Land-use planning plays an important role in agricultural development, however it lacks tools to support planner in proposing land-use planning solutions especially, under saltwater intrusion condition in the coastal regions. This study aims to apply optimization in analyzing land-use solutions for agricultural land-use planning. In which a multi-objective optimization model is developed to optimize land-use area including land-use allocation taking into account socio-economic and environmental factors. The model has been applied in three districts of Soc Trang province, Vietnam (Long Phu, My Xuyen and Tran De) representing three ecological regions including salt water, brackish water and freshwater in the Mekong Delta of Vietnam. The results showed that two multi-objective optimization scenarios (in terms of profit, labor, environment benefits and risk reduction) have been implemented: (i) Multi-objective optimization of agricultural land-use until 2030 under normal conditions; (ii) Optimizing agricultural land-use until 2030 under climate change conditions similar to the 2016 drought and saltwater intrusion phenomenon in the Mekong Delta. The results showed that the second scenario is the option considered for implementing land-use plan thanks to the balance between good profits and minimizing economic and environmental risk. The land allocation was carried out taking into account household economic, the influence of adjacent production types, local traffic and canal systems factors to allocate optimal land-use areas. The combination of land-use optimization and spatial allocation process can help planners improve the quality of agricultural land-use planning.

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.

Long-term, high-accuracy mapping of built-up land dynamics is essential for understanding urbanization and its consequences for the environment. Despite advances in remote sensing and classification algorithms, built-up land mapping using early satellite imagery (e.g., from the 2000s and earlier) remains prone to uncertainty. We mapped the extent of built-up land in the North China Plain, one of China’s most important agricultural regions, from 1990 to 2019 at three-year intervals. Using dense time-stack Landsat data, we applied discrete Fourier transformation to create temporal predictors and reduce mapping uncertainties for early years. We improved overall accuracy by 8% compared to using spectral and indices predictors alone. We implemented a temporal correction algorithm to remove inconsistent pixel classifications, further improving accuracy to a consistently high level (>94%) across years. A cross-product comparison showed that our study achieved the highest levels of accuracy across years. Total built-up land in the North China Plain increased from 37,941 km² in 1990–1992 to 131,578 km² in 2017–2019. Consistent, high-accuracy built-up land mapping provides a reliable basis for policy planning in one of the most rapidly urbanizing regions of the planet.

Demographic and socio-economic developments couple with other requirements to satisfy human needs result in rapid urban expansion sometimes with increasing rate of surface extent greater than the rate of growth of population, that result in continuous sealing of ground surface thereby affecting ecosystem services. This study applied remote sensing toward achieving the progress of SDGs and stage to determine the ratio of the rate of land consumption to the rate of population growth of Gombe metropolis. QGIS 2.18 was used for the image processing and classification analysis for the key Landsat ETM+ (Enhanced Thematic Mapper), Impervious Surface Indices and population data to inform on the urban trend and LCR/PGR for the periods 2000-2005, 2005-2010, and 2010-2015. The result appears that the LCR/PGR for the periods of study show split trends. During 2000-2005 the result shows that the study area expanded outward with LCR/PGR of 1.2. The result also indicate that during 2005-2010, the study area densified with little expansion with the LCR/PGR of 0.8. The result further reveals that during 2010-2015 the LCR/PGR reached 1.8. Pointing that the study area expanded outward with the rate of ground sealing getting high.

The urbanization effects on land surface phenology (LSP) have been investigated by many studies, but few studies focused on the temporal variations of urbanization effects on LSP. In this study, we used the MODIS EVI, MODIS LST data and China’s Land Use/Cover Datasets (CLUDs) to investigate the temporal variations of urban heat island intensity and urbanization effects on LSP in Northeast China during 2001–2015. Land surface temperature (LST) and phenology differences between urban and rural areas represented the urban heat island intensity and urbanization effects on LSP, respectively. Mann-kendall nonparametric test and Sen's slope were used to evaluating the trends of urbanization effects on LSP and urban heat island intensity. The results indicated that the average land surface phenology (LSP) during 2001–2015 was characterized by high spatial heterogeneity. The start of the growing season (SOS) in old urban area had become earlier and earlier than rural area and the differences of SOS between urbanized area and the rural area changed greatly during 2001–2015 (−0.79 days/year, p < 0.01). Meanwhile, the length of the growing season (LOS) in urban and adjacent areas had become increasingly longer than rural area especially in urbanized area (0.92 days/year, p < 0.01), but the differences of the end of the growing season (EOS) between urban and adjacent areas did not change significantly. Next, the UHII increased in spring and autumn during the whole study period. Moreover, the correlation analysis indicated that the increasing urban heat island intensity in spring contributed greatly to the increases of urbanization effects on SOS, but the increasing urban heat island intensity in autumn did not lead to the increases of urbanization effects on EOS in Northeast China.

The research probes the relationship between the Minimum Support Price (MSP) price and its income impact on the farmers with different agricultural land-holdings. It examines maize crop cultivation income under three conditions if a farmer is getting crop production value at MSP, above 20% of MSP and above 40% of MSP. It then evaluates the farmers belonging to marginal, small, semi-medium, medium and large categories position in terms of poverty criteria suggested by the World bank. For analysis purposes, it uses an economic-model approach and suggest the concept of survival income for agricultural farmers. Its findings prove that marginal and small farmers require benefits beyond the MSP rate to push them above the poverty line.

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.

The identified Urban Heat Island (UHI) phenomenon, coupled with diminished vegetation and anthropogenic heat release, poses a significant environmental challenge for major urban centers. Particularly worrisome is the UHI effect in hot and temperate climates such as the Mediterranean region during the summer season. This exacerbates discomfort and heightens the risks of diseases linked to high temperatures. Additionally, it contributes to environmental consequences, including elevated electricity consumption due to increased demand for cooling [1]. The utilization of Remotely Sensed imagery for estimating Land Surface Temperature has become more prevalent in various applications associated with evaluating urban micro-climates and the Urban Heat Island (UHI) phenomenon. This study presents an algorithm for the automatic mapping of Land Surface Temperature (LST) from Landsat-8 data using a vegetation index-based technique in the Google Earth Engine (GEE) platform. The primary aim is to discern patterns and trends in LST over a 5-year period, from 2017 to 2021. The application was tested in the urban area of Thessaloniki, Northern Greece, which is particularly representative of the Mediterranean urban environment. Computation of Normalized Difference Indices (NDVI, NDBI, NDWI) for the study area was also performed within the GEE platform and correlation analysis was implemented to evaluate the impact of the urban landscape on the distribution of LST.

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.

Land surface temperature (LST) is a critical parameter for the dynamic simulation of land surface processes and for analyzing variations on regional or global scales. Obtaining LST with high spatiotemporal resolution is a subject of intensive and ongoing research. This study proposes a pixel-wise temporal alignment iterative linear regression model for downscaling based on MODIS LST products. This approach allows us to address the problem of high temporal resolution but low spatial resolution of the ERA5 reanalysis LST product, while remaining immune to pixel loss caused by clouds. The hourly ERA5 LST of the study area for 2012–2021 was downscaled to 1000 m resolution, and its accuracy was verified by comparison with measured data from meteorological stations. The downscaled LST offers intricate details and is faithful to the LST characteristics of distinct land-cover categories. In comparison with other downscaling techniques, the proposed technique is more stable and preserves the spatial distribution of ERA5 LST with minimal missing pixels. The pixel-wise average R-squared and mean absolute error for MODIS view times are 0.87 and 2.7 K, respectively, for cloud-free conditions at a 1000 m scale. Accuracy verification using data from meteorological stations indicates that the overall error is lower during cloudless periods rather than during overcast periods, during the night rather than during the day, and at MODIS view times rather than at non-view times. The maximum and minimum mean errors are 0.13 K for cloud-free periods and −0.98 K for cloudy periods, indicating a slight underestimation and overestimation, respectively. Conversely, the maximum and minimum mean absolute errors are 2.01 K for the daytime and 0.85 K for the nighttime. Therefore, the model ensures higher accuracy during cloudy periods with only clear sky LST as input data, making it suitable for long-term, all-weather ERA5 LST downscaling.

The mantle mass flow interconnected with the process of Glacial Isostatic Adjustment (GIA) and the reformation of the Earth’s crust constantly perturbs the observed gravity field towards a hypothetic isostatic state. We analyse the temporal changes of the gravity field from the GRACE data, using different mathematical and/or statistical methods to detect the GIA amidst other gravity signals. A number of gravimetric post-glacial land uplift rate (LUR) modelling methods are investigated and compared with the data from a total number of 515 GPS stations and preferred GIA forward models in Fennoscandia and North America. We investigate three mathematical methods, namely regression, principal component, and independent component analysis (ICA) to extracting the GIA signal from the GRACE monthly geoid heights. We use some regularization techniques to exploit the GRACE monthly data to their maximum spatial resolution and to increase the Signal to Noise Ratio of their short wavelengths. Near the centres of the study areas the gravimetric LUR model using the fast-ICA algorithm of Hyvärinen and Oja (2000) is shown to be in a complete agreement with the GPS data and the predictions of the GIA forward models, and for the whole areas, subject to epeirogeny movement of the two regions, their discrepancies reach to the extrema at -1.8 and +3.3, and -4.5 and +7.5 mm/a, respectively. We show that the largest discrepancies between the gravimetric model using the ICA method and the GIA forward model, occur for the sub-regions likely collocated with strong ice mass change signals.

Multiple social and environmental justice concerns are linked to urban form such as the distribution of socioeconomic class populations, healthcare spending, air pollution exposure, and human mobility. This study used 1m resolved LIDAR data to characterize land use in Salt Lake County, Utah and associate it with sociodemographic and air quality data at the census block group and zip code levels. We found that increasing tree cover was associated with higher per capita income and lower minority populations while increasing built cover was linked to lower per capita income and higher minority populations. Air quality showed less strong correlations, however, decreased non irrigated cover, increased built cover, and higher amounts of households living under poverty was related to higher long-term PM2.5 exposure. Several policy efforts have been undertaken to improve air quality and reduce negative health outcomes in Utah which are being informed by regulatory and research grade air quality sensors.

The 2018 summer drought in Europe was particularly extreme in terms of intensity and impact due to the combination of low rainfall and high temperatures. However, it remains unclear how this drought developed in time and space in such an extreme way. In this study we aimed to get a better understanding of the role of land-atmosphere interactions. More specifically, we investigated whether there was a change in water vapor originating from land, if that caused a reduction in rainfall, and by this mechanism possibly the propagation and intensification of the drought in Europe. Our first step was to use remote sensing products for soil moisture content (SMC) and the normalized difference vegetation index (NDVI) to see where the 2018 drought started and how it developed in time and space. Our SMC and NDVI analysis showed that the 2018 drought started to impact the soil and vegetation state in June in Scandinavia and the British Isles. After that it moved towards the West of Europe where it intensified in July and August. In September, it started to decay. In October, drought was observed in southeast Europe as well. Based on the observed patterns we divided Europe into six regions of similar spatiotemporal characteristics of SMC and NDVI. Then, we used a global gridded dataset of the fate of land evaporation (i.e., where it ends up as precipitation) to investigate whether the drought intensification and propagation was impacted by the reduction in water vapor transported from the regions that first experienced the drought. This impact was investigated by identifying the anomalies in the water vapor originating from land recycling, imports and exports within Europe during the spring, summer, and autumn seasons. From these regions we identified four drought regions and investigated the changes in water vapor originating from source regions on the development of drought in those regions. It was found that during the onset phase of the 2018 drought in Europe that the water vapor originating from land played an important role in mitigating the precipitation anomalies as, for example, the share of land evaporation contributing to precipitation increased from 27% (normal years) to 38% (2018) during July in West of Europe. Land evaporation played a minor role in amplifying it during the intensification phase of the drought as the share of land evaporation contribution to precipitation decreased from 23% (normal years) to 21% (2018) during August in West of Europe. These findings are somewhat in contrast to similar studies in other continents that found the land surface to play a strong amplifying role for drought development. Subsequently, we found that the relative increase in the amount of land water vapor originating from eastern half of Europe played a role in delaying the onset and accelerating the decay of the 2018 drought in West of Europe.

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.

Madagascar is home of many biodiversity and most of them are endemic to the island. Herpetofauna combining two classes of vertebrates such as amphibians and reptiles; this group with more than 350 described species for each class is considered as high diversity. Species in this group is more specialists in terms of habitat selection which they are forest dependent especially the eastern rainforest. Habitat loss by swidden agriculture practice and charcoal production is the main threat in this country. Forest regeneration is very difficult because people continue to use lands for crops until it’s becoming infertile. We conducted research impact of land use change on biodiversity considering amphibians and reptiles around CAZ. The study area is one of the biggest remaining corridors in the eastern of Madagascar. This study took account of four habitats from forest to degraded land and one additional land use which is the reforestation plot. The mains goal of this study is to compare species diversity and abundance in objectives to identify where we should focus on conservation in the future. Three standard methods for herpetofauna inventory were used for each land use. Forty four sites were visited and 152 species of amphibian and reptile were inventoried. Closed canopy forest is home of the most species that we found and the degraded land is the poorest in terms of species richness. Result of this study indicates also that habitat restoration is very important. The difference between land uses might be the result of the change on microclimate which affect species distribution.

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.

This study to assess the Physical Land Suitability Analysis for Cultivation of Selected Cool Weather Cereal Crops, Misha District, Hadiya Zone, South Central Ethiopia of major cereal crops of barley and teff in Misha district. Each of the criteria was separately reclassified and analyzed for their suitability for supporting barley and teff crops based on the FAO crop requirements specified for them. The major data sources were climatic data, soil, LGP and topographic data as well as key informant interview, questioner observation of crop requirements which have been considered to undertake suitability assessments of the study area. The factor maps like land use /land cover, temperature, rain fall, soil type and altitude were classified based on suitability evaluation methods of FAO and experts’ opinion. At final stage these were reclassified and standardized in GIS software extension tools, which led to the preparation of suitability analysis map of the major crops plant suitability classes. As part of spatial MCDM, AHP pair wise comparison module was used to derive internal and external weights for each individual factors and parameters respectively. Consequently, suitability analysis was done and weighted overlay suitability map was visualized with integration of GIS. The findings show that among total area of land suitability maps for both barley and teff cops were using weighted overlay techniques. The suitability map of teff crop shows that 12,038.22 hectare of the investigated area are highly suitable (S1), 19,646.07 hectare moderately suitable (S2) and 4,501.71 hectare marginally suitable (S3) and 112 hectare not suitable. On the other hand, the suitability map of barley crop shows that 7,898.52 hectare of the investigated area are highly suitable (S1), 22,830.08 hectare moderately suitable (S2), and 5,466.4 hectare marginally suitable (S3) and 103 hectare not suitable for economic reasons (N1). This was done for barley and Teff crops separately. Results of the study revealed that most of the lands in the study area are suitable for the cultivation of the selected crops and other crops. Based on finding, it could be recommended that this work would be used as policy guide for planners; investment could be successful in the District, further suitability research works should be carried out in order to optimize the major crop cultivation and production.

The relocation of Indonesia's capital to the IKN (Ibukota Negara) Nusantara in East Kalimantan is leading to significant changes in land use, shifting from natural vegetation and agriculture to urban infrastructure. This transition brings about economic diversification and urban expansion, but it also raises concerns about its impact on society, the economy, and the environment. The rapid development affects biodiversity conservation, food security, and the livelihoods of rural and indigenous communities, leading to conflicts across social and economic dimensions. This research uses qualitative and quantitative data to examine the socio-economic and environmental changes in the IKN Nusantara area from 2003 to 2023. The findings show a notable increase in built-up areas, indicating urbanization and a decrease in agricultural land. The study discusses the implications for local populations and ecosystems, emphasizing the need for inclusive governance, community participation, and conflict resolution. It also proposes a comprehensive policy framework that promotes sustainable land management, recognizes indigenous and local rights, and fosters inclusive economic growth to respect Indonesia's rich environmental and cultural heritage.

Present study on land use land cover analysis and taluka wise combination of cropped area, carried out in Beed district of Maharashtra state in India and studied 11 talukas of the district. Secondary data on land use land cover and area in various crops has been collected, compiled and analyzed from various secondary sources. Simple descriptive statistics used to examine the agricultural land use land cover and J.C. Weaver’s crop combination technique was used for taluka wise analysis of crop combinations and on the basis of highest to smallest area engaged in particular crop, crops have been ranked. The study showed that, in the district as a whole, percentage of uncultivated land other than fallow was about 46 percent as compare to net sown area is only 35 percent in total geographical area (1063855ha) of Beed district. The study further revealed that about 42 percent area engaged in food crops and about 58 percent area occupied by nonfood crops, which includes cereals (25%), cotton (19%), pulses (13%), oilseed (12%), sugarcane (5%) and fruits and vegetables (3%). Results of Weaver’s crop combination technique showed that the Wadwani taluka demarcated as most diversified taluka by means of maximum number (sixteen) of crops combinations with the lowest variance value (14) found in the present investigation. Further, the study revealed that the high crop diversity found in Dharur taluka with eighteen crop combinations and the taluka has given first rank amongst others. To derive the crop diversity ranking, taluka wise maximum to minimum number of crop combinations derived in different talukas and given ranks accordingly. The study concluded that, agricultural land use analysis is essential for solving and optimizing the land use problem, maintaining socio-ecological balance, best utilization of scarce resources. The authors enlightened that the rational use of agricultural land has important for food security and biodiversity which increase the productivity and profitability of the agriculture sector and it indicates the decision making ability of farmers in 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.

Based on data from the Yunnan Province farm household survey, we examine the effect of rural land rights policy on farmers’ income. The regression results show that right significantly raises the total income of farmers, with farm income serving as the primary source of total income. After performing numerous robustness tests, using instrumental variables to handle endogeneity and arriving at the same conclusion, the result is still valid. According to the heterogeneity analysis, in the sample of households with long-term migrant workers, the confirmation of rural land rights significantly increases total and nonfarm income while decreasing farm income. Furthermore, total income includes nonfarm income, which reflects the effect of different farmers' optimal labor allocation based on the external market environment. According to the impact mechanism anal-ysis, right can increase farmers' total income by promoting land transfer, and farmers in less developed areas are more willing to increase their income by land transfer out.

Daily maximum surface air temperature (Tamax) is a crucial factor for understanding complex land surface processes under rapid climate change. Remote detection of Tamax has widely relied on the empirical relationship between air temperature and land surface temperature (LST), a product derived from remote sensing. However, little is known about how such a relationship is affected by the high heterogeneity in landscapes and dynamics in seasonality. This study aims to advance our understanding of the roles of land cover and seasonal variation in the estimation of Tamax using the MODIS (Moderate Resolution Imaging Spectroradiometer) LST product. We developed statistical models to link Tamax and LST in the middle and lower reaches of the Yangtze River in China for five major land-cover types (i.e., forest, shrub, water, impervious surface, cropland, and grassland) and two seasons (i.e., growing season and non-growing season). Results show that the performance of modeling the Tamax-LST relationship was highly dependent on land cover and seasonal variation. Estimating Tamax over grasslands and water bodies achieved superior performance; while uncertainties were high over forested lands that contained extensive heterogeneity in species types, plant structure, and topography. We further found that all the land-cover specific models developed for the plant non-growing season outperformed the corresponding models developed for the growing season. Discrepancies in model performance mainly occurred in the vegetated areas (forest, cropland, and shrub), suggesting an important role of plant phenology in defining the statistical relationship between Tamax and LST. For impervious surfaces, the challenge of capturing the high spatial heterogeneity in urban settings using the low-resolution MODIS data made Tamax estimation a difficult task, which was especially true in the growing season.

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.

Land Surface Temperature (LST) is routinely retrieved from remote sensing instruments using semi-empirical relationships between top of atmosphere (TOA) radiances and LST, using ancillary data such as total column water vapor or emissivity. These algorithms are calibrated using a set of forward radiative transfer simulations that return the TOA radiances given the LST and the thermodynamic profiles. The simulations are done in order to cover a wide range of surface and atmospheric conditions and viewing geometries. This work analyses calibration strategies, considering some of the most critical factors that need to be taken into account when building a calibration dataset, covering the full dynamic range of relevant variables. A sensitivity analysis of split-windows and single channel algorithms revealed that selecting a set of atmospheric profiles that spans the full range of surface temperatures and total column water vapor combinations that are physically possible seems beneficial for the quality of the regression model. However, the calibration is extremely sensitive to the low-level structure of the atmosphere indicating that the presence of atmospheric boundary layer features such as temperature inversions or strong vertical gradients of thermodynamic properties may affect LST retrievals in a non-trivial way. This article describes the criteria established in the EUMETSAT Land Surface Analysis – Satellite Application Facility to calibrate its LST algorithms applied both for current and forthcoming sensors.

Population is the main driver of land systems and environmental change. However, the population is usually treated as a variable that only considers the population number, and the multidimensional population structure is largely ignored. There has been a systematic transition of population structure in the past several decades, such as the changing household structure, the increasing aging population and divorce rate, and human migration. All these have direct or indirect impacts on land use and environmental issues. Here, we will take China as an example to examine the relationship between household dynamics and land use change in China by exam-ining changes in household structure and land use change in China between 1980 and 2020. The results show:1) the number of households increased by 130.95% from 1980 to 2020, while the population only increased by 42.83%. The size of households decreased from 4.41 to 2.92 in China from 1982 to 2020. The household dynamics vary from province to province, which is affected by urbanization rate and economic development. 2) Birth rates, divorce rates, population aging, and migration all affect household structure, which directly or indirectly affects changes in land use systems. 3) The changes in China's land use are interlinked and interact with changes in household structure, evident in the increase in residential land use and the abandonment of arable land. The rising household number increased the area of urban and rural settlement, leading to the fragmentation of cultivated land and the reduction of ecological land. To regulate land use change for sustainable development, future land use planning should take into effect of household dynamics, and reduce the negative effects of household dynamics on land systems and environmental change.

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.

Taxes on the consumption of certain products have played a key role in public revenue analysis in European countries. This work aims to assess the differences in tax planning on new non-combustion products across some European territories. Through theoretical analysis, the paper has three distinct aspects. Firstly, we show the taxpayer profile in different countries. Secondly, the study analyzes the risks for the health system and the individual. Thirdly, the design of the land tax is based on previous experience and planning in Europe. This paper concludes with a case study for different countries: 1) Spain “vapers” and “smokers”, where the analysis is based on micro-data from the European Health Interview Survey 2020. 2) Sweden with the analysis of snus, shows it as a practice to reach economic savings while decreasing economic costs thanks to the nudging of consumers towards better products. The results show taxation and, specially, land taxation, should consider differences in planning in the case of new products, such as the non-combustion products, given the user per capita income and the potential lower health risks involved.

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.

Taking a typical forest underlying surface as the research area, this study employed the unmanned aerial vehicle (UAV) photogrammetry to explore more accurate canopy parameters including tree height and canopy radius, which were used to improve the Noah-MP land surface model conducted in Dinghushan Forest Ecosystem Research Station (CN-Din). While the canopy radius was fitted as a Burr distribution, the canopy height of CN-Din forest followed a Weibull distribution. The replacement of the parameters by these observed UAV would result in the Noah-MP model. It was found that the influence on the simulation of the energy fluxes could not be negligible, and the main influence of these canopy parameters was on the latent heat flux which could decrease up to -11% in the midday while increase up to 15% in the nighttime. Additionally, this work indicated that the description of the canopy characteristics for the land surface model should be improved to accurately deliver the heterogeneity for the underlying surface.

Land cover change detection (LCCD) based on bi-temporal remote sensing images plays an important role in the inventory of land cover change. Due to the benefit of having spatial dependency properties within the image space while using remote sensing images for detecting land cover change, many contextual information based change detection methods have been proposed during past decades. However, there is still a space for improvement in accuracies and usability of LCCD. In this paper, a LCCD method based on adaptive contextual information is proposed. First, an adaptive region is constructed by gradually detecting the spectral similarity surrounding a central pixel. Second, the Euclidean distance between pairwise extended regions is calculated to measure the change magnitude between the pairwise central pixels of bi-temporal images. While the whole bi-temporal images are scanned pixel-by-pixel, the change magnitude image (CMI) can be generated. Then, the Otsu or a manual threshold is employed to acquire the binary change detection map (BCDM). The detection accuracies of the proposed approach are investigated by two land cover change cases with Landsat bi-temporal remote sensing images. In comparison to several widely used change detection methods, the proposed approach can achieve a land cover change inventory map with a competitive accuracy.

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.

The impact of the agriculture net carbon effect is crucial for climate change mitigation, yet research on this topic in China is currently insufficient. In this study, the carbon balance ratio (CBR) is used to characterise the net carbon effect of agriculture, and the spatial Durbin model and threshold regression model were used to empirically analyse the CBR with a sample of 30 provincial-level regions in China from 2004 to 2019. The aim was to investigate the mechanism of the influence of the land management scale (SCALE) of farming on the CBR. The results of the study indicate that national farming generally has a net sink effect, with large changes in interannual fluctuations; the expansion of SCALE has an obvious role in increasing sinks and reducing emissions, and has a positive spatial spillover effect on CBR, with significant spatial heterogeneity. Furthermore, as the SCALE expands, the direction of the influence of rural residents’ income and education level on CBR changes in the opposite direction, showing a significant non-linear relationship characteristic. However, in most areas, the SCALE threshold has not yet been reached, suggesting that the improvement in education levels can still offset the negative impact of economic income growth in the short term. The study recommends paying attention to the role of farmers’ human capital, changing production methods, and implementing carbon peaking and carbon neutrality goals to enhance the net sink effect of the farming industry, which would be achieved by increasing land management scale.

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.

Remote sensing technologies may play a fundamental role in the environmental assessment of open-cast mining and the accurate quantification of mine land rehabilitation efforts. Here, we developed a systematic geographic object-based image analysis (GEOBIA) approach to map the amount of revegetated area and to quantify the land-use changes in open-cast mines in the Carajás region situated in the eastern Amazon. Based on high-resolution satellite images from 2011 to 2015 from different sensors (GeoEye, WorldView-3 and Ikonos), we quantified forests, cangas (natural metalliferous savanna ecosystems), mine land, revegetated areas and water bodies. Based on the GEOBIA approach, threshold values were established to discriminate land cover classes using spectral bands, and the NDVI and NDWI indices and LiDAR digital ground and slope models. The overall accuracy was higher than 90%, and the Kappa indices varied between 0.82 and 0.88. During the observation period, the mining complex expanded; for that, canga and forest vegetation was converted to mine land. At the same time, the amount of revegetated area increased. Thus, we conclude that our approach is capable of providing consistent information regarding land cover changes in mines, with a special focus on the amount of revegetation necessary to fulfill environmental liabilities.

Indigenous traditional land uses, including hunting, fishing, sacred activies and land-based education at Red Sucker Lake First Nation (RSLFN) in Manitoba, Canada are impacted by mining. Traditional land use maps and interviews were undertaken with 21 Indigenous people from RSLFN, showing many traditional land uses are concentrated on greenstone belts. The interviews revealed that mining exploration has resulted in large petroleum spills, noise distress, personal property destruction, wildlife die-offs and animal population declines, which negatively impact RSLFN’s traditional land use practices, ecosystem integrity, and community health. Red Sucker Lake First Nation (RSLFN) people want their territories’ land and water protected for traditional uses, culture and ecological integrity. Towards this goal, their Island Lake Tribal Council sought support for an Indigenous-protected and conserved area (IPCA) in their territory outside of existing mining claims, but without success. Governments need to partner with Indigenous nations to reach their biodiversity targets, particularly considering northern Canada’s peatlands, including those in Island Lake, surpassing the Amazon forests for carbon storage. Critical minerals and gold’s role in renewable energy and geopolitics have colonial governments undermining Indigenous rights, climate stabilization and biodiversity. With extractivism prioritized, the environmental impacts of mining extend to not only the mines but also the extensive development required to facilitate extraction including roads, hydro and ports to ship the minerals with proposals for a national Northern Corridor to run nearby.

Nanling Mountain region is a typical southern hilly region, which plays an important ecological and environmental protection role in China's overall land protection pattern. Based on the remote sensing image data of Longnan City in Nanling Mountain in 2013, 2018 and 2023, this paper interpreted the land use type and analyzed the land use transfer situation by using Land use transfer flow, and Land use transfer matrix. At the same time, based on the remote sensing Ecological index (RSEI) model, the ecological environment quality of Longnan City from 2013 to 2023 was retrieved. The temporal and spatial response model of ecological environment quality to land use transfer in Longnan City from 2013 to 2023 was discussed based on Spatial autocorrelation and Geographic detector. The results show that from 2013 to 2023, the decrease of forest land (16.23km²) and the increase of construction land (13.25km²) were the main land use transfer in Longnan City. The ecological environment index of Longnan City in 2013, 2018 and 2023 was 0.789, 0.917 and 0.872, respectively, showing a trend of "first rising and then decreasing". The ecological environment quality in the north of Longnan City was significantly lower than that in the south, and the poor ecological quality area appeared in and around the northern main urban area, showing a trend of "inward contraction". Forest land, garden land, grassland, cultivated land and water area have a positive impact on ecological environment quality, while traffic land, construction land and other land have a negative impact on ecological environment quality. The response of ecological environment quality to different land use transfer modes is related to the change of the overall ecological environment quality. The interaction between LUCC and other factors had a great impact on the evolution of ecological environment quality in Longnan City.

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.

The use of wind energy has been developing fast over the last years. The global cumulative wind power capacity increased by 10.5% in 2019, most of which comes from onshore wind farms. One of the consequences of this continuous increase is the use of land for onshore wind farms. There are already cases worldwide where lack of well-established plans and strategies have caused delays in projects. The need for efficiently using land for wind farms will be mandatory in the short term. In this work, we present a numerical analysis to evaluate wind farm land-use. By defining the ratio between mechanical output power over an area as a parameter called land-use ratio, this work focused on comparing several cases of aligned and staggered layouts. Mechanical output power was estimated using a validated code based on Blade Element Momentum code, and the wake velocities and wake interaction effects were estimated using a validated wind turbine CFD model. In terms of output power, staggered designs are more efficient than aligned designs. However, the results showed that even though staggered designs produced higher output power, aligned farms with tight lateral spacing could be as efficient as staggered ones in terms of land-use but using fewer turbines. In summary, tightly aligned designs should be a tendency in the future towards efficient use of land in wind farms.

This paper explores the role of agroforestry in mitigating climate change by sequestering atmospheric carbon in the tropics and subtropics, specifically in the Madhupur Sal forest of Bangladesh. Agroforestry, combining trees with crops on agricultural lands, is recognized for its potential to act as carbon sinks and enhance productivity. The study assesses various agroforestry practices, including Acacia-Pineapple-Turmeric-Papaya, Acacia-Pineapple-Zinger-Banana, and Sal-Pineapple-Aroid combinations. The research reveals improved farm productivity in these agroforestry systems, with different tree species sequestering varying amounts of carbon. Acacia species, ranging from 12 to 25ft in height, sequestered an average of 23.35 lbs/year, while Sal species (Shorea robusta), with trees 45 to 61ft tall, sequestered 49.80 lbs/year on average. Factors such as tree height, diameter at breast height (DBH), number of leaves, and branches influence carbon sequestration. The paper suggests integrating the carbon trading system of the Clean Development Mechanism (CDM) with Carbon Sequestration (CS) potential to leverage agroforestry for greenhouse gas emission reduction in Bangladesh. By emphasizing the profitability of these practices alongside carbon sequestration, the study encourages the adoption of agroforestry as a sustainable and economically viable strategy for climate change mitigation.

In order to alleviate the conflict between populations and land-resource, Tianjin has adopted multi-phase reclamation projects to formed large-scale artificial reclamation land. However, the reclamation areas are susceptible to subsidence, which demonstrate a serious threat to infrastructure and people’s lives and property. The SBAS-InSAR was used to acquired surface deformation of Tianjin Binhai New Area from January 2017 year to December 2022 year, analyzed in depth the response relationship between land subsidence and reclamation projects time as well as the land use type. The results show that the Lingang Industrial Zone was the earliest to be reclaimed, with extensive reclamation completed by 2016 year, while Nangang Industrial Zone and Hangu Port started reclamation projects in 2009 year, some areas are still currently under construction. There is a strong correlation between surface deformation and reclamation time, the severe land subsidence occurred over newly reclaimed areas. Surface deformation gradually intensifies from west to east, the maximum surface settlement in Nangang Industrial Zone, Lingang Industrial Zone from the west to the east has changed from -50 mm to -890 mm,45 mm to -580 mm, respectively, reclamation area of Hangu Port with maximum surface deformation is -250 mm. Significant differences deformation among different land use types, which reclamation projects completed in the same time. Subsidence is positively correlated with surface load, in areas with higher surface loads, the surface settlement is also severer,the average surface settlement for the heavy shipyard, 67 grain storage tanks, 27 grain storage tanks, road, and bare land are -201 mm, -166 mm, -107 mm, -64 mm, and -43 mm, respectively. This study reveals significant differences of surface deformation in the reclamation completed at different times and the load is the main driving factor of settlement difference in the reclamation land completed at the same time. Which has important guiding significance for preventing and controlling geological disasters in the reclamation area and later development planning.

The sustainable management of Land - Water - Energy - Food (LWEF) nexus requires an envi-ronmental characterization that allows the comparison of complex interlinkages between nexus resources and livelihoods. This complexity makes this characterization difficult coupled with limited study in quantifying sustainability of LWEF nexus and its linkage with livelihood. Therefore, the present study aimed to investigate the link between sustainable LWEF nexus and livelihoods. We used analytical hierarchy process and pairwise comparison matrix in combina-tion with weighting model. The result of composite LWEF nexus index was 0.083 representing, low sustainability. This could be linked with nexus resources consumption, use, and manage-ment. From the analysis of the weight of land, water, energy and food nexus resources, the highest weight was observed for food. The focus of on food production only shows no clear synergy on provisioning, supporting or regulating nexus resources to address livelihoods. The result further showed that LWEF nexus resources have strong correlation with livelihoods. This was evidenced by social (r>0.8, P<0.01), natural (r>0.3, P<0.05) and physical (r>0.6, P<0.01) liveli-hood indicators showed strong positive correlation with LWEF nexus resources. From this re-sults, it was observed that managing nexus resources not only provide a significant contribution to achieve sustainable LWEF nexus, but also be effective for enhancing livelihood through food security. This could be attained by strong evidence based policy to ensure sustainable use of nexus resources. The results provided by this study would serve as the foundation for future study, policy formulation and implementation.

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.

In the context of the energy transition, the integration of land use considerations into energy planning is increasingly vital, especially in scenarios where land availability is a constraint. This study addresses the challenge of incorporating land-use aspects into Energy System Optimization Models (ESOMs), with a focus on the unique context of Pantelleria Island. It aims to bridge the gap in methodologies for renewable energy potential assessment and model integration, considering the critical role of land pricing and availability. It combines geospatial data aggregation with model adaptation to include detailed land use aspects. Findings highlight the substantial impact of land costs on renewable energy planning, with land pricing significantly altering model outcomes. This research offers key insights for sustainable energy planning and underscores the importance of considering land use in energy transition strategies.

Land use is an embodiment of human socioeconomic activities and represents a bridge between these activities and natural systems. Through social activities, humans transform land use to promote social and economic development and improve production, living conditions, and eco-logical functions of land. Rural residential land represents a space for rural residents to reside in and exhibits spatial characteristics that evolve over time, which is proof of rural socioeconomic development. This paper observes rural residential land in 21 cities on the Grand Canal and analyses its spatial differentiation. Then, it explores the driving factors of this land using spatial grid analysis and the geographic detector model. Lastly, it proposes three different forms of rural residential land based on the results. The study found that: (1) the change of rural residential land in the northern part of the Grand Canal was more volatile than that in the southern part. The change of rural residential land from 1990 to 2020 conformed to the pattern of cultivated land - rural residential land - urban construction land; (2) Based on the driving factors of rural residen-tial land, the land is divided into one-dimensional cities, two-dimensional cities and three-dimensional cities. Circular, linear, and scattered cities of different sizes were affected by socioeconomic factors, transportation accessibility, and the natural environment, respectively; and (3) Finally, according to the spatial differentiation characteristics and the driving factors of rural residential land, the study proposes the construction of three types of villages through the strate-gies of constructing large-scale villages, relocating and reconstructing new villages, and con-structing high-quality villages, respectively. Enhancing the scientific planning of rural residential land and its efficiency can offer the protection of agricultural land and the integration of urban and rural areas in the new era.

Assessment of the trends of land cover and vegetation dynamics (VD) using remote sensing (RS) and indicators such as anthropogenic activities and the socio-demographic information is essential in order to make proper planning for sustainable management. This paper attempts to evaluate land cover change (LCC) and VD in Kebbi State, Nigeria using historical Landsat data from 1986-2016 by means of remote sensing. The Driver-Pressure-State-Impact-Response (DPSIR) framework was later employed using both primary and secondary data for a better understanding of the drivers, the state of the environmental condition, the causes as well as the impact of the change. The images were classified into five thematic land cover classes as Dense Vegetation, shrubs/built area, farmland, bare/grassland and water body by means of Maximum likelihood supervised classification technique in accordance with Anderson classification scheme level 1, with acceptable accuracy. Pre-classification and post-classification change detection (CD) methodologies were executed using Normalized difference vegetation index (NDVI) and Image differencing respectively. The study illustrates a steady decline in dense vegetation and shrubs/build areas while farmland and bare/grassland increases, however, water bodies remain unchanged. The DPSIR pin-point that the major drivers of change in the study area have been the pressing need for farming land as the population grows and socioeconomic demands including fuelwood consumption and endemic poverty. Expansion of Farming land, fuelwood consumption and the need for construction materials are identified as the main key elements exerting pressure for the change. The state of the condition indicates a steady decline in dense vegetation and shrubs areas while farmland and bare/grassland are increasing significantly. The impacts include land degradation, the decline in the provision ecosystem goods and services, biodiversity loss through loss of habitats. The study, however, noted that many international and national policies in response to land degradation are channelled toward land restoration and remediating of the environment, through afforestation programs and improving the livelihood of the rural people through providing alternative income sources since they depend heavily on land for sustenance. However, the state governments, communities and individual commonly organized annual tree planting campaign with the main purpose of environmental protection.

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.

Floods are the most frequent and devastating disasters in Bangladesh. The riverine islands, known as char-lands, are particularly vulnerable to flooding. As flooding poses a significant threat to the lives and livelihoods of residents, especially farmers, it is crucial to understand how they perceive flood risk and assess their adaptation strategies in this geographically susceptible context. However, the existing literature has not adequately addressed these issues. Therefore, this study aims to analyze the factors influencing farmers' perceived flood risk and their assessments of flood adaptation. In a survey of 359 farmers in Bangladesh's char-land region, located in the Chowhali sub-district of Sirajganj district, we used the protection motivation theory (PMT) to measure farmers' perceived flood risk and adaptation assessments. Multiple regression analysis was employed to identify factors influencing them. Farmers prioritized the risk to livelihoods (production and income) over psychological aspects (health and diseases). Larger farms, more flood experience, and greater risk awareness are associated with higher overall flood risk perception; and better flood adaptation, indicating higher self-efficacy, response efficacy, and response cost among farmers. Farmers perceived lower flood risk in exchange for greater house distance from the river and more trust in government actions. Hence, strengthening campaigns and programs is crucial to understanding flood risk in char-lands for improved adaptation to floods. The study highlights the application of PMT to assess farmers' perceptions of flood risk and their attitudes towards adaptation, suggesting further research opportunities.

Satellite-based remote sensing technologies are utilized extensively to investigate urban thermal environments under rapid urban expansion. Current MODIS data is, however, unable to adequately represent the spatially detailed information because of its relatively coarser spatial resolution, while Landsat data can’t explore temporally the refined analysis due to the low temporal resolution. In order to resolve this situation, we used MODIS and Landsat data to generate “Landsat-like” data by using the flexible spatiotemporal data fusion method (FSDAF), and then studied spatiotemporal variation of land surface temperature (LST) and its driving factors. The results showed that 1) The estimated “Landsat-like” data have high precision; 2) By comparing 2013 and 2016 datasets, LST increases ranging from 1.8°C to 4°C were measurable in areas where the impervious surface area (ISA) increased, while LST decreases ranging from -3.52°C to -0.70°C were detected in areas where ISA decreased; 3) LST has a strongly negative relationship with the Normalized Difference Vegetation Index (NDVI), and a strongly positive relationship with Normalized Difference Built Index (NDBI) in summer; and 4) LST is well correlated with Building density (BD), in a complex conic mode, and LST may increase by 0.460°C to 0.786°C when BD increases by 0.1. Our findings can provide information useful for mitigating undesirable thermal conditions and for long-term urban thermal environmental management.

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.

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.

Tesso Nilo National Park is one of the protected areas designated as KPA by the Decree of the Minister of Forestry No.225/Menhut-II/2004 dated July 19, 2004 covering an area of ​​38,576 ha, then expanded again through the Decree of the Minister of Forestry No.663/Menhut/2009 dated 19 October 2009 with an area of ​​± 83,068 ha. The Tesso Nilo National Park area is experiencing the dynamics of land cover changes, namely the conversion of forest land which causes the forest area to become increasingly narrow in this area. With the reduction in forest area in this area, it causes a decrease in ecosystem network connectivity due to forest fragmentation that occurs, so that forests are separated and further apart. This study aims to analyze changes in land cover in the Tesso Nilo National Park area to find out information on changes in habitat ecosystems in the last 20 years. the observations were made using satellite images in 1999, 2010 and 2019. so that it can be seen the effect of forest fragmentation on ecosystems in the Tesso Nilo National Park area. From the results of the analysis, it was found that the area of ​​forest cover in the Tesso Nilo National Park decreased from 1999 to 2019 and caused changes in the connectivity network of forest ecosystems, which was found in the study, the weakest connectivity separated forest fragments as far as 17394.47 meters due to forest cover fragmentation.

Several extinctions have already been attributed, at least in part, to global warming, as climate change constitutes a serious threat for species living in isolated ecosystems and thus unable to track habitat changes. However, in all these cases extinction was due to human impacts, often directly but generally also through exotic invasive species. For two arboreal land snails in Indian Ocean islands a link has been proposed with decreasing rainfall. The decline (but probably not extinction) of Pachnodus velutinus, a specialist of moist forests on the summits of northwestern Mahé, was most likely caused instead by invasive plants altering its habitat and alien predators decimating the population in the small remaining moist forests. An alternative explanation assuming genetic swamping through hybridization with a species from lower elevations has no basis, as the presumed hybrid constitutes a distinct species able to survive in the altered, dryer habitat. On Aldabra Atoll, the endemic Rhachistia aldabrae was claimed to have been the first extinction due to climate change, but is still extant. No relationship can be detected between number of sightings and annual rainfall, although a weighted measure that takes into account rainfall in previous years suggests a limited impact of weather. Analysis of the sighting record in various ways yields a probability of survival over time that never dropped below 0.3. The decline was caused instead by intense impacts of exotic invasive species. Alternative shortcuts to evaluate extinction rates among poorly known species are shown to be unreliable. Although no contemporary extinction can still be attributed to climate change, indirect and synergistic impacts on biodiversity are expected, especially through promoting biological invasions.

The rural population percentage decreased from 82.7% to 68.9% in 2011, even though there is an increase in the total rural population, which stands at 833.7 million, and the rural population were now more than three times compared to the population seven decades ago. Another observation is the decrease in cultivators percentage from 71.9% to 45.1 %, while agriculture labour increase from 28.1% to 54.9% during the same period. Despite the increase in irrigated land and net area sown, the average holdings' size under the farmers is continuously decreasing, and it requires a study to look into the reasons. The research probes the role of Minimum Support Price (MSP) in supporting farmers and measuring market price above MSP needed to help marginal and small farmers remain above the poverty level. It explains how different market rates above MSP have a different impact on different categories of agriculture landholding. The study works on developing a common model that relates the impact of MSP on different farmers categories. The model can be generalized to all crops and regions and useful in designing policies that focus on uplifting the income of agricultural farmers.

Section 25(2) of the Constitution of South Africa protects property rights and the White Paper on Land Reform demonstrate tolerance and wisdom in the application of land reform policies. The central argument to this research was whether amendment of Section 25 (2) of the constitution to allow expropriation of land without compensation redresses redistribution of land for social cohesion and political stability. The researcher argues that, currently, Section 25 of the constitution provides for expropriation without compensation but at the same time protects property rights reducing the pace of redistribution. Hence, an amendment of section 25 (2) may remove the property right clause and accelerate expropriation without compensation. But whether the removal of the property right clause and acceleration of the process of expropriation without compensation will result to equitable and fair distribution of land to the majority of landless South Africans is not certain. The study concludes that, amendment of Section 25(2) is a justifiable process and priorities must be given to equity in redistribution to the majority landless at the margins of communities and not elites. If the amendment of Section 25 (2) cannot guarantee equity in redistribution for all ill respective of race, social cohesion, political stability and economic growth, intra-racial tensions may emerge. Such tensions may further compound the land question and affects investors’ confidence in South Africa.

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.

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.

This study has simulated the typical rainstorm on 20 July 2021 over central east China by using the first-generation Chinese Reanalysis datasets and Global Land Data Assimilation System datasets, and the Noah land surface model coupled with the advanced weather research and forecasting model. Based on this, the gridded planetary boundary layer (PBL) profiles and ensemble states within soil perturbations are collected to investigate the main land-atmosphere coupling characteristics during this modeled rainstorm by using various local coupling metrics and the introduced ensemble statistical metrics. Results have shown that (1) except for the stratospheric thermodynamics and surface thermal over mountain areas, the main characteristics of mid-low layers and surface have been well documented in this modeled rainstorm; (2) the typical coupling intensity is characterized by the dominant morning moistening, early noon weak PBL warming around 2, noontime buoyant mixing temperature deficit around 274 K, daytime PBL and surface latent flux contribution around 100 and 280 W/m2 respectively, and significant afternoon soil-surface latent flux coupling; (3) moist static energy is more significant than PBL height during the relation chains, which is consistent with the significance of surface moistening indicated by local coupling metrics. In general, wet soil contributes greatly to daytime moisture evaporation, which then increases the early noon PBL warming and enhances the noontime buoyant mixing within weak flux contribution. However, this has been suppressed by large-scale forcing such as the upper southwestern inflows of rainstorms, which has further significantly shaped the spatial distribution of statistical metrics in contrast. These quantitatively described local couplings have highlighted both the convection potential diagnoses usage for the local weather application and more applicable coupling threshold diagnoses within the finer spatial investigation.

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.

SOC stock (SOCS) changes caused by land use changes are still unclear, and understanding this response is essential for many environmental policies and land management practices. In this study, we investigated the temporal-spatial and vertical distribution characteristics of SOCS on the Western Sichuan Plateau (WSP) using the sparrow search algorithm-random forest regression (SSA-RFR) models with excellent model applicability and accuracy. The temporal-spatial varia-tions in the SOCS were modeled using 1080 soil samples and a set of nine environmental covariates. We analyzed the effect of land use changes on the SOCS on the WSP. The total SOCS increased by 18.03 Tg C from 1990 to 2020. The results of this study confirmed that the SOCS in the study area has increased significantly since 2010, with an increase of 27.88 Tg C compared to the total SOCS in 2010. We found that the spatial distribution of the SOCS increased from southeast to northwest, and the vertical distribution of the SOCS in the study area decreased with increasing soil depth. Forest and grassland are the main sources of SOCS, the total SOCS in the forest and grassland accounted for 37.53 and 59.39% of the total SOC pool in 2020, respectively. Expansion of the wetlands, forest, and grassland areas could increase SOCS in the study area.

The modification of land use is a crucial factor in the dysfunction of ecosystems. It considerably influences the hydrological cycle of basins. This study focuses on the Oueme basin, which represents almost half of the total area of Benin, and describes the current and future evolution of its land cover using the maps of the Land Use Land Cover Dynamics project (1975, 2000 and 2013). A temporal analysis of the surface states was performed with QGIS and the potential land cover in 2025, 2050 and 2085 was estimated using the Markov chain algorithm in the IDRISI software. The results show that the Oueme basin is predominantly savanna (77.70% in 1975, 66.29% in 2000 and 57.10% in 2013). Forest areas, which represented the second class in 1975 with a total proportion of 13.34%, have gradually decreased to 8.66% and 6.89% respectively in 2000 and 2013. Conversely, cultivated areas more than tripled in 2000 and quadrupled in 2013. Residential areas are increasing very strongly in the southern part of the basin with an amplification in the recent period (6% between 2000-2013 against 2% between 1975-2000). The recent period is more exposed to changes in surface condition and these changes are likely to be amplified in the future (probable total disappearance of forested areas in 2085). We recommend clarifying the impacts that each land use category generates/will generate on the hydrological cycle of this basin.

Fire regimes in mountain landscapes of southern Europe have been shifting from their baselines due to rural abandonment and fire exclusion policies. Understanding the effects of fire on biodiversity is paramount to implement adequate management. Herein, we evaluated the relative role of burn severity and heterogeneity on bird abundance in an abandoned mountain range located in the biogeographic transition between the Eurosiberian and Mediterranean region (the Natural Park ‘Baixa Limia–Serra do Xurés’). We surveyed the bird community in 206 census plots distributed across the Natural Park, both inside and outside areas affected by wildfires over the last 11 years (from 2010 to 2020). We used satellite images of Sentinel 2 and Landsat missions to quantify the burn severity and heterogeneity of each fire within each surveyed plot. We also accounted for the past land use (forestry or agropastoral use) by using a land cover information for year 2010 derived from satellite image classification. We recorded 1,735 contacts from 28 bird species. Our models, fitted by using GLMs with Poisson error distribution (pseudo-R²_-average of 0.22 ± 0.13), showed that up to 71% of the modelled species were linearly correlated with at least one attribute of the fire regime. The spatiotemporal variation in burnt area and severity were relevant factors for explaining the local abundance of our target species (39% of the species; Akaike weights > 0.75). We also found a quadratic effect of at least one fire regime attribute on bird abundance for 60% of the modeled species. The past land use, and its legacy after 10 years, was critical to understand the role of fire (Akaike weights > 0.75). Our findings confirm the importance of incorporating remotely sensed indicators of burn severity into the toolkit of decision makers to accurately anticipate the response of birds to fire management.

Mount Hamiding Protected Forest is located in North Halmahera Regency, North Maluku Province, the Wallace zone has an important role in providing protection functions, life support systems and regulating water management, preventing floods, preventing seawater intrusion, and controlling soil fertility. The protected forest area in the Wallace Zone is globally renowned for its endemic characteristics of flora and fauna. The condition of the protected forest of Mount Hamiding HMPF is currently experiencing anthropogenic damage as a result of forest encroachment, illegal logging, shifting cultivation, grazing and poaching to meet social needs. Anthropogenic damage has been in the spotlight for decades and has become a global issue. This study aims to determine damage to protected forests, changes in land cover, and mitigation of protected forest areas. This research uses quantitative and descriptive qualitative methods. Determination of research locations by purposive sampling. Parameters measured in this study were damage to protected forests, changes in land cover and area mitigation strategies. To identify forest damage, snowball sampling was carried out, and land cover changes through land cover data processing were obtained from the Ministry of Environment and Forestry of the Republic of Indonesia. Then using Imagery 7 ETM+ and 8 OLI to calculate changes in forested land to non-forested from 2006 -2021, analysis of land cover change using supervised classification, developing a strategy based on identity verification of forest damage and analysis of land cover change. The results showed that damage to protected forests was caused by anthropogenic disturbances in the form of forest encroachment, shifting cultivation, illegal logging, grazing and hunting of wild animals. Changes in land cover experienced the greatest damage in 2006-2021 amounting to 1,796.54 ha (16.17%). Strategic efforts are carried out using forest engineering, namely the agroforestry system and social engineering through community empowerment, namely training and outreach.

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.

LDAS-Monde, an offline land data assimilation system with global capacity, is applied over the CONtiguous US (CONUS) domain to enhance monitoring accuracy for water and energy states and fluxes. LDAS-Monde ingests satellite-derived Surface Soil Moisture (SSM) and Leaf Area Index (LAI) estimates to constrain the Interactions between Soil, Biosphere, and Atmosphere (ISBA) Land Surface Model (LSM) coupled with the CNRM (Centre National de Recherches Météorologiques) version of the Total Runoff Integrating Pathways (CTRIP) continental hydrological system (ISBA-CTRIP). LDAS-Monde is forced by the ERA-5 atmospheric reanalysis from the European Center For Medium Range Weather Forecast (ECMWF) from 2010 to 2016 leading to a 7-yr, quarter degree spatial resolution offline reanalysis of Land Surface Variables (LSVs) over CONUS. The impact of assimilating LAI and SSM into LDAS-Monde is assessed over North America, by comparison to satellite-driven model estimates of land evapotranspiration from the Global Land Evaporation Amsterdam Model (GLEAM) project, and upscaled ground-based observations of gross primary productivity from the FLUXCOM project. Also, taking advantage of the relatively dense data networks over CONUS, we also evaluate the impact of the assimilation against in-situ measurements of soil moisture from the USCRN network (US Climate Reference Network) are used in the evaluation, together with river discharges from the United States Geophysical Survey (USGS) and the Global Runoff Data Centre (GRDC). Those data sets highlight the added value of assimilating satellite derived observations compared to an open-loop simulation (i.e. no assimilation). It is shown that LDAS-Monde has the ability not only to monitor land surface variables but also to forecast them, by providing improved initial conditions which impacts persist through time. LDAS-Monde reanalysis has a potential to be used to monitor extreme events like agricultural drought, also. Finally, limitations related to LDAS-Monde and current satellite-derived observations are exposed as well as several insights on how to use alternative datasets to analyze soil moisture and vegetation state.

The major global pressures of rapid urbanization and urban growth are compounded by climate impacts resulting in increased vulnerability for urban dwellers, with these vulnerabilities exacerbated during COVID-19. Much of this is concentrated in urban and peri-urban areas where urban development spreads into hazard-prone areas. Often this development is dominated by poor quality homes in informal settlements or slums with poor tenure security. Lessons from a current resilience-building project shows that the fit-for-purpose (FFP) approach to land administration can provide a solution to increase the number of households with security of tenure and improve resilience outcomes as informal settlements grow. This paper discusses the influence of FFP land administration on vulnerabilities to multiple shocks related to climate change and COVID-19. This paper proposes ways the growth of human settlements can be better managed through responsible governance of land tenure rights, and effective land-use planning to improve resilience to different shocks and stresses and provide adequate access to safe land and shelter. Land administration systems can support improved resilience to the multiple stressors of climate and pandemics through improving tenure security and enhancing land use planning controls. Climate change adaptation and risk management need to be better mainstreamed into two major elements of land governance: (i) securing and safeguarding of land rights, and (ii) planning and control of land-use.

Impact of land use and land cover (LULC) change on soil erosion is still imperfectly understood, especially in northeastern China (NEC). Based on the Revised Universal Loss Equation (RUSLE), the variability of soil erosion at different spatial scales following land use changes in1980, 1990, 2000, 2010, and 2017 was analyzed. The regionally spatial patterns of soil loss coincided with the topography, rainfall erosivity, soil erodibility, and use patterns, and around 45% soil loss came from arable land. Regionally, soil erosion rates increased from 1980 to 2010 and decreased from 2010 to 2017, ranging from 3.91 to 4.45 t ha-1 yr-1 with an average of 4.22 t ha-1 yr-1 in 1980-2017. The rates of soil erosion less than 1.41 t ha-1 yr-1 decreased from 1980 to 2010, and increased from 2010 to 2017, and opposite changing patterns occurred in higher erosion classes (i.e., above 5 t ha-1 yr-1). At a provincial scale, Liaoning Province experienced the highest soil erosion rate of 9.43 t ha-1 yr-1, followed by Jilin Province, the east Inner Mongolia, and Heilongjing Province. Arable land continuously increased at the expense of forest in the high-elevation and steep-slope areas from 1980 to 2010, and decreased from 2010 to 2017, resulting in increased areas with erosion rates higher than 7.05 t ha-1 yr-1. At a county scale, around 75% of the countries had soil erosion rate higher than its tolerance level. The county numbers with higher erosion rate increased in 1980-2010 and decreased in 2010- 2017, resulting from the sprawl and withdrawal of arable land. The results indicate that appropriate policies can control soil loss through limiting arable land sprawl in areas of unfavorable regions in the NEC.

The urban heat island (UHI) becomes more and more serious with the acceleration of urbanization. Many researchers have shown interest in studying the UHI by using remote sensing data. But these studies rarely examine the mountainous cities. The studies on UHI in mountainous cities often used empirical parameters to estimate the land surface temperature (LST), and lacked satellite-ground synchronous experiment to test the accuracy. This paper revised the parameters in mono-window algorithm used to retrieve the LST according to the characteristics of mountainous cities. This study examined the spatial and temporal patterns of the UHI intensity in Chongqing, a typical mountainous city, and its relationship with land cover from 2007 to 2011 based on the Landsat TM data and the improved method. The accuracy of the LST derivation increased by about 1°C compared to the traditional method. The high LST areas increased and extended from the downtown to suburban area each year, but the rate of change decreased. The UHI is dramatically impacted by the rivers. There is a good relationship between the urban sprawl and the UHI. The LST was reduced by about 1°C within a 300m distance from large urban fringe green spaces. The urban landscape parks had a strong effect relieving the UHI at a 100m distance. The LST was reduced by about 0.5°C. The study greatly improves the accuracy of LST derivation, and provides a reliable parameters for the UHI researched in mountainous city.

In Ethiopia, land degradation in the form of gully development and soil nutrient depletion is a very serious issue. The goal of this study is to determine how different types of land management practices and slope positions affect particular soil physico-chemical characteristics in the Agamssa watershed. Using systematic sampling techniques, soil samples were taken using a sampling quadrat (15 * 15 m) that was placed 50 m apart from one another. A total of 54 quadrats were planted at three slope positions: upper (>15%), middle (10–15%), and foot (3–10%) slope respectively. 18 composite soil samples were then. A two-way ANOVA was used to analyze the data, and the Least Significant Difference (LSD) test was used to separate the means at p ≤ 0.05. According to the study's findings, the value of most soil physical and chemical characteristics was higher in closed area than on open grazing land, as well as at foot slope position compared to middle and upper slope positions. The higher mean value (7.3 ppm) was recorded at the foot slope, while the lower mean value (4.9 ppm) was found at the upper slope position. The exchangeable cations such as Mg+2, K+, and Na+ were significantly (p≤ 0.01) affected by the main effect of land-use types. The higher mean values of Mg+2 (9.70 mq/100g), K+ (0.38 mq/100 g), and Na+ (0.035 mq/100 g) were found at area closure, whereas the lower mean values of Mg+2 (7.33 mq/100g), K+ (0.30 mq/100 g), and Na+ (0.027 mq/100g) were recorded at open grazing land. It was able to conclude this study that area closure enhances the physical and chemical qualities of soil and recovers woody plant species. Therefore, converting open grazing land into a closure area is advised.

The Sentinel-2 satellite mission offers high resolution multispectral time series image data, enabling the production of detailed land cover maps globally. At this scale, the trade-off between processing time and result quality is a central design decision. Currently, this machine learning task is usually performed using pixelwise classification methods. The radical shift of the computer vision field away from hand engineered image features and towards more automation by representation learning comes with many promises, including higher quality results and less engineering effort. In this paper we assess fully convolutional neural networks architectures as replacements for a Random Forest classifier in an operational context for the production of high resolution land cover maps with Sentinel-2 time series at the country scale. Our contributions include a framework for working with Sentinel-2 L2A time series image data, an adaptation of the U-Net model for dealing with sparse annotation data while maintaining high resolution output, and an analysis of those results in the context of operational production of land cover maps.

Change detection with heterogeneous remote sensing images (Hete-CD) plays an important role in practical applications, especially when homogenous remote sensing images are unavailable. However, bitemporal heterogeneous remote sensing images (HRSIs) cannot compare directly to measure change magnitude, and many deep learning methods require large amounts of samples to train the module. Moreover, labeling many samples for land cover change detection with HRSIs is time-consuming and labor-intensive. Therefore, acquiring satisfactory performance of Hete-CD remains a challenge for deep learning networks with very small training samples. In this study, we promote a novel deep-learning framework for Hete-CD to obtain satisfactory performance while the initial samples are very small. We initially design a multiscale network with select kernel-attention module to focus on capturing different change targets with various sizes and shapes. Then, a simple yet effective non-parametric sample-enhanced algorithm based on the Pearson correlation coeffi-cient is promoted to explore potential samples around each initial sample. Finally, the proposed network and sample-enhanced algorithm are fused into one iterative framework to improve the change detection performance with very small samples. Experimental results conducted on four pairs of actual HRSIs indicated that the proposed framework can achieve competitive accuracies with very small samples for initialization when compared with some state-of-the-art methods. For example, the improvement is approximately 3.38% and 1.99% when compared with the selected traditional methods and deep learning methods, respectively.

Abstract: The study focuses on how socio-economic and demographic indicators affect fertilization sustainability (excessive amount of fertilization). Principally we aim to examine the significance magnitude of the effects of three socio-demographic variables such as traditional way of fertilization, rental land farming, and farmers’ younger age on over-fertilization in Bangladesh and other developing countries. In 1960s, Bangladesh state authority launched a campaign ‘Grow more Food’ to feed huge numbers of population and thus the farmers are provided chemical fertilizers and pesticides at a subsidized low price. Farmers began to use huge amount of fertilizers for gaining high yields and continued it to present causing environmental woes a lot. We interview (face-to-face, focus group discussion, and phone interview) 210 Bangladesh farmers in 2016 by semi-structured questionnaire. Data has been analyzed using General Linear Model (GLM) in Univariate Analysis of Variance. The study found the effect of traditional way of fertilization on excessive amount of fertilization is strongly significant at 1% level. Apart from, rental land farming and farmers’ younger age have a significant influence on over- fertilization; though their significance level (5% and 10% respectively) is quasi-strong. Policy makers can be able to formulate fertilizer policy on the basis of these findings.

In recent years, land supply in Hong Kong has fallen sharply and fails to keep pace with the growth of population and number of households. Land shortage becomes urgent and dire. With the inadequate provision of residential land, housing supply is also adversely affected.Insufficient housing supply leads to surging property and rental price in the private market. According to the Rating and Valuation Department (RVD), the overall private domestic price index peaked in June 2017 at 336.1. Keen housing demand is also observed in the private rental market. RVD statistics showed that the domestic rental index also reached the peak at 183.6 in June 2017 and the vacancy rate of about 3.8% as at the end-2016, which is much lower than the average vacancy rate of 5% from 1996 to 2015 (Development Bureau, 2017).In addition, there is soaring housing demand in public housing. As at the end-December 2021, the average waiting time for general applicants was 5.7 years, which is nearly double of the Housing Authority’s target for providing the first flat offer to general applicants at around three years on average (Housing Authority, 2021). Identifying and securing sufficient land to meet both current and anticipated pressing housing demand becomes a key challenge of the government. In the light of this, the government has established a dedicated task force (Task Force on Land Supply) in September 2017 and appointed 30 professionals from different disciplines, such as planning, engineering, academia and think tank, to take a Marco-review on the land supply sources, look for feasible options as well as consider the pros and cons of various options. 18 land supply options were worked out for the public to make choices in the public engagement exercise. Among the 18 choices, the development area on the Periphery of Country Parks was regarded as one of the land supplies sources. This option does not only include the Hong Kong Housing Society’s studies on developing Two Pilot Areas on the Periphery of Tai Lam and Man On Shan Country Parks, but also include developing more areas on the periphery of Country Parks. The proposed option received overwhelming attention from the public and aroused debates in various perspectives. Its ecological value, recreational value, financial viability and even legitimacy were discussed. However, spatial analysis on the suitability of having residential development in Country Parks has not been conducted. Therefore, in this study, multi criteria GIS analysis is conducted to evaluate the geographic suitability of Hong Kong Country Parks for residential purpose with the consideration of various criteria.

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 movement direction of propagating convective systems originating from both inland and offshore over the north coast of West Java in Indonesia is determined primarily by the prevailing wind. However, the role of a land-sea contrast and a rugged topography over southern West Java is also expected to affect propagating convective systems by increasing land-sea breezes and enhancing upward motion. These hypotheses are tested using a weather prediction model incorporating convection (up to 3 km height) to simulate the heavy rainfall event during 26–29 January associated with the 2002 Jakarta flood. First, we addressed the influence of land-sea contrast and topography on the local circulation, particularly in the area surrounding Jakarta, by replacing the inland topography over western Indonesia (96°–119°E, 17°S–0°) with a water body with an altitude of 0 m. We then compared the results of model simulations with and without topography. The results show that the main role of the topography here is enhancing the upward motion and generating a deep convective cloud in response to the land-based convective system during 26–27 January 2002, which then continuously and rapidly propagates offshore due to the cold pool mechanism. Furthermore, the land-sea contrast has a significant role in increasing sea breeze under the rapidness of the landward propagation system during 28–29 January 2002, which was strengthened by the gravity waves and resulted in early morning convection over coastal regions.

In light of the critical and emerging global challenge posed by the increasing frequency and severity of heatwaves in recent decades, this study demonstrates a practical and robust workflow that bridges the gap in understanding how the effective integration of remote sensing data with ground-based observations can facilitate a comprehensive assessment of spatiotemporal heatwave patterns and trends in the central region of Thailand. This research transcends traditional methods, utilizing air temperature (Tair) and satellite-derived land surface temperature (LST) data from 1981 to 2019. Results exhibit that an analysis of Tair indicates increasing daytime heatwaves in peri-urban areas, with significant trends in heatwave number (HWN), heatwave frequency (HWF), and heatwave duration (HWD), heatwave amplitude (HWA) rises in urban settings while nighttime heatwaves significantly intensify in rural locales. Notably, LST trends reveal varied patterns, with peri-urban areas showing marked daytime increases in heatwave magnitude (HWM), HWA, and HWF. Correlation analysis (p=0.05) highlights strong daytime associations between Tair and LST in rural (HWN, HWF, HWD, r&gt;0.90) and peri-urban (HWM, HWA, r&gt;0.65) regions. Overall, this study advances approaches to the adaptable measurement and spatial-temporal pattern of heatwave-related risk areas, providing insights for decision-makers to develop sustainable practices and strategies for climate change adaptation.

Land cover and climate changes greatly influence hydrologic responses of a basin. However, the response vary from basin to basin depending on the nature and severity of the changes and basin characteristics. Moreover, the combined impacts of the changes affect hydrologic responses of a basin in an offsetting or synergistic manner. This study quantified the separate and combined impacts, and the relative contributions of land cover and climate changes on multiple hydrological regimes (i.e., surface runoff, streamflow, groundwater recharge evapotranspiration) for the Dhidhessa Subbasin. Land cover and climate change data were obtained from a recent study completed for the basin. Calibrated Soil and Water Analysis Tool (SWAT) was used to quantify the impacts. The result showed that SWAT model performed well for the Dhidhessa Subbasin in predicting the water balance components. Substantial land cover change as well as an increasing temperature and rainfall trends were reported in the river basin during the past three decades. In response to these changes, surface runoff, streamflow and actual evapotranspiration (AET) increased while groundwater recharge declined. Surface runoff was more sensitive to land cover than to climate changes whereas streamflow and AET were more sensitive to climate change than to land cover change. The combined impacts played offsetting effect on groundwater recharge and AET while inconsistent effects within study periods for other hydrologic responses. Overall, the predicted hydrologic responses will have negative impacts on agricultural production and water resources availability. Therefore, the implementation of integrated watershed management strategies such as soil and water conservation and afforestation could reverse the negative impacts.

Substantial reductions of the human and economic activities like road traffic for several months in 2020 were one of the consequences of the Coronavirus disease. This unprecedented change in urban metabolism also affected temperature and air pollutants. This study investigates the effects of the first COVID-19 lockdown over 43 cities in Europe. It determines the influence of anthropogenic activities on nitrogen dioxide (NO2), ozone (O3), and particulate matter (PM2.5) as well as on land surface temperature (LST), and the surface urban heat island intensity (SUHII), using satellite, modelled, and mobility data. Our findings show that there are great temporal and spatial differences and distinct patterns between the cities regarding the magnitude of change of the variables under study. In general, the results indicate a significant decrease in NO2 concentrations in most of the studied cities compared to the reference period 2015-2019. However, reductions could not be attributed to mobility changes like less traffic at transit stations, contrary to the results of previous studies. O3 levels increased during the first lockdown mainly influenced by the decreasing NO2 concentrations. The PM pattern was inconsistent over time and space. Similar as the NO2 results, no relation to the altered mobility behavior was found. No clear signal could be detected for LST and the SUHII, likely due to dominating meteorological influences. Therefore, single city case studies may be misleading.

Agricultural land fires have been linked to various and adverse impacts on ecosystems, food security and the agriculture sector. Understanding the patterns and drivers of agricultural land fires is essential for effective agricultural land fire management. The key objectives of this study were to (1) analyze the temporal and spatial patterns of agricultural land fires using satellite remote sensed data, (2) assess a range of environmental conditions that could drive the occurrence of agricultural land fires, (3) determine the best model for predicting agricultural land fires and (4) determine the relative contribution of each environmental condition variable on the best predictive model. We used both univariate and multivariate regressions for the fire prediction capability of four independent environmental conditions (fuel, weather, topographic and anthropogenic). Analysis of historical satellite data revealed that agricultural land fires were more frequent than forested land fires. Our analyses also revealed that fuel condition was the most important variable for predicting agricultural land fires followed by weather, topographic and anthropogenic conditions. This study provides a novel multivariate model for predicting agricultural land fires that harbors the potential to improve agricultural land fire management and reduce fire risk within the agricultural sector.

To ensure sustainable production and consumption in the agricultural sector, it is necessary to assess the contribution of each element of the nexus in the agricultural production chain. The aim of this study is to make a quantitative and qualitative analysis of the contributions of each element of the energy, water, waste and land nexus to agricultural products. A composite method approach combining aspects based on input-output model, Location Quotient (LQ) as well as competitive position is adopted. A database of nexus elements over a period from 2009 to 2018 is used for Cameroon, with ten regions considered. The results show proportions of around 0.42% energy, 67.88% water withdrawal, 11.91% harvested area, 97.81% waste for agricultural products. The geolocation of harvested areas shows that the largest portion is in the far north (1,373,829 ha) and the smallest in Adamawa (224,038 ha). Maximum production is in the central region (4,334,095 tons) and minimum in the Adamawa region (915,841 tons). The central, littoral and west regions are more representative of agricultural products. The analysis of the competitive position of agricultural products contributes to a better orientation of national strategies for agricultural sustainability according to existing potentials.

Climate change is expected to result in rising temperatures, leading to increased occurrences of extreme weather events like heat waves and cold spells. Urban planning responses are crucial for improving the adaptive capacity of cities and communities in dealing with significant temperature variations across seasons. This study aims to investigate the relationship between urban temperature fluctuations and urban morphology throughout the four seasons. Through quadrant and statistical analyses, the study identifies built-environment factors that contribute to moderate seasonal land surface temperatures (LST). The research focuses on Seoul, South Korea as a case study and calculates seasonal LST values at both the grid level (100m×100m) and street-block level, incorporating factors such as vegetation density, land use patterns, albedo, two- and three-dimensional building forms, and gravity indices for natural reserves. The quadrant analysis reveals spatial segregation between areas demonstrating high LST adaptability (cooler summers and warmer winters) and those displaying LST vulnerability (hotter summers and colder winters), with significant differences in vegetation and building forms. The spatial regression analysis demonstrates that higher vegetation density and proximity to water bodies play key roles in moderating LST, leading to cooler summers and warmer winters. Building characteristics have an invariant impact on LST across all seasons, where horizontal expansion contributes to higher LST, while vertical expansion reduces LST. These findings are consistent for both grid- and block-level analyses. The study emphasizes the flexible role of the natural environment in moderating temperatures.

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 Global Human Settlement Layer (GHSL) produces new global spatial information, evidence-based analytics and knowledge describing the human presence on the planet based mainly on two quantitative factors: i) the spatial distribution (density) of built-up structures and ii) the spatial distribution (density) of resident people. Both factors are observed in the long-term temporal domain and per uniform surface units in order to support trends and indicators for monitoring the implementation of international framework agreements. The GHSL uses various input data including global, multi-temporal archives of fine-scale satellite imagery, census data, and volunteered geographic information. In this paper, we present the characteristics of GHSL information to demonstrate how original frameworks of data and tools rooted on Earth Observation could support Sustainable Development Goals monitoring. In particular, we demonstrate the reach of gridded, open and free, local yet globally consistent, multi-temporal data in filling the data gap for the Sustainable Development Goal 11. Our experiments produce a global estimate for the Land Use Efficiency indicator (SDG 11.3.1) for 10,000 urban centers, calculating the ratio of land consumption to population growth rate that took place between 1990 and 2015. The results of our research demonstrate that there is a potential to lift SDG 11.3.1 from a tier 2 as GHSL provides a global baseline for the essential variables called by the SDG 11.3.1 metadata.

Urban sprawl is recognized as one of the most critical drivers disrupting the functional integrity of rural and natural landscapes. A systematic multiscale study has yet to be conducted to measure the Megalopolis of Mexico City's regional extent, comprising ca. 23 million inhabitants. This paper investigates land cover, land use, vegetation and soil changes at macro-regional, regional, local and site scales. Land cover/use data from the 1970s and 2018 were used as the primary input to analyze changes using remote sensing and geographical information systems. At the local scale, fieldwork data from the 1970s, 1990s, and 2020 served as the primary input and were subjected to multivariate analyses. At site scale, soils profiles and hydrological balance analyses at micro-basin level were conducted. Furthermore, social perception of changes was investigated among local residents/stakeholders using semi-structured interviews with four communities. Outcomes were validated to reach 85 percent accuracy in cartographic and 95 % statistical outputs. At the regional scale, land-use changes, especially human settlements, increased from about four to almost 40 % between 1970 and 2018 , with significant incursion into rural landscapes. At the local scale, analyses revealed significant decline in predominantly cold-humid vegetation types and conversion of agricultural fields into peri-urban landscapes. Site scale revealed the predominant importance of soils as the core landscape component for water infiltration and carbon sequestration. Nested multi-scale analyses revealed different disrupting processes which are hidden at one scale and evident at another. Poorly implemented, disconnected urban and environmental policies prevail as the main driving force, with implications for the weak local governance of rural communities. Regional integrated analyses are discussed in light of the relevance of urban resilience theory.

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 County of Avon in England was abolished in 1996 and replaced by four unitary planning authorities. Recently the authorities have been working closely to develop a West of England Joint Spatial Plan to facilitate better integration of policies on transport, housing, the environment etc. The Joint Spatial Plan team commissioned a multidisciplinary study to investigate whether the West of England has special characteristics of 'place' that engender shared interest and regional affinity, i.e. ‘sense of place’, to which emerging planning policies might positively respond. In this regard the present article is particularly focused on identifying whether the West of England has unique and unifying landscape characteristics, relating to topography, rural scenery, and flora and fauna, which combine with human experiences to distinguish the Region from adjoining areas. It is concluded that the West of England does indeed have real geographical integrity, being bound on all sides by attractive and prominent landscape features - the Mendip Hills, Cotswold Hills and Severn Estuary – that contribute to a sense of identity and belonging among its inhabitants. The alternating limestone ridges and broad clay vales that prevail across the Region’s heart, combined with low lying flatlands on the Region’s western fringe, provide further contrast with neighbouring regions, reinforcing the emotional bond to the landscape. Furthermore, it is suggested that the inhabitants of the West England show a particularly special environmental consciousness that sets them apart from neighbouring populations, complementing the influence of the physical environment in making the Region a special place to live.

Revealing the multidimensional value of cultivated land resources, improving calculation methods, and exploring their spatial distribution characteristics and influencing factors are crucial for the enhancement of natural resource accounting system and the protection of cultivated land resources. This study take Guangxi, China as an example and construct a comprehensive multidimensional value evaluation system for cultivated land resources at the county scale. The income capitalization method, substitution market method, and value equivalent correction method were applied to calculate the economic, social, and ecological values of cultivated land resources in 111 counties. Furthermore, spatial autocorrelation analysis was employed to study their distribution characteristics and influencing factors. The results show that: (1) The total value of cultivated land resources in Guangxi reach 19,729.2 billion yuan, and the average cultivated land value is 5.3511 million yuan/hm2, of which the ratio of economic, social and ecological values is about 6:1:2; (2) The value of cultivated land has a certain distribution pattern in the global space, and the average economic and social value show the spatial distribution patterns of "low in the west and high in the east" and "low in the northwest and high in the southeast" respectively."(3) There is a significant spatial clustering effect of all values of cultivated land resources in local space, with "high-high" and "low-low" clustering. (4) Economic development level is significantly negatively correlated with the ecological value of cultivated land, while has a significant positive correlation with social value; (5) Natural conditions, economic development and agricultural development approaches are the key factors affecting the value of cultivated land resources.

Land-cover classification that uses very-high-resolution (VHR) remote sensing images is a topic of considerable interest. Although many classification methods have been developed, there is still room for improvements in the accuracy and usability of classification systems. In this paper, a novel post-processing approach based on a dual-adaptive majority voting strategy (D-AMVS) is proposed for improving the performance of initial classification maps. D-AMVS defines a strategy for refining each label of a classified map that is obtained by different classification methods from the same original image and fusing the different refined classification maps to generate a final classification result. The proposed D-AMVS contains three main blocks. 1) An adaptive region is generated by extending gradually the region around a central pixel based on two predefined parameters (T1 and T2) in order to utilize the spatial feature of ground targets in a VHR image. 2) For each classified map, the label of the central pixel is refined according to the majority voting rule within the adaptive region. This is defined as adaptive majority voting (AMV). Each initial classified map is refined in this manner pixel by pixel. 3) Finally, the refined classified maps are used to generate a final classification map, and the label of the central pixel in the final classification map is determined by applying AMV again. Each entire classified map is scanned and refined pixel by pixel based on the proposed D-AMVS. The accuracies of the proposed D-AMVS approach are investigated through two remote sensing images with high spatial resolutions of 1.0 and 1.3 m, respectively. Compared with the classical majority voting method and a relatively new post-processing method called general post-classification framework, the proposed D-AMVS can achieve a land-cover classification map with less noise and higher classification accuracies.

The Southwest Alpine Canyon Area of China was one of the regions in the world that suffered from severe soil erosion. The focus of this research was to understand the response of land use change on soil loss by water erosion in alpine canyon on Southeast Tibet, we analyzed the characteristics of temporal and spatial dynamics of land use in the Niyang River Basin from 1990 to 2020 using GIS and statistical methods, assessed the spatial and temporal change characteristics of soil erosion in the Niyang River Basin using RUSLE model. For this purpose, the meteorological, soil, topographic, remote sensing data were collected. The results showed the area of cropland and construction land in the Niyang River Basin increased to 2.4 and 6.1 times the original from 1990 to 2020, respectively, the area of forest and water continued to decrease. Grassland, unused land and forest have always been the dominant land types in the Niyang River Basin. Tolerable soil erosion was distributed in the flat areas of the valley terraces in the main stream and its tributaries, slight soil erosion was mainly distributed in the flat areas at high altitudes, and moderate, severe, very severe and destructive soil erosion was sporadically distributed in the Niyang River Basin. The areas of tolerable and slight soil erosion exceeded 82% of the total area, The area of severe, very severe and destructive soil erosion was less than 6%, but the total soil loss amount of severe, very severe and destructive erosion was more than 27%. From 1990 to 2020, the soil erosion area decreased from 9219.34 km2 to 8,090.84 km2 in Niyang River Basin, more than 85% of the soil erosion class has not changed, and the change of total soil loss amount also shows a significant reduction trend as a whole. 99% of the total soil loss amount in the Niyang River basin is generated by grassland, forest and unused land. The conversion of various land use types to cropland will cause the enhancement in soil erosion grade. We recommend that the focus of soil erosion control in the Niyang River Basin is to protect grassland, forest and carry out scientific farming.

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.

We investigated the characteristics of surface wind speeds and temperatures predicted by the local data assimilation and prediction system (LDAPS) operated by the Korean Meteorological Administration. First, we classified automated weather stations (AWSs) into four categories [urban flat (Uf), rural flat (Rf), rural mountainous (Rm), and rural coastal (Rc) terrains] based on the surrounding land cover and topography, and selected 25 AWSs representing each category. Then we calculated the mean bias error of wind speed (WE) and temperature (TE) using AWS observations and LDAPS predictions for the 25 AWSs in each category for a period of 1 year (January–December 2015). We found that LDAPS overestimated wind speed (average WE = 1.26 m s–1) and underestimated temperature (average TE = –0.63°C) at Uf AWSs located on flat terrain in urban areas because it failed to reflect the drag and local heating caused by buildings. At Rf, located on flat terrain in rural areas, LDAPS showed the best performance in predicting surface wind speed and temperature (average WE = 0.42 m s–1, average TE = 0.12°C). In mountainous rural terrain (Rm), WE and TE were strongly correlated with differences between LDAPS and actual altitude. LDAPS underestimated (overestimated) wind speed (temperature) for LDAPS altitudes that were lower than actual altitude, and vice versa. In rural coastal terrain (Rc), LDAPS temperature predictions depended on whether the grid was on land or sea, whereas wind speed did not depend on grid location. LDAPS underestimated temperature at grid points on the sea, with smaller TE obtained for grid points on sea than on land.

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.

The integration of nature-based solutions into land use optimization has emerged as a focal point of current research, primarily due to its efficacy in mitigating flooding impacts and fostering sus-tainable development in both urban and rural areas. Utilizing Shanghai Pujiang Country Park as a case study, this paper conducts a simulation analysis to assess the flood mitigation effectiveness of three distinct land use patterns (Natural scenario, Scenario N; Complete urbanization scenario, Scenario U; Country Park Planning scenario, Scenario P) under five stormwater scenarios with re-turn periods of 2, 5, 10, 20, and 50 years. The findings reveal that Scenario P exhibits superior flood mitigation performance, particularly under stormwater scenarios with a return period of less than 50 years. Building upon these results, the paper proposes recommendations for optimizing land use with a focus on mitigating the impact of flooding. This study is crucial for comprehending the mechanisms involved in urban stormwater logging mitigation through land use methods and holds significance for decision-making in land use and planning at the micro level.

Land use/land cover (LULC) and climate changes are two main factors directly affecting hydrologic conditions. However, very few studies in Vietnam have investigated changes in hydrological process under the impact of climate and land use changes on a basin scale. The objective of this study is to assess the individual and combined impacts of land use and climate changes on hydrological processes for the Nam Rom river basin, Northwestern Viet Nam using Remote Sensing (RS) and Soil and Water Assessment Tools (SWAT) model. SWAT model was used for hydrological process simulation. Results indicated that SWAT proved to be a powerful tool in simulating the impacts of land use and climate change on catchment hydrology. The change in historical land use between 1992 and 2015 strongly contributed to increasing hydrological processes (ET, percolation, ground water, and water yield), whereas, climate change led to significant decrease of all hydrological components. The combination of land use and climate changes significantly reduced surface runoff (-16.9%), ground water (-5.7%), water yield (-9.2%), and sediment load (-4.9%). Overall climatic changes had more significant effect on hydrological components than land use changes in the Nam Rom river basin during the 1992–2015. Under impacts of projected land use and climate change scenarios in 2030 on hydrological process of the upper Nam Rom river basin indicate that ET and surface flow are more sensitive to the changes in land use and climate in the future. In conclusion, the findings of this study will basic knowledge of the effects of climate and land-use changes on the hydrology for future development of integrated land use and water management practices in Nam Rom river basin.

Accurate, detailed and recent Information about land cover/use is important and much more needed for different aspects of sustainable development and environmental management. As remote sensing datasets are becomes one of the most important and effective tools to generate such information, this study aimed to generating land cover map for sub area in Al-Ahasaa Oasis, Saudi Arabia, by using and classifying a subset of Landsat-ETM+ image of the selected study area, as bases and required input for future studies and researches. Different image preprocessing techniques in addition to a will-known and widely used classification method (i.e., Maximum Likelihood classifier) were applied. To be reliable with the final product, accuracy assessment was carried out with 89% agreement and accepted according to the applied method. Different land cover classes were found in the study area, which includes (Sand dunes, Water bodies, Sabakha, Bare soil, Urban, and Agricultural lands). The study also revealed that the dominant land cover class is sand dunes with approximately ± 70% in area. The study strongly indicated that the area has long been affected by sand movement. Finally, the study suggested that, further researches with more advanced methods rather than traditional methods are needed in the future to support the findings of this study, with high degree of accuracy.

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.

Mangrove vegetation plays a vital role in habitat and nursing ground for different organisms and prevents coastal erosion caused by wave and tide action. In recent years the mangrove vegetation in Chattogram coast, Bangladesh, has been interrupted by other infrastructural development, which has a destructing effect on the surrounding environment. Land surface temperature analysis of an area helps learn about different environmental conditions, weather, and climate. It is also essential to monitor the rising temperature and global warming, the biggest threat to humanity. NDBI and NDVI are the efficient process for monitoring vegetation and build up areas of a geographical location. This study focused on those analyses to understand the importance of mangrove vegetation in the Salimpur area and surrounding coastal areas of Chattogram by studying the relationship between NDVI and NDBI, NDVI and LST, NDBI, and LST. The outcome indicates that a higher vegetation index results in lower land surface temperature during different periods, negatively correlated. This study also found a strong positive correlation between buildup index (NDBI) and land surface temperature (LST), which means Land Surface temperature was found higher in Buildup areas. The vegetation areas are greatly affected by the buildup areas. The correlation between buildup areas and vegetation areas was strongly negative, which means an increase of NDBI decreases NDVI, and a decrease of NDBI increases NDVI.

A land cover map of two arctic catchments, nearby the Abisko Scientific Research Station, was obtained from a classification of a Sentinel-2 satellite image and a ground survey performed in July 2022. The two contiguous catchments, Miellajokka and Stordalen, are covered by various ecotypes, from boreal forest to alpine tundra and peatland. Two classification algorithms, support vector machine and random forest, were tested and gave very similar results. The percentage of correctly classified pixels was over 88% in both cases. The developed workflow relies solely on open source software and acquired ground observations. Space organization was directed by the altitude as demonstrated by the intersection of the land cover with the topography. Comparison between this new land cover map and previous ones based on data acquired between 2008 and 2011 shows some trends of vegetation cover evolution in response to climate change in the considered area. This land cover map is key input data for permafrost modeling, and hence for the quantification of climate change impacts in the studied area.

Analysis of the correlation between indices (Normalized Difference Vegetation Index, Normalized Difference Barren Index and Modified Normalized Difference Water Index) and land surface temperature is used to natural resources and environmental studies. This research aimed to analysis of Land Surface Temperature due to dynamics of Different Indices (NDVI, NDBaI and MNDWI) Using Remote Sensing Data in three selected districts (Gida Kiremu, Limu and Amuru), western Ethiopia. From thermal and multispectral bands of landsat imageries (Landsat TM of 1990, landsat ETM+ of 2003 and landsat OLI/TIRS of 2020) Land surface temperature and NDVI, NDBaI and MNDWI were calculated. Correlation analysis was used to indicate relationships between LST with NDVI, NDBaI and MNDWI. The study found that Land Surface Temperature was increased by 5⁰C from 1990 to 2020. Vegetation areas (NDVI) and Water bodies (MNDWI) have strong negative relationship with Land Surface Temperature (R²= 0.99, 0.95) whereas Barren land (NDBaI) has positive relationship with Land Surface Temperature (R²= 0.96). Finally, we recommend the decision makers and environmental analyst to emphasis the importance of vegetation cover and water body to minimize the potential impacts of land surface temperature.

To enhance pomegranate production on marginal gravelly lands, our study evaluated standardized planting techniques in an 8-year-old orchard. We employed trenching, wider pit excavation, pit digging, and auger digs with dimensions of 1 and 2 meters. Utilizing native soil from barren land, with or without spent wash, and mixing it with black soil up to 1 meter deep, we assessed growth parameters, leaf nutrients, and fruit yield. The trench and wider pit methods outperformed others, yielding greater above-ground biomass (>7.03 t tree-1), root biomass (2.5 t tree-1), and cross-sectional area (3.3 m² tree-1). Additionally, trench planting enhanced leaf phosphorus (0.28%) and potassium (1.8%) levels, fruit juice content (48.5%), total soluble solids (16.05°), and fruit yield (>9.3 t ha-1). The trench method also fostered longer roots at 90–150 cm radial distance and deeper roots at 40–60 cm depth. In summary, the trench and wider pit methods, combined with a soil mixture, are recommended for sustainable, high-quality fruit production in shallow gravelly terrains, thereby improving food security and the livelihoods of farmers in arid regions.