Land Use Cover Change Research Articles

Impacts of land use/cover change on urban rainfall-flooding processes based on numerical simulations

ABSTRACT The evolution of surface conditions caused by urbanization has a great impact on urban flooding, whose increasing frequency of occurrence has severely affected urban safety. Most previous studies have focused on land use/cover change (LUCC) but have not specifically explored the effects of LUCC on the spatial distribution of flood points and the ponded depth. We combined the storm water management model (SWMM) with multiyear remote sensing data to simulate the flood points and ponded depth in different rainstorm types. Results showed that the ratios of flood points with ponded depths >0.7 m increased from 2.58% to 17.12% with the evolution of the urban surface conditions in 1988–2021. Also, the flood points with ponded depths >0.7 m were mainly located in the southern and northwestern parts of Bantian Street. These results can provide better-informed decision making for storm water management and early warning of flooding disasters in Shenzhen.

Hydrological response to climate and land use and land cover change in the Teesta River basin

ABSTRACT The Teesta basin is shared by Bangladesh and India, holds significant importance in the bilateral relationship, and sustains the livelihoods of over 30 million people in Bangladesh. Employing a cellular-automata model (CA), we accurately estimate LULC for the 2020s and projected for the 2050s and 2080s. A semi-distributed hydrological model, Soil Water Assessment Tool (SWAT), is used to generate flow for the base period (1995–2014), the near future (2035–2064), and the far future (2071–2100). SWAT model is forced by eight general circulation models (GCMs) under two socioeconomic pathways (SSP245 and SSP585). The CA-Markov prediction indicates LULC changes, especially increased agriculture and settlements by 76 and 42%, and decreased forest and water by 13 and 36%, respectively, which are expected by 2050s and will influence discharge patterns. This results in additional discharge increases of 4% (–8 to 5%) for SSP245 and 5% (–8 to 10%) for SSP585 scenarios during wet seasons. In the far future, monsoon flow will increase by 13% (0.4 to 23%) for SSP245 and 52% (–29 to 151%) under SSP245 and SSP585. A marginal change in winter flow was shown by –6% (–16 to 4%) reduction under SSP245 and –13% (–64 to 63%) under SSP585 reduction in the 2080s.

Enhancing decision-making for climate change mitigation and sustainable urban growth

Uncontrolled urban expansion presents significant challenges to green spaces, leading to increased land surface temperature, and carbon emissions. This study emphasizes the importance of predicting urban growth, monitoring LST, and assessing green space suitability to mitigate these impacts in Bojnourd City, Iran. This research aims to enhance land use planning by employing the SLEUTH model and integrating landscape features to evaluate and compare urban growth scenarios. The study consisted of five main stages: monitoring LULC and LST changes, utilizing the InVEST Carbon Storage and Sequestration model for carbon stock mapping, assessing green space suitability, simulating urban growth scenarios up to 2050, and prioritizing scenarios using landscape metrics and TOPSIS. Five scenarios were analyzed: Low Carbon City, Compact Urban Growth, Historical Urban Growth, Uncontrolled Urban Growth, and Green City. Landscape metrics were utilized to assess the environmental consequences of each scenario. The results demonstrate that the Compact Urban Growth scenario, which focuses on land conservation, achieved the highest environmental sustainability score of 0.818, followed by the Green City scenario at 0.72, and the Low Carbon City scenario at 0.55. These findings highlight the effectiveness of the SLEUTH model in guiding urban planners toward decisions that promote sustainable, low-carbon urban development.

Identifying Changes and Their Drivers in Paddy Fields of Northeast China: Past and Future

Northeast China plays a crucial role as a major grain-producing region, and attention to its land use and land cover changes (LUCC), especially farmland changes, are crucial to ensure food security and promote sustainable development. Based on the Moderate Resolution Imaging Spectroradiometer (MODIS) data and a decision tree model, land types, especially those of paddy fields in Northeast China from 2000 to 2020, were extracted, and the spatiotemporal changes in paddy fields and their drivers were analyzed. The development trends of paddy fields under different future scenarios were explored alongside the Coupled Model Intercomparison Project Phase 6 (CMIP6) data. The findings revealed that the kappa coefficients of land use classification from 2000 to 2020 reached 0.761–0.825, with an overall accuracy of 80.5–87.3%. The proposed land classification method can be used for long-term paddy field monitoring in Northeast China. The LUCC in Northeast China is dominated by the expansion of paddy fields. The centroids of paddy fields gradually shifted toward the northeast by a distance of 292 km, with climate warming being the main reason for the shift. Under various climate scenarios, the temperature in Northeast China and its surrounding regions is projected to rise. Each scenario is anticipated to meet the temperature conditions necessary for the northeastward expansion of paddy fields. This study provides support for ensuring sustainable agricultural development in Northeast China.

Dam Siltation in the Mediterranean Region Under Climate Change: A Case Study of Ahmed El Hansali Dam, Morocco

Dams are vital for irrigation, power generation, and domestic water needs, but siltation poses a significant challenge, especially in areas prone to water erosion, potentially shortening a dam’s lifespan. The Ahmed El Hansali Dam in Morocco faces heightened siltation due to its upstream region being susceptible to erosion-prone rocks and high runoff. This study estimates the siltation at the dam from its construction up to 2014 using bathymetric data and the Brown model, which is a widely-used empirical model that calculates reservoir trap efficiency. Additionally, the study evaluates the impact of Land Use and Land Cover (LULC) changes and projected future rainfall until around 2076 based on siltation rates. The results indicate that changes in LULC, particularly temporal variations in precipitation, have a significant impact on the siltation of the Ahmed El Hansali dam. Notably, rainfall is strongly correlated with the siltation rate, with an R2 of 0.92. The efficiency of sediment trapping (TE) is 97.64%, meaning that 97.64% of the sediment in the catchment area is trapped or deposited at the bottom of the dam. The estimated annual specific sediment yield is about 32,345.79 tons/km2/yr, and the sediment accumulation rate is approximately 4.75 Mm3/yr. The dam’s half-life is estimated to be around 2076, but future precipitation projections may extend this timeframe due to the strong correlation between siltation and precipitation. Additionally, soil erosion driven by land management practices plays a crucial role in future siltation dynamics. Hence, this study offers a comprehensive assessment of the siltation dynamics at the Ahmed El Hansali dam, providing essential information on the long-term effects of erosion, land use changes, and climate projections. These findings may assist decision makers in managing dam reservoir sedimentation more effectively, ensuring the durability of the dam and extending the reservoir life.

Urban Heat Island and Environmental Degradation Analysis Utilizing a Remote Sensing Technique in Rapidly Urbanizing South Asian Cities

Rapid urbanization in South Asian cities has triggered significant changes in land use and land cover (LULC), degrading natural biophysical components and intensifying urban heat islands (UHIs). This study investigated the impact of LULC changes on land surface temperature (LST) and the role of biophysical indicators in enhancing urban resilience to thermal extremes. We used Landsat satellite imageries from 1993 to 2023, conducted a comprehensive analysis of LULC changes, and estimated LST variations at 6-year intervals in the Dhaka, Gazipur, and Narayanganj districts in Bangladesh. Afterward, we performed statistical analysis upon employing correlation, regression, and principal component analysis (PCA) techniques to summarize information. The results reveal that 339.13 km2 worth of urban expansion has occurred in last 30 years, with an average annual growth rate of 3.5%, accompanied by a substantial reduction in water bodies (−139.17 km2) and vegetation cover. Consequently, summer temperatures exceeded approximately 36.52 °C in dense urban areas. Also, the results highlighted the strong influence of built-up areas (BSI and SAVI) on LST, while vegetation (NDVI) and water indices (NDWI) exhibited a negative association. The findings emphasize the urgency of integrating green infrastructure and deploying sustainable urban planning policies to mitigate the potential adverse impacts of scattered urbanization in the face of climate change.

ASSESSMENT OF THE IMPACT OF GURARA DAM ON LAND USE/LAND COVER IN THE SURROUNDING COMMUNITIES OF KACHIA LOCAL GOVERNMENT AREA OF KADUNA STATE, NIGERIA

The study assessed the impact of Gurara Dam on land use/land cover changes (LULCC) in the Kachia Local Government Area of Kaduna State. The study made use of geospatial techniques to assess the impact of the dam on land use/land cover changes within the period of study. Landsat data from 2001, 2012 and 2022 were acquired and processed to produce the land use/land cover maps of the area. The identified land use/land cover in the area were Built-up areas, Water bodies, Vegetation, bare land, and Rock outcrops. The Annual rate in land use/landcover changes was analyzed and the result revealed that, during the period 2001-2012, and 2012-2022 water bodies increased at an annual rate of 242% and 97% but reduced at an annual rate of 0.9%between 2012 and 2022. The analysis revealed that all the land use/land cover types identified in the study area recorded a net gain except vegetation. Water bodies gained about 5480 ha from 2001 to 2022. The study concluded that the construction of the Dam has altered the land use land cover dynamics of the area and there is also evidence of deforestation in the study area. The study recommends the control of land use in the basin and uses it as a guide to help in prioritizing the management of the basin and the dam among others.

A 28-time-point cropland area change dataset in Northeast China from 1000 to 2020

Abstract. Based on historical documents, population data, published results, remote sensing data products, statistical data, and survey data, this study reconstructed the cropland area and the spatial pattern changes at 28 time points from 1000 to 2020 in Northeast China. The period from 1000 to 1600 corresponds to historical provincial-level administrative districts, while the period from 1700 to 2020 corresponds to modern county-level administrative districts. The main findings are as follows: (1) the cropland in Northeast China exhibited phase changes of expansion–reduction–expansion over the past millennium. (2) The cropland area in Northeast China increased from 0.55×104 km2 in 1000 to 37.90×104 km2 in 2020, and the average cropland fraction increased from 0.37 % to 26.27 %; (3) from 1000 to 1200, the cropland area exhibited an increasing trend, which peaked in 1200. The scope of land reclamation was comparable to modern times, but the overall cropland fraction remained low. The cropland area significantly decreased between 1300 and 1600, with the main land reclamation area being reduced southward into Liaoning province. From 1700 to 1850, the cropland area increased slowly and the agricultural reclamation gradually expanded northward. After 1850, there was almost exponential growth, with the cropland area continuously expanding to the whole study area, and this growth trend persists until 2020; (4) the dataset of changes in the cropland of administrative districts in Northeast China, reconstructed based on multiple data sources and improved historical cropland reconstruction methods, significantly enhances time resolution and reliability. Additionally, the dataset shows relatively better credibility assessment results, which can provide a refined database for historical land use and land cover change (LUCC) dataset reconstruction, carbon emission estimation, climate data construction, etc. The dataset can be downloaded from https://doi.org/10.6084/m9.figshare.25450468.v2 (Jia et al., 2024).

Assessment of dyna clue model for prediction of spatio-temporal dynamics of urbanisation and green space in Jaipur district, Rajasthan (India)

Urbanisation in Jaipur, Rajasthan’s capital, has significantly impacted land use and land cover (LULC) over the past four decades. This study addresses the pressing issue of how rapid urban expansion affects green spaces and environmental balance. Utilizing satellite imagery and a support vector machine (SVM) algorithm, LULC maps for 1993, 2003, 2013, and 2023 were generated to analyze changes in land cover, including agriculture, barren land, built-up areas, vegetation, wasteland, fallow land, and water bodies. The Dyna-CLUE model, incorporating variables such as elevation, slope, aspect, and proximity to streams and roads, was employed to forecast LULC changes for 2033 and 2043. The findings reveal a marked increase in built-up areas at the expense of vegetative cover, driven by urbanization, infrastructural development, agricultural expansion, climate change, and policy decisions. With Kappa coefficients indicating high agreement between classified land cover and ground truth data (84–90% accuracy), the study projects continued urban growth and further decline in vegetation. This underscores the urgent need for sustainable land use planning and environmental conservation in Jaipur. Proposed strategies to address these issues include establishing ecological zones, enforcing green building regulations, promoting mixed-use development, and implementing a 15-min green space policy. These measures aim to enhance green space distribution and support Jaipur’s transition towards a greener urban environment.

EVALUACIÓN DEL IMPACTO DE LOS CAMBIOS EN EL USO Y COBERTURA DE LA TIERRA EN EL ESCURRIMIENTO SUPERFICIAL

The aim of this study was to analyze the behavior of surface runoff as a result of changes in land use and land cover (LULC), using the Rio Novo basin (Brazil) as the analysis site. To estimate surface runoff, the curve number (NRCS-CN) method was used; as input data, the LULC classifications provided by the MapBiomas project and the pedological map of the state of São Paulo (1:250,000) were used. The Rio Novo basin was discretized into ten sub-basins. The results showed major changes in LULC between 1992 and 2022, with a reduction in pasture areas and an increase in annual crops and sugarcane fields, as well as in urban areas. Such alterations are conditioning factors of changes in Curve Number (CN) values, which imply changes in surface runoff values. For a rainfall of 130 mm (roughly 10-year return period), the surface runoff depth values ranged from 3.21 mm (areas with forest cover on soils in hydrological group A) to 101.35 mm (for urban areas on soils in hydrological group C). The urbanization process that occurred in sub-basins 1, 6, and 9 led to an increase in areas with the highest CN values (CN equal to 85 and 90). Locations with increased surface runoff values should be considered as critical areas, where soil and water losses may occur, thereby compromising water security in the basin. Keywords: NRSC-CN method, Geographic Information System, Water Resources Management, MapBiomas.

Machine Learning and Remote Sensing Applications for Assessing Land Use and Land Cover Changes for Under-monitored Basin

Urban sprawling caused by industrial and economic growth has significantly affected land use and land cover (LULC). Using satellite imagery for real-time examination in Kuantan has become exceedingly expensive due to the scarcity and obsolescence of real-time LULC data. With the advent of remote sensing and geographical information systems, LULC change assessment is feasible. A quantitative assessment of image classification schemes (supervised classification using maximum likelihood and deep learning classification using random forest) was examined using 2022 Sentinel-2 satellite imagery to measure its performance. Kappa coefficient and overall accuracy were used to determine the classification accuracy. Then, 32 years of LULC changes in Kuantan were investigated using Landsat 5 TM, Landsat 8 OLI, and Sentinel-2 based on the best classifier. Random forest classification outperformed maximum likelihood classification with an overall accuracy of 85% compared to 92.8%. The findings also revealed that urbanisation is the main factor contributing to land changes in Kuantan, with a 32% increase in the build-up region and 32% in forest degradation. Despite the subtle and extremely dynamic connection between ecosystems, resources, and settlement, these LULC changes can be depicted using satellite imagery. With the precision of using a suitable classification scheme based on comprehensive, accurate and precise LULC maps can be generated, capturing the essence of spatial dynamics, especially in under-monitored basins. This study provides an overview of the current situation of LULC changes in Kuantan, along with the driving factors that can help the authorities promote sustainable development goals.

Linking land use and precipitation changes to water quality changes in Lake Victoria using earth observation data

Due to the continued increase in land use changes and changing climatic patterns in the Lake Victoria basin, understanding the impacts of these changes on the water quality of Lake Victoria is imperative for safeguarding the integrity of the freshwater ecosystem. Thus, we analyzed spatial and temporal patterns of land cover, precipitation, and water quality changes in the Lake Victoria basin between 2000 and 2022 using global satellite products. Focusing on chlorophyll-a (Chl-a) and turbidity (TUR) in Lake Victoria, we used statistical metrics (correlation coefficient, trend analysis, change budget, and intensity analysis) to understand the relationship between land use and precipitation changes in the basin with changes in Chl-a and TUR at two major pollution hotspots on the lake, i.e., Winam Gulf and Inner Murchison Bay (IMB). Results show that the Chl-a and TUR concentrations in the Winam gulf increase with increases in precipitation. Through increases in precipitation, the erosion risks are increased and transport of nutrients from land to the lake system, promoting algal growth and turbidity. In the IMB, Chl-a and TUR concentrations decrease with an increase in precipitation, possibly due to dilution, but peak during moderate rainfall. Interestingly, changes in land use and land cover (LULC) at 5-year intervals showed no substantial correlation with water quality changes at selected hotspots even though a broader LULC change analysis over the past two decades indicated a notable 300% increase in built-up areas across the Lake Victoria basin. These findings underscore the dominant influence of precipitation changes over LULC changes on the water quality of Lake Victoria for the selected hotspot areas.

Ecological effects of land use and land cover change in the typical ecological functional zones of Egypt

Evaluation the value of ecosystem services can provide crucial reference for formulating ecological protection plans and making informed management decision. This study utilized Landsat remote sensing images as the data source and employed land-use transfer chains and land use transfer matrix methods to compare the ecological effects of land use and land cover change(LUCC) in the two typical ecological functional zones of Egypt, one area isthe northern region of Egypt with the Priority function of Economic Development, another area is the Nasser Reservoir area with the priority function of water conservation. The key findings are as follows: (1)The northern region of Egypt and the Nasser Reservoir exhibited different trends across the ecological functional zones.From 1985 to 2020, the northern region of Egypt is characterized by an increase in arable land and impervious surface,the Nasser Reservoir area is distinguished by the expansion of water and a reduction in sand.(2) Key land transfer patterns vary significantly between the ecological functional zones of the northern region of Egypt and the Nasser Reservoir. From 1985 to 2020, the Egypt’s northern region experienced significant shifts between arable land, sand, and impervious surfaces. The conversion of arable land to impervious surfaces represented 2.41% of the total arable land transfer area, while sand converted to impervious surfaces accounted for 11.68% of the total sand transfer area. In the Nasser Reservoir region, significant conversions occurred between water, grasslands, and sand. Sand converted to water made up 3.83% of the total sand transfer area, while grassland converted to water compriseed 5.38% of the total grassland transfer area. (3) The ecological benefits of the northern region of Egypt and the Nasser Reservoir have increased significantly. In northern region of Egypt, the primary drivers of this increase in ecological service value are the conversion of arable land and grasslands, along with the ecological development and utilization of sand. In the Nasser Reservoir area,the inflow of water and the continued outflow of sands are the main factors contributing to the rise in ecosystem service value. (4) Differentiated LUCC management should be implemented for different ecological functional zones. In northern region of Egypt, the focus should be on balancing ecological security with human development, while the Nasser Reservoir area should prioritize water resource protection and sustainable development. The research findings are not only significant for optimizing LUCC but also for enhancing ecosystem service functions in Egypt.

Ecological protection makes the ecological Kuznets curve turning point come earlier

Exploring the relationship between land use cover/change (LUCC) and ecosystem service value (ESV) under different future scenarios can provide guidance for selecting future development patterns and for the scientific utilization of land resources in the region. In this study, LUCC under different scenarios in the North Slope of Tianshan Mountain (NSTM) was simulated using the PLUS model. The ESV coefficients were adjusted for regional differences and social development factors to better reflect the actual situation in the study area. The interactions between LUCC, landscape pattern (LSP), and ESV were systematically analyzed, while at the same time, ESV and the level of economic development were fitted to the Ecological Kuznets Curve, which was then used to determine its trend and inflection point. The following conclusions were drawn: (1) Cropland and unused land are the main types of land use change in the NSTM, both historically and in the future. Cropland shows an increase in the natural development scenario and a decrease in the ecological protection scenario. Unused land shows an increase in the different development scenarios, indicating that unused land has higher development potential in the NSTM. NSTM shows a continuous decrease in ESV in the natural development scenario and a continuous increase in ESV in the ecological protection scenario. (2) LSP in both historical and future NSTM have evolved to show fragmentation, heterogeneity, and complexity in patch forms. However, this trend is slower in the ecological protection scenario than in the natural development scenario. LUCC, LSP, and ESV form an integrated framework of interactions, where LUCC influences ESV through LSP, and changes in ESV feedback to LUCC through LSP, which acts as a bridging mediator. (3) The Ecological Kuznets Curve of NSTM exhibits an N-shape, showing a clear overall rightward trend across different development scenarios at the annual level. At the interannual level, the curves for the natural development scenario are situated in the middle of the declining phase of the N-shape, with no ecological inflection point occurring during the study period. In contrast, the curves for the ecological protection scenario display a declining-ascending trend, with the ecological inflection point occurring when per capita GDP reaches 2.5 × 10^6 CNY.

Simulation and prediction of daytime surface urban heat island intensity under multiple scenarios via fully connected neural network

The intensification of the Surface Urban Heat Island (SUHI), driven by urbanization, land use and land cover (LULC) changes, and population growth, presents significant environmental and public health risks in urban areas. Simulating and predicting SUHI, particularly through the identification of future high SUHI intensity (SUHII) zones, has been recognized as a critical step in mitigating these effects. This study employs a Fully Convolutional Neural Network (FCNN) model, trained on data from four research sites, to simulate the current daytime SUHII across six validation sites in Singapore, utilizing 15 key independent variables identified in previous studies. The model exhibits high validation accuracy, achieving 87.45%. Three projection scenarios, based on projected population growth and LULC changes, predict a decrease in High SUHII across all validation sites, ranging from 98.3% to 9%. This reduction is attributed to the LULC improvements proposed in the 2019 Master Plan. Spatial analysis of the predicted SUHII maps indicates that the majority of High SUHII locations across scenarios remain consistent with the current situation. This research also suggests that the model could be a valuable tool for urban planners, allowing them to assess whether new urban development plans will effectively reduce High SUHII to desired thresholds, thereby mitigating SUHII in urban environments.

Mapping and Identification of Ecosystem Services Hotspots in the Brazilian Pampa Biome.

The intensification and expansion of changes in land use and land cover (LULC) can reduce the availability and quality of natural habitats and ecosystem services (ES). These changes have generated environmental damage in different parts of the world, especially in biomes more susceptible to modifications, such as the Pampa biome in the extreme south of Brazil. The Pampa biome has been neglected by environmental protection laws, despite its broad ecosystem and social importance. In this study, we used InVEST models to map and quantify five ES provided (i.e., water supply, carbon stock, groundwater stock, sediment retention and habitat quality) by 14 watersheds distributed in the Brazilian Pampa biome as well as determine ES hotspots by summing the areas with high provision of ES. We identified low availability of water supply and groundwater stock in practically the entire study area. High sediment retention and carbon stock were reported in areas with the presence of native vegetation. In addition, despite the large degraded areas, we observed high habitat quality associated with native vegetation in all studied watersheds. The hotspots varied spatially in the study area according to the proposed scenarios, the supply and the overlap of ES. Scenario 1 (>50% of ES) presented a larger area of high provision of ES. In contrast, scenario 2 (>75% of ES) presented smaller patches of areas with high provision of ES distributed across different watershed. We observed that large territorial extensions with high and medium provision of ES are vulnerable to the negative effects of LULC. Our study presented scenarios that indicate areas of high provision of ES, contributing to a more practical application, being a simplified and useful tool that can assist conservation and sustainable policies.

Projection of land use and land cover changes based on land change modeler and integrating both land use land cover and climate change on the hydrological response of Big Creek Lake Watershed, South Alabama

Changing land use/land cover (LULC) and climate substantially affect the hydrological components of a watershed. This study explored the future impact of the hydrological responses due to the changing LULC and climate on the Big Creek Lake watershed in Alabama, USA, from 2021 to 2050 using the Soil and Water Assessment Tool (SWAT). Five climate model datasets were used under the moderate scenario (Representative Concentrative Pathways 4.5) and the extreme scenario (Representative Concentrative Pathways 8.5), and the datasets were downscaled and bias-corrected. In addition, changing the LULC of five categories was predicted by Cellular Automata Markov (CA- Markov). With these data combined with the elevation (Digital Elevation Model), soils, and weather data, the SWAT model was calibrated and validated for the studied watershed to quantify how climate change will affect streamflow, nitrogen, and phosphorus. Our results indicate streamflow will increase due to the 50-acre increase in urban LULC. As streamflow increases, the percolation, surface runoff, lateral flow, groundwater flow, and water yield will also increase because the streamflow impacts these hydrological components. Moreover, the increase rate in streamflow is the same for all the components for January, February, and March. Therefore, there is a strong correlation between these months. On the contrary, evaporation will be high in May, June, and July because of the increasing temperature and streamflow. However, the changes in the water hydrological parameters and total nitrogen and phosphorus will be more intense in RCP8.5 than in RCP4.5.

Assessment and Multiscenario Simulation of Land Use and Ecosystem Services Interactions in Inner Mongolia

ABSTRACTBalancing land development and ecological protection poses significant challenges for sustainable development in arid and semi‐arid regions like Inner Mongolia. This study uses the integrated valuation of ecosystem services (ESs) trade‐offs model and patch‐generated land‐use simulation model to analyze the impacts of land‐use/cover (LULC) changes on ESs from 2005 to 2020 and simulate scenarios for 2035. The results show that (1) ecological governance efforts improved the comprehensive ecological index (CEI), habitat quality, and soil conservation capacity but led to a decrease in the annual water yield (AWY) in the eastern region. Additionally, the conversion of grassland and forest land to construction land and farmland caused slight declines in carbon sequestration and increased nitrogen export. (2) The external driving factors of different ESs vary, and the internal relationships within ESs have also changed. Notably, changes in LULC transformed the synergy between AWY and habitat quality into a trade‐off relationship after 2010 due to increased forest and grassland. (3) Among the five land‐use scenarios, the comprehensive development scenario combined with zonal management strategies can achieve the sustainable development goals of economic growth, ecological protection, and food security. This study clarifies the internal and external factors affecting ESs in Inner Mongolia and provides a scientific basis for future LULC management and ecological governance policies. It fills a gap in the spatiotemporal simulation of ESs under multiple scenarios in this region. These findings offer valuable references for promoting sustainable development in similar arid and semi‐arid regions, highlighting the importance of integrating multi‐objective strategies and adaptive management practices to balance ecological and economic objectives.

Impact of land use land cover changes on urban temperature in Jakarta: insights from an urban boundary layer climate model

Urbanization is one of the important drivers of increasing local temperatures. As cities and urban areas evolve, extensive land use and land cover (LULC) changes alter the physical characteristics of surface materials. This modification results in reduced evapotranspiration rates, ultimately contributing to higher surface and air temperatures. This study investigated the impact of urbanization on urban temperature in Jakarta. Urban temperature was simulated for a 20-year time period (1995–2014) by the urban boundary layer climate model UrbClim, using LULC data for both 1995 and 2014. Temperature changes were analysed by assessing the temperature anomaly across different LULC change classes divided into four main classes namely no built-up changes (BB), no green spaces changes (GG), built-up to green spaces (BG), and green spaces to built-up (GB). The study revealed that the conversion of green spaces to built-up areas (GB) had the most significant impact on the increase in air temperature. This was indicated by the mean values of the temperature anomaly of GB of about 0.24°C followed by GG, BB, and BG with the mean values of the temperature anomaly of about 0.20°C, 0.19°C, 0.17°C, respectively. The different temperature anomalies of the LULC change classes indicate that green spaces have an important role in maintaining local climate. Hence, it is important for local government to effectively manage the composition, the quantity, as well as the distribution of green spaces within a city. By looking at temperature anomalies of LULC change classes, the present study provides an alternative approach to many existing methods that provide general information about temperature changes, without specifically analyzing the effects of LULC transformations.

A multi-objective optimization framework for regional land-use allocation: Fully utilizing terrestrial vegetation to mitigate carbon emissions

Human-induced changes in land use and land cover (LULC) considerably impact the global carbon cycle. Rational LULC optimization with full utilization of terrestrial vegetation facilitates reconciling carbon reduction and socio-economic development. To this end, this study develops a multi-objective framework for low-carbon LULC spatial optimization that incorporates carbon suitability, historical suitability, and socio-economic needs. The framework is applied to Hubei Province, China. The key findings include: (1) Considering spatial variations in vegetation carbon sinks could lead to remarkable carbon reductions of 2.75 × 106 t C by 2030 and 7.68 × 106 t C by 2060. It would also lower carbon emissions per unit of gross domestic product (GDP) and enhance carbon sequestration per unit of vegetation by 2030, signifying enhanced carbon reduction efficiency. (2) Integrating carbon sequestration potential and historical suitability can considerably minimize emissions while sustaining socio-economic growth. Our method, compared with strategies based solely on historical development laws, can reduce carbon emissions by approximately 1.3–1.6 × 106 t C·a−1. (3) We also propose targeted low-carbon development suggestions for different LULCs. This study provides optimal spatial LULC allocations and strategic advice for regional LULC planning aimed at low-carbon development, demonstrating the feasibility of reconciling the tension between carbon reduction and socio-economic growth at the regional scale.