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Soil erosion and sediment yield in basins are influenced by a combination of land use/land cover changes and climatic factors. The existing empirical sediment yield index (SYI) model does not consider the spatiotemporal non-stationarity of the parameters and its application is limited in data-deficient basins. To address these issues, a novel framework was proposed to extend the application of the empirical SYI model, and to identify the spatiotemporal heterogeneity of the driving factors using the geographically and temporally weighted regression (GTWR) model, and it was demonstrated in the Dongjiang River basin, South China. The constructed multi-factor GTWR model explains 87% of the variation in SYI. Spatially, population density and urban land are the main driving factors of SYI, and there are significant spatial differences in their effects. Temporally, urban land is the most significant driving factor for SYI, and its effect increased over time. [ABSTRACT FROM AUTHOR]

This paper aims to evaluate the performance of a hydrological model by using satellite image classification (SIM) to extract land use (LU) information. Four methods, namely naive Bayes (NB), classification and regression trees (CART), support vector machine (SVM), and random forest (RF), are assessed for SIM using satellite images. CART demonstrated the highest overall accuracy (OA) of 0.996, followed by RF (OA = 0.994), SVM (OA = 0.797), and NB (OA = 0.543). The Soil and Water Assessment Tool (SWAT) model was employed in this study to construct and refine the hydrological model for simulating the streamflow in the basin. For this purpose, the ground-based layer was replaced by LU generated from the classification algorithms. Integrating the four classification approaches yielded a significant improvement in Nash-Sutcliffe efficiency of the SWAT model, increasing it from 0.37 to approximately 0.76. These findings highlight the effectiveness of using satellite image classification in enhancing the efficiency of hydrological models. [ABSTRACT FROM AUTHOR]

With the continuous increase of rapid urbanization and population growth, sustainable urban land-use planning is becoming a more complex and challenging task for urban planners and decision-makers. Multi-objective land-use allocation can be regarded as a complex spatial optimization problem that aims to achieve the possible trade-offs among multiple and conflicting objectives. This paper proposes an improved Non-dominated Sorting Biogeography-Based Optimization (NSBBO) algorithm for solving the multi-objective land-use allocation problem, in which maximum accessibility, maximum compactness, and maximum spatial integration were formulated as spatial objectives; and space syntax analysis was used to analyze the potential movement patterns in the new urban planning area of the city of Kigali, Rwanda. Efficient Non-dominated Sorting (ENS) algorithm and crossover operator were integrated into classical NSBBO to improve the quality of non-dominated solutions, and local search ability, and to accelerate the convergence speed of the algorithm. The results showed that the proposed NSBBO exhibited good optimal solutions with a high hypervolume index compared to the classical NSBBO. Furthermore, the proposed algorithm could generate optimal land use scenarios according to the preferred objectives, thus having the potential to support the decision-making of urban planners and stockholders in revising and updating the existing detailed master plan of land use. [ABSTRACT FROM AUTHOR]

The Paraguayan Chaco is increasingly known for the extreme rates of forest loss caused by the rapid expansion of cattle ranching and crop farming over the last few decades. Knowledge of its twentieth-century land-use history, however, remains limited. In this article, I address that gap by discussing land-use dynamics since the 1900s in the Pilcomayo River basin, a part of the Chaco that borders Argentina and Bolivia, and hosts a great diversity of actors and land uses. Using the concept of land-use regimes, I show that the area, once characterized by what can be called an Indigenous mixed-use regime, transitioned to a land-use regime dominated by livestock herding by Argentine Criollo settlers after the Chaco War (1932–35), and then again to one of large cattle ranches managed by absentee owners toward the end of the twentieth century. No land-use regime ever completely dominated the area, however, and I use this fact as a starting point to then discuss how using the concept of land regimes can help direct attention to the coexistence of regimes in space and to their relationships in a way that helps refine our understanding of land-use transitions. [ABSTRACT FROM AUTHOR]

Ethiopia, marked by diverse geography and rapid land use/land cover (LULC) changes, grapples with formidable water resource management challenges. Understanding the hydrological response to these changes is paramount for sustainability. This review paper provides an overview of studies that investigated the hydrological impacts of LULC changes in Ethiopian basins. The review discusses methodologies, key findings, implications for sustainable land and water resource management, research gaps, and future directions. Emphasizing results from diverse studies that utilized hydrological and geospatial modelling, LULC significantly affects surface runoff, streamflow patterns, and groundwater recharge. The observed consequences are increased surface runoff, modified streamflow timing, and reduced groundwater recharge. The review underscores the urgency for integrated land and water management strategies to alleviate adverse effects. Future research priorities include basin-specific studies, long-term monitoring, integrated modelling, consideration of socio-economic factors, and incorporating climate change scenarios to enhance understanding and guide sustainable water resource management in Ethiopian basins. [ABSTRACT FROM AUTHOR]

Rapid urbanization currently poses a threat to cropland areas. Therefore, exploring the pattern of change in cropland areas and its driving mechanism is of great significance in safeguarding regional economic development and food security. In this study, data regarding cropland in the Changsha-Zhuzhou-Xiangtan city group (CZTCG) from 2000 to 2020 were collected, and dynamic changes in cropland in the past 20 years were analyzed. Based on this, the mechanisms that drive cropland change were explored in the context of multiple dimensions. Furthermore, an Inertial Development Scenario and a Cropland Priority Scenario were designed to simulate land use/land cover (LULC) changes in the CZTCG in 2025 and 2035, and, in particular, to analyze the characteristics of future spatiotemporal changes of cropland. The results demonstrated that the cropland area in the CZTCG in the past 20 years has shown a two-stage trend of increasing (2000-2015, increase of 8.25%) and decreasing (2015-2020, decrease of 2.91%), and the main reasons for cropland loss in the whole process of change were forest and building, with serious loss of cropland area in Changsha County and Wangcheng District. Between 2000 and 2020, socio-economic factors (GDP, total agricultural output), topography (elevation, slope), and climate change (average annual temperature, annual precipitation) were highly correlated with changes in cropland area, exhibiting significant temporal and regional variability. The simulation results indicate that until 2035, the Cropland Priority Scenario shows a significant increase in the area of cropland in the study area compared to the Inertial Development Scenario. Consequently, the implementation of a strategy that prioritizes cropland can effectively protect it, while helping to promote ecological development and regional socio-economic development. [ABSTRACT FROM AUTHOR]

Human activities, including agricultural expansion, urbanization, and industrial advancement, have led to land use/cover change (LULCC). These changes have had negative consequences, such as the loss of species and the degradation of forest areas. The Yayo Coffee Forest Biosphere Reserve (YCFBR) is undergoing changes due to forest fires and encroachment from coffee plantations, which are predicted to increase in the future. The objective of this study was to simulate the dynamics of LULCC and its impact on habitat quality in the area over the next three decades. The study used classified land cover (LC) maps of 1992, 2022, and 2052 (predicted), as well as factor and constraint maps of the area. In addition, household surveys, key informant interviews (KII), and focus group discussions (FGD) were conducted to understand the factors influencing changes in habitat quality. Habitat quality was simulated under three different future scenarios (Business as Usual; S1), conservation scenario (S2), and development scenario (S3) using CA-Markov, Future Land Use Simulation (FLUS), and Integrated Valuation of Environmental Services Tradeoffs (InVEST) models. The result showed a 28% increase in open forest and a 35% increase in agricultural area under S1, with a minimal increase in built-up area. The mediumlevel habitat quality increased from 11.3% in 1992 to 27.8% in 2052 S3. The highest average haitat quality value was 0.62 in S2, while the lowest was 0.51 in S3. If S3 is the case, this value is expected to fall below 40%, indicating the lowest possible level of habitat quality in the future. The model also predicts a 7% increase in high forest areas in S2, indicating the possibility of an alternative path to save high forest loss in the area. The main causes of habitat quality deterioration include population growth, agricultural land expansion, a lack of diverse incomes, land tenure issues, and settlement expansion. Based on the findings, S2 appears to be the best future scenario for maintaining habitat quality. This study provides useful information that will help planners and decision-makers effectively prepare future conservation strategies. [ABSTRACT FROM AUTHOR]

In the karst area, the epikarst increases the infiltration of rainfall and the depressions and conduits make water exchange frequently between surface rivers and karst aquifers. To improve simulation accuracy, we proposed the Soil and Water Assessment Tool-Genetic Algorithm-Back Propagation (SWAT-GA-BP) model. Also, the SWAT-tank model was created to elaborate the runoff processes in different karst systems. Furthermore, we designed three scenarios to study the influence of land use changes on runoff. The Zuo River Basin was selected as a case study. Compared to SWAT, the determination coefficient of the SWAT-GA-BP increased by 4.8% and the Nash-Sutcliffe efficiency increased by 4.9%; the rapid flow accounted for more than 50% of the total runoff, and the slow flow for less than 10%; the contribution of the land use changes was 10.80% from 2008 to 2012 and 5.57% from 2013 to 2017. Therefore, the effect of land use change on runoff should not be ignored. [ABSTRACT FROM AUTHOR]

The establishment of refugee settlements has caused profound segmented impacts on the coverage of land use/cover types. Few studies have computed the spatial drivers of land use/cover changes in Refugee prone areas. This study explored how refugee settlements induced geo-changes in land use/cover in Bidi-Bidi refugee settlement in Uganda. Sentinel-2B images (2015, 2017 and 2020) were used to assess and predict (2030 and 2040) the spatial areal extent of land use/cover changes. The images were classified using Supervised algorithm (Maximum-likelihood) and used CA-Markov model to generate transitions into the future. A Binary Logistic regression was used to compute the spatial drivers of geo-changes. Our results reveal that the settlements triggered more geo-changes in built-up (0.6%), refugee settlements (4.1%), and subsistence farmlands (7.0%) at the expense of woodlands (−0.3%), wetlands (−2.9%), and grasslands (−8.3%). The same trajectory will also be expected between 2030 and 2040. The most critical spatial drivers of these changes are as follows: population growth, increased temperatures, precipitation variation, distance to water sources, distance to roads, distance to police posts, and distance to trading centres. To reduce the acceleration of changes in land use/cover types, this study agitates for equal spatial establishment of woodlots, promotion of alternative sources of energy and livelihoods, and settlement construction materials. [ABSTRACT FROM AUTHOR]

Land-use Suitability Analysis, which aims to identify the suitability of a given area for a particular use by using a certain number of criteria, is a domain that has received a lot of attention from researchers during the last 20 years and most of the works that have been proposed rely on the use of multi-criteria methods which are based on a complete aggregation of alternatives such as Weighted Linear Combination (WLC). The outranking methods, which are multi-criteria methods that rely on a partial aggregation of alternatives, have rarely been used. In the context of Land-use Suitability Analysis, outranking methods quickly reach their computational limits because they require performing comparisons between each pair of pixels. To reduce the initial number of alternatives, we propose to proceed to the regionalization of the study area by grouping neighbouring pixels that have similar properties in homogeneous zones. We then use PROMETHEE II (Preference Ranking Organization Method for Enrichment of Evaluations), an outranking method whose objective is to rank a set of alternatives from the best to the worst. A study for the choice of a landfill site was carried out using our approach and the obtained results were compared with those of WLC. [ABSTRACT FROM AUTHOR]

The potential of citizens as a source of geographical information has been recognized for many years. Such activity has grown recently due to the proliferation of inexpensive location aware devices and an ability to share data over the internet. Recently, a series of major projects, often cast as citizen observatories, have helped explore and develop this potential for a wide range of applications. Here, some of the experiences and learnings gained from part of one such project, which aimed to further the role of citizen science within Earth observation and help address environmental challenges, LandSense, are shared. The key focus is on quality assurance of citizen generated data on land use and land cover especially to support analyses of remotely sensed data and products. Particular focus is directed to quality assurance checks on photographic image quality, privacy, polygon overlap, positional accuracy and offset, contributor agreement, and categorical accuracy. The discussion aims to provide good practice advice to aid future studies and help fulfil the full potential of citizens as a source of volunteered geographical information (VGI). [ABSTRACT FROM AUTHOR]

Hillside urbanization currently provides the most economical solution for urban expansion. However, limited attention was paid to the characteristics, processes, and patterns of gradient expansion of construction land (GEC) in mountainous regions and its impact on landscape fragmentation. This study suggests an approach to identify GEC in mountainous regions and quantify its spatial impact on the fragmentation of cultivated land and ecological land. The results are as follows: (1) GEC can be categorized as 'unidirectional', 'bidirectional', or 'multidirectional' expansion, influenced by the proportion of topography in different directions of the cities. The magnitude of expansion is correlated with the city's economic level. (2) GEC leads to an increasing trend of landscape fragmentation, with nearly a three-fold increase in arable land fragmentation and a two-fold increase in ecological land fragmentation within the focus areas over 20 years. (3) The impact of GEC on the fragmentation of cultivated and ecological land diminishes with distance, primarily influencing within 3 km. The results of this study provide a methodological reference for identifying key areas and characteristics of GEC, and serve as a theoretical basis for reducing landscape ecological risks in the process of mountainous urban development and promoting sustainable development. [ABSTRACT FROM AUTHOR]

Coastal resorts, whose dominant economic activities are those of providing an array of recreational services to tourists, reflect this specialization in their land-use patterns. Therefore, the business districts in coastal resorts have a unique morphology, landscape, and land use. However, the literature reflects that there is limited attention to the tourism business districts (TBDs) that have developed in coastal resorts. Moreover, few empirical studies have been conducted in developing countries, such as Thailand, China, and Turkey, as well as developed ones such as United States, Canada, and Italy. This study discusses the TBDs located in Turkey's coastal resorts in terms of location, form, and function. The findings are presented statistically, and detailed maps are presented to explain the TBDs from a geographical and practical perspective. In this study, ArcGIS 10.5 software has been used to perform spatial analysis of the data. The main findings include that Turkish TBDs have similar characteristics in terms of location, form, and function compared to other coastal resorts worldwide. Therefore, it is possible to say that these similar features constitute a model in terms of land use. In addition, the statistical findings of the study are largely similar to those found in the literature. [ABSTRACT FROM AUTHOR]

The availability of spatial data in grids allows to enrich the statistics ranked by census units, being of great interest for regional analysis and territorial planning. The objective of this work is the elaboration of cartography, independent of administrative boundaries, which collects demographic data, accessibility and major land uses in cells of one square kilometre. Applying a methodology that has allowed the assignment of a category related to the predominant territorial model in each grid, the main result is a synthesis map of the rural-urban gradient that can be recognised in the province of Jaén, showing the contrasts and imbalances derived from the physiographic conditions and the recent territorial changes. [ABSTRACT FROM AUTHOR]

Land consumption is a major environmental problem. In relation to it, over the past decades different studies have raised awareness of the importance of a less visible but equally damaging process: growing 'Anthropogenic Landscape Fragmentation'. The objective of this study is to offer a global portrait of this phenomenon through a map. Following a methodology developed in previous studies, this research builds on the calculation of a widely used index for measuring Anthropogenic Landscape Fragmentation, the effective mesh size (meff). This index considers existing human settlements, as well as global railway and road networks. The maps illustrate the heterogeneity in the distribution of Anthropogenic Landscape Fragmentation worldwide. In addition, the study calculates average fragmentation values at the national level and explores the correlation of these values with other variables such as population density or the Human Development Index, revealing a positive trend but with a weak correlation. [ABSTRACT FROM AUTHOR]

In the context of global warming and the increasing water shortage in dry areas, it is necessary to find a sustainable pathway for utilization of land resources (ULR) to solve these problems. For this purpose, using socioeconomic and environmental indicators from 2006 to 2018 and taking the Tarim Basin, China as an example, this study employed an integrated approach composed of the indicator evaluation system (IES) and the System Dynamics (SD) model to evaluate the possibility of sustainable ULR in the basin. During the simulation, three scenarios namely traditional development (TD), economic priority (EP) and harmonious development (HD) were designed, and different thresholds were set for each indicator of potential ULR in each sub-region to predict their future development status. The IES was established to derive the sustainable utilization degree (SUD) of ULR. The results show that the SUD in Tarim in 2030 is likely be 0.60 (TD), 0.62 (EP) and 0.68 (HD), indicating that only in HD scenario is it possible to find pathway to solve water scarcity problem and achieve sustainable ULR. This study provides a supportive idea for decision-making on sustainable ULR in Tarim and also an approach for similar sustainability assessment in other dry areas. [ABSTRACT FROM AUTHOR]

Cover crops (CCs) are a diverse group of species that are sown simultaneously or after the cash crop either as monocrops or mixtures. A farmer survey with 1130 respondents was carried out with the aim to gain knowledge on CC species used by Finnish farmers, to understand how experienced farmers were with them, how experiences varied depending on farm and farmer characteristics, and to identify target groups for dissemination and policy measures. The studied groups were conventional and organic farms that had selected CCs as a registered measure in 2020 to receive agricultural payments. Our results show that farmers were experienced with a high number of CCs despite the high-latitude conditions. Only 11% of respondents had plenty of experience with CCs as mixtures. Farmers tended to favour CCs that were familiar to them as cash crops. Organic producers were usually more experienced than conventional farmers. Education increased curiosity towards CCs. Farmers who used more diverse cash crops tended to use more diverse CCs. In conclusion, especially farmers who have cereal-based systems and rotations should be a core group for knowledge sharing to support transition towards increased use of CCs and higher diversity of CC species in the future. [ABSTRACT FROM AUTHOR]

Partitioning the contributions of climate, economic growth, and policy to a region's carbon flows is an important process for the Chinese government seeking to optimize their regional development policies to achieve carbon neutrality by 2060. A combination of the carbon emission analysis and human appropriation of net primary production (HANPP) framework was applied to a village in the Lhasa river valley, Tibet, to quantify the contributions of these different factors to carbon flows and neutrality. From 2010 to 2019, the average annual net sequestration of CO2 was 374.9 g CO2 m−2 a−1. Changes in climate conditions and the regional policy of Grassland Ecological Protection Subsidy and Reward increased carbon sequestrations by 409.5 and 25.7 g CO2 m−2 a−1, respectively. Socioeconomic development, policies for reducing poverty, and promotion of forage production led to the increase in CO2 emissions by 103.5, 88.8, and 4.3 g CO2 m−2 a−1, respectively. The cumulative CO2 emissions (including HANPP) caused by land use were 298.92 Tg CO2 (2479.63 g CO2 m−2; 1 Tg = 1012 g), while the cumulative CO2 emissions due to energy use were only 11.22 Tg CO2 (93.07 g CO2 m−2), equal to 3.75% of the CO2 emissions driven by land use. Livestock grazing and cropland cultivation were the two main land use factors affecting the carbon balance. We argue that unhooking economic growth from traditional nomadic animal husbandry and lifestyles through policy optimizations would highly contribute the carbon neutrality in Tibet. [ABSTRACT FROM AUTHOR]

Land use changes affect soil and biomass carbon sequestration potential of the agroecosystems of most Sub-Sahara Africa facing rising temperatures due to global climate change. One such ecosystem is the Owabi reservoir catchment in Ghana, which has undergone extensive changes in land use through urbanization. Our study aimed to determine the impact of the spatial and temporal variability of the different land uses on soil and biomass carbon storage in the Owabi catchment. Land use/cover maps were elaborated using SPOT satellite images of 30 × 30-m resolution and Erdas Imagine and ArcGIS Pro softwares. Soil and vegetation were sampled along three transects in the Y plane in early 2014. Nested plot design and temporary sample plots of 50 × 50 m were demarcated within a 1 ha plot in each of the land uses. Trees, herbs and litter were sampled to assess aboveground carbon, and soil samples were taken at 0–15 cm and 15–30 cm depth. Belowground (root) biomass was calculated using the root:shoot ratio. Seven (7) land use types – dense forest, sparse forest, grassland, cropland, wetland, settlement, and excavated land – were identified and differences in carbon stocks were assessed. Soil carbon stock (0–30 cm) ranged from 51.80 Mg/ha in dense forest to 7.00 Mg/ha in excavated land. Our study showed that the conversion of forest lands to other land uses through excavation resulted in about 30-folds loss in carbon and also a major loss of carbon in the catchment from c. 1.4 × 106 Mg C in 1990 to 0.55 × 106 Mg C in 2014. Enhancing forests or growing trees to sequester carbon seems to be the optimum choice among the seven land uses if the introduction of payment for environmental services options is considered. [ABSTRACT FROM AUTHOR]

Agrarian change affects the supply and demand of ecosystem services (ES) by reducing the extent of natural ecosystems. Agricultural intensification can lead to changes in land covers and livelihood opportunities and it remains unclear how such changes align or misalign with the desires of local communities. Using participatry mapping, we assessed ES uses and desires of Indigenous people and local communities provided by different land cover types along a gradient of agricultural intensification (forest subsistence, agroforestry mosaic, and monoculture and market-dependence) in West Kalimantan, Indonesia. We found that mapped ES use diversity was highest in the forest-dependent zone and lowest near monoculture agricultural systems. The expressed ES uses and desires varied greatly among land cover types amidst loss of old-growth forest and greater reliance on secondary forest and shrub land. The spatial analysis showed that high priority areas of ES use was related to access in the landscape, demonstrating the importance of attending to place-based social values in ES assessments. From this study, we call for a people-centric spatial modelling approach to address the divergence of social and cultural ES values associated with land covers under different intensification contexts. Participatory mapping clarifies the ES desires of local communities, which state policy often fails to address. We recommend a place specific management strategy to reduce ES trade-offs of specific land use practices, which are currently apparent with agrarian change in Indonesia and relevant for other tropical developing countries. [ABSTRACT FROM AUTHOR]

Based on commercial passenger-carrying airships like LZ129 or R100, a hypothetical electric rigid framed airship including a solar cell covered surface and a lithium-ion battery is designed. The size of the battery and the coverage with solar cells are selected such that long-haul flights are possible. To simulate flight times, weather data from 2019 and time-dependent solar irradiation are used. Travel route and battery use are optimised in order to reduce flight times. For a mid-range and long-haul use case for passenger or freight transport, travel times have been calculated. Building on these results, analysis of CO2 emissions, land-use, and operating costs are carried out to reveal that depending on the use case, CO2 emissions of solar-powered airships could be as low as 1% to 5% of the emissions of a conventional aircraft at an estimated energy consumption in USD per km of 0.5% to 2.5%. [ABSTRACT FROM AUTHOR]

This paper examined the dynamics of urban land use and land cover change, and their implications for livelihoods in peri-urban Tamale, Ghana. The study employed household data and Landsat Thematic Mapper (TM) for 1986, Enhanced Thematic Mapper Plus (ETM +) for 2004 and Landsat 8 Operationalised Landsat Imager/Thermal Infrared Sensor (OLIS/TIRS) for 2019. The findings show that the urban expansion process witnessed a transition from agricultural livelihood to a more complex and monetised urban economy, which presented mixed impacts on the livelihoods of the peri-urban households. We argued that the horizontal expansion of urban areas into prime agricultural lands could be halted by promoting vertical development in the form of multi-storey buildings rather than the horizontal multiplication of individual housing units. Supporting the peri-urban households to diversify their livelihood portfolios by venturing into beekeeping, poultry farming, and livestock keeping, which do not require large tracts of land is recommended. [ABSTRACT FROM AUTHOR]

The ecological civilisation has become a consensus on society development in China, and is an inevitable requirement for building a community with a shared future for mankind. Exploring the changes in land use in mountainous counties is practically required to achieve a sustainable economy and society and build a beautiful China. Aiming at the contradiction between the expansion of urban construction land and the ecological environment, the research takes a typical mountainous city, Qianshan city, as an example. Under the three scenarios guided by the two development concepts: protect cultivated land priority and protect ecological priority, the research applies the SD model to predict the demand for land use, the EL-CA model to simulate the spatial evolution of land use, and the gravity centre model to analyse the city's future development. Results show that: (1) In the scenario of protect cultivated land priority, ecological land is severely fragmented, and part of it is converted into cultivated land; in the scenario of protect ecological land priority, the ecological land nearby built-up area is largely encroached, and the others may be spottily encroached by construction land; (2) In different development scenarios, cities will mainly expand to the south in the future, and the northern part of the city will generally undertake the protection of ecological and cultivated land. The research simulates the evolution process of future land use in mountainous cities; it provides a theoretical reference for spatial planning for national land and the implementation of green development and technical guidance for urban expansion and ecological coordination. [ABSTRACT FROM AUTHOR]

Hydrodynamic model outputs are used in urban flood risk modelling, flood alert systems, and Monte Carlo hazard assessment. This study tackles an under-explored challenge wherein regular updates to the spatial characteristics of the watershed -- due to factors such as changing land use -- alter the watershed's response to rainfall forcing, thus rendering existing model outputs obsolete. Because state-of-the-art hydrodynamic models are computationally expensive, frequently re-running simulations can be costly. Modularization addresses this problem by requiring re-computation only for a limited domain affected by the land use changes. This article introduces a novel approach by modularizing the 2D domain into independent sub-domains before ('discrete') and after ('abstract') the numerical computations. Using the Hydrologic Engineering Center River Analysis System (HEC-RAS) 2D model of a large urban watershed in Houston as an illustrative and generalizable testbed, we show that both the discrete and abstract modularization closely approximates the results from rerunning the entire model. The computational cost of modularization scales linearly with model size for memory requirements as storing the solution on the interior boundaries (discrete) or throughout the domain (abstract) are necessary. This trade-off of memory for computation may facilitate advances in surrogate modelling or Monte Carlo flood risk assessment. [ABSTRACT FROM AUTHOR]

The impact of land use on water quality is spatially scale-dependent. Exploring the relationship between land use pattern and river water quality provides an important basis for water quality safety and land planning. This study explores the effect of land use patterns on surface water quality using land use data and water quality data of 16 sampling points in the middle reach of the Huai River. It investigates the water quality status of the middle reach of the Huai River and the relationship between land use patterns and water quality indices at 100, 500, and 1000 m and watershed scales utilising Spearman correlation, redundancy analysis (RDA), and multiple linear regression analysis. Multiple linear regression analysis showed that the water pollutants in the middle reach of the Huai River are mainly total nitrogen (TN) and total phosphorus (TP). Redundancy analysis (RDA) indicated that the impact of land use patterns on water quality is significant on watershed scales. Spearman correlation indicated that water quality and land use showed significant correlation differences, the building land was positively correlated with TP, TN and NH3-N, the cultivated land was positively correlated with TN, and the grassland was negatively correlated with TP and NH3-N. This studies have revealed that building land acts as a 'source' of pollutants, grassland purifies the load of TP and NH3-N, and forest land has the effect of interception and deposition of pollutants. The results can provide important information for land use planning and water quality protection measures at multiple spatial scales. [ABSTRACT FROM AUTHOR]

Land Use and Land Cover Changes (LULC) are some of the worldwide factors that have the most impact on city growth. The aim of this study could be a quantification of the land use/land cover dynamic over three decades in Hawassa City, Ethiopia. This study used multi-spectral satellite images of the years 1990 and 2020. The six category classifications within the study area were agriculture, bare land, built-up, bushland, forest, and water body. The data for the study was acquired from a satellite image of Landsat 5TM 1990, 2000, and 2010 and Landsat 8 OLI and SWIR 2020. Packages like QGIS version 3.2, ArcGIS 10.3, ENVI 4.2, and ERDAS Imagine 2013 were accustomed to performing image classification. From this finding, it is clear that the study space is underneath serious land use conversion of bare land to built-up space and bush land to agricultural. The general LULCC between the years 1990 and 2020, satellite results show that between 1990 and 2020, the quantify of built-up land increased from 12.76% to 16.85% of the study area as bare land and bush decreased from 4.77% to 2.48% and 14.29% to 10.16%, respectively, from the entire study. [ABSTRACT FROM AUTHOR]

A mature developed urban area like London has various policy tools to trigger economic development and leverage poverty. The scale of economic inequality in London has called for more effective policy tools to leverage poverty and close the gaps of economic inequality. Opportunity Areas is one of the tools in urban regeneration to alleviate poverty and develop communities. After over a decade of the policy rollout we have little knowledge how effective this type of policy tool is. The project investigates how effective opportunity areas for economic growth and societal development in London. The key economic indicators including unemployment rate and house price were assessed at MSOA/ward levels in London to understand their spatial variation through GIS mapping. Subsequently, socio-economic factors of commercial land use, culture infrastructure and public transport accessibility were discussed and selected to explore whether they have impacts on the difference of economic performance within opportunity areas. The spatial impacts of these factors among wards/MSOA were evaluated by Geographically Weighted Regression. The research discussed these factors' variations in Lee Valley, Park Royal and Croydon. Finally, this paper argued that local geographical context has limitations for small area growth corresponding to general policy and strategic management plan. [ABSTRACT FROM AUTHOR]

Using a participatory Bayesian network-based land-use decision model, we simulate future land-use patterns under various scenarios, including changes in vanilla and clove market prices as well as changes in irrigation water availability and potential harvest failures. Findings indicate that specifically the vanilla value chain (compared to the clove value chain) has a major influence on farmers income vulnerability. Abandoning vanilla cultivation may lead to poverty once income from vanilla reaches a certain threshold. By comparing farmer's income gains from cash crop production with costs for buying rice to cover basic needs, we show that while focusing on cash crop production is more lucrative, it is, however, highly risky with regard to climate change, price volatility and possible crop thefts. Such lock-in-effects in cash crops, like the vanilla ones in northeastern Madagascar, are essential to be considered, when designing policies for a more sustainable development of resource-rich but poverty-prone regions. [ABSTRACT FROM AUTHOR]

Against the backdrop of urban sustainable development around the world, how to coordinate both economic growth and ecological benefits in urban space becomes an important problem. Therefore, this study simulated and predicted the spatiotemporal changes in urban economy and ecosystem service value (E.S.V.) equivalent ratio under the current policies by 2030, and analysed how adjusting planning policies influences economy and ecology. This process was based on the future land use simulation (F.L.U.S.) model of coupled neural network, and on methods assessing the spatial changes in ecosystem services and land economy. This study aims to analyse urban land economy and E.S.V., and assess how China's land spatial planning guides and promotes high-quality urban economic development. Results show that artificial intelligence (A.I.) simulation can forecast the results of spatial planning policies of national lands, to make policy-making more forward-looking. The guidance of planning policies on urban expansion accelerates the increase in economic value of urban residential and commercial lands, thereby promoting the economic growth. However, adjusted planning policies may lead to ecological destruction. So, this study provides model verifications and path guidance to realise coordinated sustainable development between economy and ecology, serving as an important reference to formulating proper policies for urban development. [ABSTRACT FROM AUTHOR]

Land cover classification (LCC) refers to the task of classifying each pixel in satellite/aerial imagery by predicting a label carrying information about its nature. Despite the importance of having transparent, symbolic decision models, in the recent literature, LCC has been mainly approached with black-box functional models, that are able to leverage the spatial dimensions within the data. In this article, we argue that standard symbolic decision models can be extended to perform a form of spatial reasoning that is adequate for LCC. We propose a generalization of a classical decision tree learning model, based on replacing propositional logic with a modal spatial logic, and provide a CART-like learning algorithm for it. We evaluate its performance at five different LCC tasks, showing that this technique leads to classification models whose performances are superior to those of their propositional counterpart, and at least comparable with those of non-symbolic ones. Ultimately, we show that spatial decision trees and random forests are able to extract complex, but interpretable spatial patterns. [ABSTRACT FROM AUTHOR]

Land use and Land cover change (LULCC) is a major global problem, and projecting change is critical for policy decision-making. Understanding LULCCs at the watershed level is essential for transboundary river basin management. The present study aims to analyse the past and future LULCCs in two significant watersheds of the Senegal River basin (SRB) in West Africa: Bafing and Faleme. This study used Landsat images from 1986, 2006 and 2020 and the Random Forest classification method to analyze past LULCCs in these two watersheds. The results revealed: In Bafing, vegetation, settlement, agricultural areas and water increased, while the bareground decreased significantly between 1986-2020. In Faleme, two periods have different trends. Between 1986-2006, vegetation, settlement, agricultural areas and water increased, while bareground decreased. Between 2006-2020, settlement increased, while vegetation, agricultural areas, water and bareground decreased. To predict LULCCs in 2050 under business-as-usual assumptions, the Multilayer Perceptron and Marcov Chain model (MLP-MC) was used. The MLP-MC shows better results on Bafing than on Faleme but without questioning its application on the two watersheds. Bafing has seen a trend towards "more people, more trees", while Faleme has seen a trend towards "more people, more deforestation". These results contribute to develop appropriate land management policies and strategies to achieve or to maintain sustainable development in the SRB. [ABSTRACT FROM AUTHOR]

The rapid decline of Lake Urmia in northwest Iran, caused by both human and natural factors, motivated our utilization of the Soil and Water Assessment Tool (SWAT) model. The objective was to identify the most effective reservoir outflow simulation scheme and assess the influence of land use changes in the Zarrineh River basin on Lake Urmia. The target release approach for controlled reservoirs and the measured outflow schemes were evaluated. Despite improved calibration results in the latter method, the former demonstrated superior performance during the validation phase. Three land use scenarios – a model with the 2001 land use map, a model with the 2008 land use map, and a model with a gradually updating land use map – were considered. The gradually updating land use scenario exhibited a significant enhancement in validation results; it showed a 250% increase in water yield, while evapotranspiration declined by 3%. [ABSTRACT FROM AUTHOR]

CORINE Land Cover is one of the most relevant Land Use Cover (LUC) databases in Europe because of its degree of detail and long time series. Although some studies have assessed the uncertainty and inconsistencies of the database for specific years and periods, no work has been found that analyses all the available CORINE time series (1990–2018). In this study, we analyse the inconsistencies of the CORINE time series for a specific Spanish region (Asturias). To this end, we compare and analyse the CORINE status layers (CLC) and the CORINE layers of changes (CHA) for each of the mapped periods: 1990–2000, 2000–2006, 2006–2012, 2012–2018. Results show how CLC and CHA layers provide different information, especially after the change of production of CORINE Spain in 2012. The last two CORINE editions (2012, 2018) show a lot of technical changes that make the use of CLC layers very uncertain. In addition, mixed categories, whose definition is imprecise and, therefore, more uncertain, are behind most of detected change in both types of CORINE layers (CHA, CLC). [ABSTRACT FROM AUTHOR]

Previous studies generally used land use and travel flow to investigate the efficiency of the railway system in Transit-Oriented Development (TOD) cities. Furthermore, to study the association of land use and jobs–housing distribution of commuters, we can find out the potential development of rail commuting. In this research, four railway lines in Wuhan, China, were selected to explore the land use in promoting practical commuting population according to the smart-card data obtained. For land use issues, except the road density and building density, a Normalized Location-Weighted Landscape Index (NLWLI) based on the source – sink theory in landscape ecology was established to assess the jobs–housing land use around rail transit stations. Meanwhile, employment and housing details of commuters around rail transit stations were identified using smart-card data. We found that the generation of commuting flow was affected by building density and the land use of employment in the immediate vicinity of rail transit stations. The distribution of building density and commuters in a mature rail line was roughly a normal distribution. However, due to the inconsistency of land use and jobs – housing distribution around stations, the requirement of the balance of land use and jobs – housing distribution should be reduced at the scale of rail stations in the TOD planning systems. This study is the application of massive smart-card data in the field of urban research. It identifies land use issues that affect rail transit commuting flow, and can help urban planners improve the efficiency of rail transit through planning and design. [ABSTRACT FROM AUTHOR]

The relative influence of climate and catchment characteristics to the variations in runoff in five Indian river basins is assessed using the climate elasticity approach based on the Budyko hypothesis. From 1980 to 1999, catchment characteristics are found to be the main contributor to runoff variation for all of the basins except Upper Mahanadi sub-basin, where climatic factors are the major contributor. Among the climatic factors, runoff is more responsive to changes in precipitation than to changes in potential evapotranspiration. The mean contribution of climate (catchment) to runoff variation is largest at the Cauvery (Krishna) basin. The findings may be useful in planning sustainable water resources infrastructure. Investigation of the relationship between runoff changes in the basins and their land use and land cover changes, as well as the vegetation index, adds to the novelty and usefulness of the study. [ABSTRACT FROM AUTHOR]

Land use is a driver for hydrological and soil erosion responses at the watershed scale. This study aimed to assess the hydrological and soil erosion processes in small watersheds under three different land uses, at three time scales. We investigated four small watersheds in southern Brazil: Agricultural North watershed (ANW), Agricultural South watershed (ASW), Eucalyptus watershed (EW), and Grassland watershed (GW). The SWAT (Soil and Water Assessment Tool) model was used to simulate streamflow (SF) and sediment yield (SY) at monthly, daily and hourly time scales. EW had the lowest SF and SY, whereas ANW showed the highest SY with an increase of 90% and ASW had the highest SF with an increase of 70%. The SWAT model had a satisfactory performance in all time scales and watersheds for SF and SY (NSE and R2 ≥ 0.3 and Pbias ≤ ± 39%). Overall, land use has a major impact on hydrological and soil erosion responses, and the magnitude of these processes depends on the time scale. [ABSTRACT FROM AUTHOR]

Land price distortion will not only lead to a series of economic problems such as widening regional economic gap, local government debt risk and serious ecological deterioration, but also lead to the imbalance of macro allocation of land resources and irrational spatial structure, and the land input-output efficiency will also be affected. This article studies the impact of land price distortion on China's land use efficiency using a dataset of 103 cities in China during the years 2008–2015. The results show that there exist significant spatiotemporal disparities of land use efficiency. The land use efficiency has significant spatiotemporal differences. Empirical results document that increases in land price distortion leads to significant decreases in land use efficiency. Our findings are robust to alternative measures of land price distortion, different subsamples and instrumental variable estimations. [ABSTRACT FROM AUTHOR]

This work performs an analysis of the spatial pattern of the coffee harvested area in the Rio de Janeiro state between 1988 and 2018. To relate changes in land cover and land use with the coffee land abandonment, geographically weighted regressions (GWR) were adopted with the rates of change in forest and pasture cover, and also with changes in the size of the cattle herd. The coffee-crop area evolution identifies three behaviors: the concentration of planted area in the northwest, with constant growth after the 1990s; a remaining area in the mountainous region; and the abandonment of coffee farms in the south. Although bivariate models can't explain the changes in land cover and land use, geographically weighted regressions point to a trend of replacing coffee cover with pasturelands in the south region of the state, while eventual changes for forest cover are more likely in other regions. [ABSTRACT FROM AUTHOR]

Remote sensing and land resource surveys have been used in recent decades for land use/land cover (LULC) mapping; however, keeping the developed LULC up-to-date and consistent with land survey statistics remains challenging. This study developed a practical and effective framework to automatically update existing LULC products and bridge the gap between remote sensing classification results and land survey data. This study employed Landsat imagery time series, change detection algorithms, sample migration, and random forests to develop a framework for updating existing LULC products in China from 1980–2015 to 1980–2022. The updated LULC maps reflect the post-2015 LULC changes well and maintain continuity with the pre-2015 products. Additionally, a statistical space allocation method based on the minimum cross-entropy strategy was proposed to optimize the LULC maps, increasing the correlation coefficient (r) with China's second and third national land survey statistics from 0.41–0.89 to 0.86–0.99. Thus, the framework and products developed in this study provide valuable tools for sustainable land use and policy planning. [ABSTRACT FROM AUTHOR]

In arid Africa, it is unclear how the transition from grassland to cropland affects CO2 fluxes and whether these effects are climate-dependent. From November 2019 to March 2020 (dry season), we studied autotrophic (Ra) and heterotrophic (Rh) soil respiration. At highlands, grazing land (1.18 ± 0.13 µmol m−2 s−1) and teff croplands (1.36 ± 0.14 µmol m−2 s−1) had the lowest Rh, while acacia decurrens plantations (1.94 ± 0.19 µmol m−2 s−1) were the largest. When compared to teff (2.08 ± 0.20 µmol m−2 s−1) and khat (1.73 ± 0.24 µmol m−2 s−1), grazing land in the midland had a lower Rh (1.18 ± 0.13 µmol m−2 s−1). Ra on teff (1.51 ± 0.27 µmol m−2 s−1) was substantially (P < 0.05) greater than on grazing land (1.08 ± 0.32 µmol m−2 s−1) in the highlands. Grazing lands (1.54 ± 0.21 µmol m−2 s−1) have a considerably (P < 0.05) greater Ra than farmlands (teff, 0.20 ± 0.07 µmol m−2 s−1; groundnut, 0.09 ± 0.03 µmol m−2 s−1) in lowlands. Growing teff in the highlands and midlands will result in higher CO2 fluxes into the atmosphere. However, in-depth research is needed to implement effective land management that reduces CO2 emissions. [ABSTRACT FROM AUTHOR]

Land surface temperature (LST), especially day-night LST difference (LS T d − LS T n ) , is a key variable for the stability of terrestrial ecosystems, affected by vegetation and climate change. Quantifying the contribution and feedback of vegetation and climate to LST changes is critical to developing mitigation strategies. Based on LST, Normalized vegetation index (NDVI), land use (LU), air temperature (AT) and precipitation (Pre) from 2003 to 2021, partial correlation was used to analyze the response of LST to vegetation and climate. The feedback and contribution of both to LST were further quantified by using spatial linear relationships and partial derivatives analysis. The results showed that both interannual LST (LS T y ) and LS T d − LS T n responded negatively to vegetation, and vegetation had a negative feedback effect in areas with significantly altered. Vegetation was also a major contributor to the decline of LS T d − LS T n. With the advantage of positive partial correlation area of 94.99%, AT became the main driving factor and contributor to LS T y change trend. Pre contributed negatively to both LS T y and LS T d − LS T n , with contributions of −0.004 °C/y and −0.022 °C/y, respectively. AT played a decisive role in LST warming of YRB, which was partially mitigated by vegetation and Pre. The present research contributed to the detection of LST changes and improved understanding of the driving mechanism. [ABSTRACT FROM AUTHOR]

Land change science co-evolves with remote sensing technology. The world has witnessed an exponential growth in Earth observation satellites since 1972, and concurrently, land change research has experienced transformative advancement. This review summarizes the major milestones in global land cover and change mapping in a chronological order, from the pioneering efforts in the 1980s to the latest innovations at present, illustrating the tremendous progress in monitoring global land change from space. The second part of the review presents a critical synopsis of the recent progress in land change research, focusing on the technical aspects of temporal trends characterization, change mapping and area estimation, as well as the applied aspects of driver attribution and the complex consequences to the Earth system and human society. The last part of the article offers insights in the strategic directions of land change monitoring, including generation of analysis ready data, application of artificial intelligence algorithms, reconstruction of historical land change records, and near-real-time land change monitoring. Land change science will continue to play a vital role in addressing a wide range of global challenges, including climate change and carbon sequestration, food security, sustainable energy transition, natural disaster relief and environmental change in conflicted societies. [ABSTRACT FROM AUTHOR]

The combination of spatial distribution, semantic characteristics, and sometimes temporal dynamics of POIs inside a geographic region can capture its unique land use characteristics. Most previous studies on POI-based land use modeling research focused on one geographic region and select one spatial scale and semantic granularity for land use characterization. There is a lack of understanding on the impact of spatial scale, semantic granularity, and geographic context on POI-based land use modeling, particularly large-scale land use modeling. In this study, we developed a scalable POI-based land use modeling framework and examined the impact of these three factors on POI-based land use characterization using data from three geographic regions. We developed a unified semantic representation framework for POI semantics that can help fuse heterogeneous POI data sources. Then, by combining POIs with a neural network language model, we developed a spatially explicit approach to learn the embedding representation of POIs and AOIs. We trained multiple supervised classifiers using AOI embeddings as input features to predict AOI land use at different semantic granularities. The classification performance of different land use classes was analyzed and compared across three geographic regions to identify the semantic representativeness of POI-based AOI embedding and the impact of geographic context. [ABSTRACT FROM AUTHOR]

Successful implementation of natural resource planning and land management systems requires understanding of how land use and land cover (LULC) have changed in the past and how they will change in the future, taking into account both space and time. The Yayo Coffee Forest Biosphere Reserve (YCFBR), in southwestern Ethiopia, is currently experiencing the consequences of different human actions such as wildfires and the expansion of coffee plantations. Although the Biosphere Reserve (BR) has undergone significant changes and efforts since it was registered by UNESCO in 2010 as a high biodiversity area of international importance, there is still a lack of information about the anticipated changes in LULC in the future. The primary aim of the study is to simulate the potential changes in LULC in the YCFBR area for the upcoming three decades. In this study, we utilized Landsat satellite imagery taken in 1992, 2007, and 2022 for analysis. The findings suggest that the agricultural area is expected to grow from 20.3% in 2022 to 24% in 2052, while the proportion of open forest is predicted to rise from 13.4% in 2022 to 18% in 2052. In addition, there is an anticipated decrease in both high forest and grazing lands. High forest is expected to decline from 50.1% in 2022 to 40% in 2052, while grazing lands are projected to decrease from 8.3% in 2022 to 6% in 2052. Thus, the study revealed a significant shift of grazing land to agriculture and high forest to more open forest types. We recommend a proper land use zoning to prevent further loss of the forest cover due to human activities and also restore the degraded parts of the area. [ABSTRACT FROM AUTHOR]

Land use / land cover (LULC) change profoundly impacts regional natural, economic, and ecological development; However, no study has been conducted to classify LULC changes in Ibb city using high-resolution satellite images. This study aims to evaluate and predict LULC changes and their driving forces in Ibb city, the tourist capital of Yemen. In this study, an integrated cellular automata and Markov chain (CA-Markov) model were implemented to analyze the spatio-temporal trends of Ibb city. Meanwhile, a socio-economic survey and key informant interviews were conducted to analyze the probable drivers of LULC change. Landsat (5, 7, and 8) data are used to analyze maps of LULC distributions for 1990, 2005, and 2020 at regular intervals. A CA–Markov model was employed to simulate long-term changes to the landscape at 15-year intervals from 2020 to 2050. Results indicate that the vegetation area decreased from 1760.4 km2 (33.2%) to 1371.7 km2 (27.8%). Meanwhile, barren land, grassland, and built-up areas increased from 3190.5 km2 (60.1%) to 3428.6 km2 (64.8%), from 336.0 km2 (6.3%) to 419.3 km2 (7.9%), and from 11.8 km2 (0.38%) to 76.2 km2 (1.42%), respectively. The CA-Markov model's accuracy was validated by comparing simulated and actual LULC maps for 2020 using the land change modeler (LCM) of IDRISI-TerrSet software. The predicted LULC maps for 2035 and 2050 indicate that the vegetation area, grassland, and barren land showed decreasing trends, while the built-up area and waterbody showed increasing trends. These results provide valuable insights for tracking future LULC changes and are pivotal in guiding sustainable land use practices, striking a balance between conserving natural resources and advancing urban development projects in the future. Driving factors on land-cover transitions tend to be spatiotemporal scale-dependent. The study analyzed changes in LULC trends and their Proximate and Underlying drivers. Significant changes were observed between 1990 and 2020, and changes are expected by 2035 and 2050. The integration of the CA-Markov Model and GIS techniques successfully simulated spatiotemporal LULC changes. Fine-tuned analysis of driving forces is essential for planning and managing sustainable land use. [ABSTRACT FROM AUTHOR]

We conducted a scientific quantitative analysis of the spatiotemporal evolution and driving factors of land use in Henan Province using a spatial zoning approach. The province was divided into five distinctive regions. Employing methods, such as information mapping, we analyzed land use data for 1990, 2000, 2010, and 2020, investigating spatiotemporal evolution and differences. Additionally, we employed a geographic detector model to explore the dominant factors behind land use changes in 2010 and 2020. Primary land classes in Henan Province included cultivated land, forests, and construction, with cultivated land transitioning mainly to forests and construction. However, regional analyses revealed diverse outcomes. In the Yudong area, cultivated land dominated with an 80% area proportion, shifting mostly to construction. In the Yubei area, grassland transformed into cultivated land and forests, with escalating grassland loss. The Yuxi area exhibited a 40% forest area proportion, with frequent mutual conversions between forests, cultivated land, and grassland. Spatiotemporal evolution indicated active changes in cultivated land. The geographic detector revealed a shift in influential factors from natural to economic drivers for cultivated land changes in Henan Province between 2010 and 2020. By uncovering land use disparities across regions, we contribute suggestions for sustainable development decisions regarding land use in Henan. [ABSTRACT FROM AUTHOR]

This study evaluates the sensitivity of the Dynamic Habitat Index (DHI), utilizing multitemporal Normalized Difference Vegetation Index (NDVI) data, to changing environmental conditions across Land Use/Land Cover (LULC) types in a central European landscape (2017–2020). We observed distinct DHI characteristics for all LULC types, and the DHI responded to an extreme drought year in 2018 with no return to pre-drought conditions except for deciduous forests. The DHI also effectively captured spatio-temporal variability of pedo-climatic conditions. Thus, integrated with ancillary geodata, the DHI enhances traditional categorical LULC maps, offering applications in biodiversity and ecosystem research. Such integrated products could serve as valuable tools for decision makers to formulate sustainable land management strategies and contribute to Sustainable Develop Goal indicators related to land degradation, e.g. by identifying deviations from typical, context-specific DHI profiles as a response to disturbance and environmental stress. [ABSTRACT FROM AUTHOR]

LULC and climate change are the two most common manifestations of global environmental change. The objective of this study was to quantify past and future LULC and climate change impacts on environmental sustainability in the Vea catchment of Ghana. The past LULC change (1998–2022) was analyzed using ERDAS Imagine 15 upon the application of the Support Vector Machine (SVM) classifier algorithm. The CA-Markov was used to predict land-use changes in 2038 and 2054. Climate change was projected under SSP 4.5 and SSP 8.5 emission scenarios using the R software. The projections from an ensemble mean of SSPs in the near future (2023–2052) and far future (2071–2100) were compared to the reference period (1993–2022). The results show that, between 1998 and 2022, cropland increased from 10.9% to 51.98%, while grassland and forest areas decreased from 54.8–18.14% and 31.7–22.73%, respectively. The results of the predicted LULC change showed an increase in cropland from 181 km2 in 2038 to 183 km2 in 2054 at the expense of grassland and forest, which are expected to decrease from 51–50 km2 and 73–71 km2, respectively. The findings of climate change show the projected increases in average temperature range from 2.10 to 3.5 °C under SSP4.5 and from 2.7 to 4.15 °C under SSP8.5. Under the SSP4.5, annual average precipitation is anticipated to decrease by 12.34–13.1%, while the SSP8.5 projects a decrease of 12.6–13.6%. Results will help in the setting up of long-term environmental management strategies in the catchment as well as the development of appropriate adaptation methods to mitigate the ongoing impacts of LULC and climate change on environmental sustainability. [ABSTRACT FROM AUTHOR]

Green space (GS) is a crucial resource in urban areas, but not spatially uniformly distributed. We compare the availability of GS on a national scale using green land cover (GLC) and public green space (PGS). Using spatial census data we analyse GS availability and accessibility for the German population. The average GS availability differs by a factor of three between GLC and PGS. 19.2 % of Germans find less than the WHO defined target for PGS in their neighbourhood. PGS is less equally distributed among the population than GLC, and green space equity varies significantly between rural and urban areas. In areas with multi-family homes, a higher share of the population has access to sufficient PGS than in areas with predominantly single-family homes. We find a negative relation between GLC availability and share of immigrant population, which does not extend to PGS. [ABSTRACT FROM AUTHOR]

Spatial plan decisions guide both the future use of the lands and many activities from protection to construction and permit. Due to its functions, spatial plan decisions play a key role in land administration. Spatial planning information for integrated land administration systems (LASs) should be associated with land registration systems. The Land Administration Domain Model (LADM) standard offers components to enable this structure. Integrating spatial plan data with LASs will provide standardization for plan data and assurance of plan decisions. Although the spatial planning mission differs across various administrative regions, planning activities produce land use decisions, albeit in different ways. The study aims to establish the common points in planning activities and design a joint spatial planning system data model using various countries' spatial planning systems and international standardization studies. The spatial plans in the model that has been proposed are depicted as a system, not merely by the rights, restrictions, and responsibilities (RRRs) that they establish on the land. The results point out that spatial planning systems have some similarities but also some limitations to support conceptual model design. Based on joint data and relationships, the proposed spatial planning system data model can be adapted for different country practices. The study's results are expected to support the LADM second version development studies. [ABSTRACT FROM AUTHOR]