.001) affected SOC (3.4%) and CMI (126.3). Hand hoe cultivated land at 0–15 cm recorded CMI of 259.8. Regression analysis showed an increase in CMI ranging from 97% to 99%, with standard error ranging from 2.177 to 46.096. Similar trends, but with disparity magnitudes in regressed parameters provide useful insight into transformations of organic carbon in contrasting land use types.

The integration of transportation systems with land use through the Transit-Oriented Development (TOD) model can effectively promote sustainable development in cities. By increasing the intensive use of land within the supply capacity of urban public transportation, this model can comprehensively improve the efficiency of urban transportation and land use, while also addressing problems such as traffic congestion and environmental pollution. To implement this model, a "Node-Place-Function" (NPF) framework is proposed based on the coordination degree between rail transit and land use in Qingdao. A comprehensive evaluation system is constructed to quantitatively assess the TOD level and comprehensive development level of land use around rail transit stations from three dimensions. By applying the NSGA-II genetic algorithm, a land use allocation optimization model is developed to maximize rail transit station accessibility, land economic benefits, and environmental comfort. The research results guide other cities in China to implement TOD in land use planning and promote coordinated development between urban rail transit and land use.

The development of a decision framework for landscape governance and management has become one of the prioritised policy instruments for actualising policy objectives relating to agri-food system, biodiversity conservation, nature restoration, environmental management, climate change mitigation and adaptation, net zero greenhouse gas emissions, and the transition to renewable energy supplies in the United Kingdom (UK). However, the landscape lens in policy-making is challenging because of the diverse landscape archetypes, environmental problems, and diverging policy targets that it must address. This highlights the importance of having a robust, evidence-based landscape decisions framework. To address this issue, this study undertakes a systematic review and transdisciplinary synthesis of research outputs from the Landscape Decisions Programme (LDP). This study compiles and synthesizes outputs from the LDP projects in the context of the relevant literature to develop an understanding of the relationships among the emerging evidence with respect to decision-making for more sustainable and multifunctional landscapes. The synthesis analyzed the drivers of landscape decisions, and methodological approaches used to generate evidence for decision-making. The emerging themes from the synthesis were distilled into five principles that can be used as a basis for a roadmap towards the development of a holistic landscape decisions framework.

The eutrophication caused by excessive total nitrogen(TN) and total phosphorus(TP) emissions has been widely concerned by the whole society. Studies have revealed the relationship between land use and TN and TP, but the relationship between land use compound topographic position and TP and TN was seldom studied. Therefore, Spearman correlation and redundancy analyses were used to reveal the relationship between land use compound topographic position and TN and TP based on the monthly data of 28 water quality sampling sites and the land use data of 2013 and 2016 in the lakes of Guizhou Plateau. The results show that the nutritional state of the HBA watershed is medium. The trophic level index (TLI) value and TN concentration were high during flood, while TP concentration was high in dry period. The TN concentration in the tributaries was higher than that in the reservoir area. Construction and valley were the sources of the pollution, whereas forest land and gentle slope were the sink. According to the”source-sink”effect, the optimal zoning of land use was completed, and the urban land pollution govern area should be strengthened firstly. This paper can provide decision support for water environment management and sustainable development decision-making.