Rapid Urban Expansion Research Articles

Low Residents’ Satisfaction with Wetland Leisure Demand in Typical Urban Areas of the Semi-Arid Region in Western China: Spatial Variations and Their Causes

Wetlands, as a crucial component of urban green spaces, provide important leisure services for residents. Construction of wetlands has increased with the rapid urban expansion and population growth in China over recent decades, especially in semi-arid regions with scarce water resources. However, the residents’ satisfaction with wetland leisure demand remains unclear. This study evaluated the residents’ satisfaction with wetland leisure demand by a framework of physical calculation, taking Yinchuan City, the capital city of Ningxia Hui Autonomous Region, in the semi-arid region of Western China as a case study area. Spatial variations in residents’ satisfaction and their causes were revealed by a supply–demand relationship between the population capacity of wetlands and the total population of communities under a framework of physical calculation. The results indicated that 4.22% of the study area, which covered 7.38% of the total population, was fully satisfied with wetland leisure demand. Residents’ satisfaction in the urban area as a whole is low at 0.49, with a concentric distribution pattern increasing as the distance from the central urban area increases. The high population density and scanty wetlands mainly induced a relative-low residents’ satisfaction in the central urban area, accounting for 12.02% of the area and 32.70% of the population. Meanwhile, a relative-high residents’ satisfaction in the outer ring of the central urban area accounting for 59.10% of the area and 20.63% of the population was primarily due to the adequate capacity of wetlands. Medium residents’ satisfaction was mainly attributed to the road network density, which partially transferred local wetland leisure demand to adjacent areas. Wetland constructions and internal structural optimization to improve the capacity for leisure in densely populated central urban areas could provide a feasible path to alleviate unbalanced conditions. These results could deepen the understanding of supply–demand dynamics in the wetland leisure service and provide valuable information for optimizing wetland allocation in urban construction in semi-arid regions.

Exploring and Predicting Landscape Changes and Their Driving Forces within the Mulan River Basin in China from the Perspective of Production–Living–Ecological Space

With rapid economic development and urban expansion, China faces a serious imbalance between production, living, and ecological land use, in which the erosion of water ecological space by urban expansion is especially notable. In order to alleviate or solve this imbalance, this study constructs the water ecological space in the Mulan River Basin based on national land spatial planning using remote sensing statistics and the 2000–2020 statistical yearbooks for the Mulan River Basin. A landscape index is applied to explore this landscape in terms of its production–living–ecological space (PLES) patterns and evolutionary characteristics. Factors affecting the drivers of PLES changes are analyzed through Geo-Detector, and predictions are made using the cellular automata Markov (CA-Markov) model. It was found that (1) PLES distribution patterns in the Mulan River Basin from 2000 to 2020 are dominated by non-watershed ecological spaces, with a significant expansion of living space. Its ecological space is shrinking, and there is significant spatial variation between its near-river and fringe areas. (2) Of the PLES conversions, the most dramatic conversions are those of production space and living space, with 81.14 km2 of production space being transferred into living space. Non-water ecological space and water ecological space are also mainly transferred into production space. (3) As shown by the results of the landscape index calculation, non-water ecological space in the Mulan River Basin is the dominant landscape, the values of the Shannon diversity index (SHDI) and Shannon homogeneity index (SHEI) are small, the overall level of landscape diversity is low, the aggregation index (AI) is high, and the degree of aggregation is obvious. (4) The progressive PLES changes in the Mulan River Basin are influenced by a combination of natural geographic and socioeconomic factors, with the mean population density and mean elevation being the most important factors affecting PLES changes among social and natural factors, respectively. (5) The Kappa coefficient of the CA-Markov model simulation is 0.8187, showing a good simulation accuracy, and it is predicted that the area of water ecological space in the Mulan River Basin will increase by 3.66 km2 by 2030, the area of production space and non-water ecological space will further decrease, and the area of construction land will increase by 260.67 km2. Overall, the aquatic ecological space in the Mulan River Basin has made progress in terms of landscape ecological protection, though it still faces serious erosion. Therefore, attaching importance to the restoration of the water ecological space in the Mulan River Basin, integrating multiple elements of mountains, water, forests, fields, and lakes, optimizing the spatial structure of its PLES dynamics, and formulating a reasonable spatial planning policy are effective means of guaranteeing its ecological and economic sustainable development. This study offers recommendations for and scientific defenses of the logical design of PLES spatial functions in the Mulan River Basin.

New criteria for sustainable land use planning of metropolitan green infrastructures in the tropical Andes

ContextUrbanization is rapidly increasing worldwide, with about 60% of the global population currently residing in cities and expected to reach 68% by 2050. In Latin America's tropical Andes region, managing these changes poses challenges, including biodiversity loss and vulnerability to climate change.ObjectivesThis study assesses urban growth and agricultural intensification impacts on the ecological functionality of metropolitan green infrastructures and their capacity to provide ecosystem services using a landscape sustainability and sociometabolic approach. Specifically, it aims to identify landscape configurations promoting socio-ecological sustainability amidst rapid urbanization.MethodsA landscape-metabolic model (IDC) was applied to evaluate the interactions between land use changes and ecosystem functions in the metropolitan region of Cali.ResultsAgricultural intensification and industrialization, coupled with uncontrolled urban growth, have significantly transformed the landscape, posing threats to its sustainability. The prevailing biocultural landscapes hold a substantial potential to provide essential ecosystem services to the metropolis. The IDC offers an approach that utilizes a land cover map and agricultural production/metabolism data to calculate an indicator closely related to ecosystem services and multifunctionality.ConclusionsThe IDC model stands out for efficiently capturing landscape dynamics, providing insights into landscape configuration and social metabolism without extensive resource requirements. This research highlights the importance of adopting a landscape-metabolic and green infrastructure framework to guide territorial policies in the tropical Andes and similar regions. It stresses the need for informed land use planning to address challenges and leverage opportunities presented by biocultural landscapes for regional sustainability amidst rapid urbanization and agricultural expansion.

The Detection of Past and Future Land Use and Land Cover Change in Ugam Chatkal National Park, Uzbekistan, Using CA-Markov and Random Forest Machine Learning Algorithms

This comprehensive study investigates land use and land cover (LULC) changes in Ugam Chatkal Na-tional Park, Uzbekistan, over a 30-year period from 1993 to 2022 with Landsat satellite images. Utili-zing advanced CA-Markov and Random Forest machine learning algorithms, it meticulously analyzes historical data to understand past trends and projects future LULC changes. According to remote sen-sing analysis of the past, our findings show the sharp decline of glacier land cover from 2105 km2 to 1334 km2 in the Ugam Chatkal National Park, replaced by tree cover (from 327 km2 in 1993 to 450 km2 in 2022), rangelands (1259 km2 in 1993 to 1355 km2 in 2020), and rocks (from 834 km2 in 1993 to 1390 km2 in 2022). Agriculture, water and bare land witnessed some fluctuations but did not change significantly. At the same time, the region experienced some urbanization, raising the urban area from 50 km2 in 1993 to 90 km2 after 29 years. The article suggests three possible scenarios for the future of the region: “hard”, “soft” and “bad” scenarios. Land cover change predictions are done in TerrSet software with the CA-Markov model for four decades: 2035, 2045,2055 and 2065. Hard and soft sce-narios predict similar patterns for the future: a decline in glacier cover and a rise of tree cover, rock and rangelands, with a slight increase in agriculture and urban classes. Whereas “bad” scenario, which incorporates rapid urbanization and agricultural expansion for the study area, forecasts a climb of the urban area until 415 km2 (8% of the territory) until 2065, and 286 km2 for agriculture.

Efficiency and greenness evaluation of urban land use change in the Yangtze River Economic Belt, China

AbstractImproving urban land use efficiency and greenness is essential for achieving sustainable urban development and improving the well‐being of urban settlements. Using satellite‐based land use data, socioeconomic data, and sustainable development goal (SDG) indicators, we quantified the changes in the urban land use efficiency and greenness under rapid urban expansion in provincial cities in the Yangtze River Economic Belt (YREB) from 1990 to 2020. Over this period, urban area increased significantly, by 254.57%, at a rate of 191.41 km2 per year in the YREB, as national macro‐policies shifted the center of urban expansion westward. Nevertheless, the urban land use efficiency and greenness have both increased. The ratio of land consumption rate to population growth rate increased from 0.55 in 1990–2000 to 0.83 in 2010–2020 in the YREB, accompanied by an increase in the investment output ratio of fixed assets. In addition, the population‐weighted greenspace exposure increased by 5.31%, due to an 8.16% increase in the urban greenspace coverage, which improved the urban living environment amidst substantial urban population growth. We emphasize the importance of fostering coordinated development between central and western cities in the YREB. The results provide an important reference for the rational allocation of land resources, improving land use efficiency, and building resilient cities within global urbanization hotspots under the SDG framework.

Urban greening as a sustainable solution to heat stress in tropical cities: a case study of Monrovia in Liberia

Urbanization and climate change pose significant challenges to cities worldwide, increasing heat stress issues. Monrovia, Liberia, is currently undergoing rapid urban expansion, which exacerbates the urban heat island (UHI) phenomenon. Consequently, this raises the risk of heat stress, including adverse health effects and higher energy demands. The objective of this study is to present a comprehensive overview of Monrovia, with a specific focus on addressing/analyzing its urban greening initiatives and evaluating their effectiveness in mitigating the challenges posed by heat stress. A critical Evaluation was also conducted on the existing urban greening initiatives in Monrovia and its effect on land usage. To achieve this, comprehensive analysis methods, such as green infrastructure assessment and examination of satellite imagery, are employed. The data utilized for this study is collected from a comprehensive network centered around a single station, namely Roberts International Airport. This study aims to provide evidence-based insights into the potential of urban greening as a sustainable strategy to mitigate heat stress in tropical urban environments. Additionally, the research aims to offer recommendations for optimizing and implementing urban greening initiatives to enhance Monrovia's resilience against rising temperatures and urbanization.

Revealing the urban heat Island: Investigating spatiotemporal surface temperature dynamics, modeling, and interactions with controllable and non-controllable factors

The unchecked growth of urban populations has spurred rapid and unsustainable urban expansion, exacerbating environmental degradation both locally and globally. This research offers a comprehensive analysis of the Urban Heat Island (UHI) phenomenon in Bangalore and Hyderabad, India, focusing on its spatial and temporal distribution and its correlation with air pollutants. Conducted over the course of summer and winter seasons from 2001 to 2021, this study advances our understanding of UHI dynamics in rapidly urbanizing regions, shedding light on the complex interplay between urbanization, climate, and air quality. The primary objective of this study is to assess and compare the predictive performance of baseline Random Forest (RF) and Extreme Gradient Boosting (XGBoost) models for forecasting Land Surface Temperature (LST) in Hyderabad, India, while examining the impact of integrating spatial information into these models. Incorporating an extensive array of input variables, ranging from spectral indices to terrain features, land use/land cover (LULC) data, atmospheric parameters, and spatial data, the analysis reveals significant relationships between LST and various factors. Notably, Aerosol Optical Depth (AOD) and Normalized Difference Built-up Index (NDBI) exhibit strong positive correlations with LST, while Enhanced Vegetation Index (EVI) demonstrates a pronounced negative correlation. Similarly, Modified Normalized Difference Water Index (MNDWI) displays the strongest positive correlation with LST (r = 0.49), whereas EVI exhibits the most notable negative correlation (r = −0.67). Additionally, Modified Bare Soil Index (MBI) demonstrates a noteworthy negative correlation (r = −0.48) with LST for Bangalore. Atmospheric components such as CO, NO2, and O3 also show significant positive correlations with LST, with NO2 displaying the highest correlation during winter in urban areas. XGBoost emerges as the superior model, achieving high R2 values of 0.84 for Bangalore and 0.88 for Hyderabad. Integration of spatial information consistently enhances the performance of both RF and XGBoost models, resulting in reduced Mean Squared Error (MSE) and Root Mean Squared Error (RMSE) values. However, predictions over water bodies tend to be underestimated. The study underscores the importance of incorporating spatial data for accurate LST prediction, with implications for environmental monitoring and management. Despite the advancements made, further research is needed to elucidate the specific mechanisms through which spatial information improves model performance, suggesting avenues for future investigation and refinement of modeling methodologies. At the intersection of rapid urban growth and environmental conservation, these findings are poised to inform policymakers, urban planners, and researchers, guiding them towards innovative and sustainable urban development strategies aimed at mitigating the adverse impacts of rapid urban expansion while promoting ecosystem well-being. The study contributes to spatial modeling strategies and refines LST prediction methodologies, offering valuable insights for addressing the challenges posed by urbanization and climate change in rapidly urbanizing regions.

Production and reconstruction mechanism of consumption spaces in urban fringe areas under capital intervention: Evidence from Guangming town in Shenzhen

As the rapid urban expansion and the rise of consumer society, urban fringe areas have become an essential place for urban capital to intervene and achieve spatial regeneration, and it has triggered the consumerization and transformation of space. Taking Guangming Town in the urban fringe area of Shenzhen as an example, this paper reveals the process and dynamics of spatial consumerization transformation under the influence of capital intervention. It examines the intricate mechanisms of capital operation underlie the production of space, and endeavors to explore a novel model of rural spatial regeneration in China's urban fringe areas. This paper found that the production of space in Guangming Town under the capital intervention includes the material production and social relations production. With the reconstruction of spatial form and relationships, new local products, spatial configuration, social services and organizational relations are generated, forming a consumption space with heterogeneous landscape, market institutionalized management, commercialization and symbolization. The realization of the production of consumption space in urban fringe areas is based on the joint action of core elements such as land, capital and government, which provide the material foundation, operational power and coordination organization for space consumption. These promote capital to complete the triple cycle of “acquiring land - creating space scarcity - realizing space consumption”, and then realizing space reproduction and capital appreciation. In the Chinese context, the spatial transformation and production of urban fringe areas should not be regarded as a local practice of Western counter-urbanization or rural gentrification theory. Rather, it as a new spatial regeneration mode that harmonizes urban and rural production, lifestyles and development trajectories. This paper offers valuable practical insights and analytical perspectives for promoting integrated urban-rural development and fostering a new type of urbanization, thereby broadening the regional framework of rural development.

How does rapid urban construction land expansion affect the spatial inequalities of ecosystem health in China? Evidence from the country, economic regions and urban agglomerations

Identifying the adaptation mechanisms between urban construction land expansion (UCE) and ecosystem health (EHI) is a crucial aspect of sustainable management. However, there is still progress room for existing studies in distinguishing the impact mechanisms of UCE on the EHI of China's cities, different economic subregions and urban agglomerations. These gaps hinder the development of differentiated supportive frameworks for urban land management policies and ecosystem restoration initiatives across various scales in China. This study integrated multivariate satellite remote sensing data to monitor the heterogeneous evolution patterns of EHI and UCE in Chinese cities, economic subregions and urban agglomerations. A set of spatial measure models are utilized to distinguish the variability impact of UCE on China's EHI from a multi-dimensional perspective, including global and local, whole-area and sub-area, and direct and indirect influences. The results indicate that as UCE continues to grow, EHI steadily declined, reaching 0.512 with an average annual decrease of 1.507% from 2000 to 2020. A diminishing cluster pattern of EHI was observed, primarily concentrated in urban agglomerations such as BTH, GBA, and YRD. UCE exhibited a significant negative spatial dependence on EHI, and both global and local perspectives, UCE had a gradually weakening negative effect on the EHI of Chinese cities and economic subregions. However, the impacts of UCE on EHI in mature urban agglomerations (e.g., GBA, BTH, and YRD) were dominated by spatial spillovers, whereas growing urban agglomerations (e.g., MRYRU and CCU) were more affected by direct shocks from UCE. Our investigation informs site-specific ecologically sustainable management strategies in China based on cross-scale analyses, providing new perspectives into establishing cooperative mechanisms for cross-regional ecological management while emphasizing ecological risks management under the integration of urban agglomerations.

Design and optimization of haze prediction model based on particle swarm optimization algorithm and graphics processor

With the rapid expansion of industrialization and urbanization, fine Particulate Matter (PM2.5) pollution has escalated into a major global environmental crisis. This pollution severely affects human health and ecosystem stability. Accurately predicting PM2.5 levels is essential. However, air quality forecasting currently faces challenges in processing vast data and enhancing model accuracy. Deep learning models are widely applied for their superior learning and fitting abilities in haze prediction. Yet, they are limited by optimization challenges, long training periods, high data quality needs, and a tendency towards overfitting. Furthermore, the complex internal structures and mechanisms of these models complicate the understanding of haze formation. In contrast, traditional Support Vector Regression (SVR) methods perform well with complex non-linear data but struggle with increased data volumes. To address this, we developed CUDA-based code to optimize SVR algorithm efficiency. We also combined SVR with Genetic Algorithms (GA), Sparrow Search Algorithm (SSA), and Particle Swarm Optimization (PSO) to identify the optimal haze prediction model. Our results demonstrate that the model combining intelligent algorithms with Central Processing Unit-raphics Processing Unit (CPU-GPU) heterogeneous parallel computing significantly outpaces the PSO-SVR model in training speed. It achieves a computation time that is 6.21–35.34 times faster. Compared to other models, the Particle Swarm Optimization-Central Processing Unit-Graphics Processing Unit-Support Vector Regression (PSO-CPU-GPU-SVR) model stands out in haze prediction, offering substantial speed improvements and enhanced stability and reliability while maintaining high accuracy. This breakthrough not only advances the efficiency and accuracy of haze prediction but also provides valuable insights for real-time air quality monitoring and decision-making.

The identification and efficiency evaluation of industrial parcels by integrating multi-source spatial data in Shenzhen, South China

ABSTRACT Industrial land status, encompassing quantity, distribution and efficiency, is pivotal in urban planning and sustainable development. However, obtaining detailed and up-to-date industrial land maps poses a significant challenge in many developing countries due to rapid urban expansion. Furthermore, the identification and efficiency assessment of industrial land at the parcel scale are rarely undertaken. To address these challenges, our study proposes an innovative approach to map industrial land, categorize its types and assess its efficiency at the parcel scale. We select Shenzhen, one of China’s largest industrial cities, as a case study to demonstrate the effectiveness of our method. Our results unveil several key findings: (1) Shenzhen’s urban area was meticulously segmented into 15,591 multi-size socio-economic parcels, of which 5,738 were identified as industrial parcels (IPs); (2) IPs were further categorized into three distinct types: office industrial parcels at 69.47%, manufacturing industrial parcels at (6.08%) and comprehensive industrial parcels at 24.45%; (3) Their efficiency was classified into four levels: low (20.30%), middle (35.73%), fine (35.97%) and high (8.00%). Efficient IPs were predominately concentrated in the southwest, whereas other IPs clustered in the northwest. Our findings can provide valuable insights into industrial land identification, classification and efficiency evaluation at parcel scale.

River system changes under urban expansion: Insights from the Suzhou-Wuxi-Changzhou metropolitan area, China

Study regionThe Suzhou-Wuxi-Changzhou (SWC) metropolitan area, China. Study focusUrban expansion is a natural product of growing cities at the expense of river systems. In this study, we evaluated river system changes that come with urban expansion on a grid scale. We also utilized the spatial analysis models to examine the impact of urban expansion on river system changes. New hydrological insights for the regionOur results indicate that the cities in the metropolitan area had a similar pattern of urban expansion from the 1960s to the 2010s, with Changzhou, Wuxi, and Suzhou losing 45.8%, 32.3%, and 42.2% of their rivers, respectively. A negative correlation was detected between the urban expansion area (UEA) and the river density variation (∆Rd). During the rapid urban expansion period, ∆Rd significantly decreased as UEA increased. We then identified the spatial dependence and spatial spillover effect between river system changes and urban expansion. In our analysis, the river density was degraded as a result of urban expansion both in the in-situ location and in the neighboring locations. The river system has seen significant changes due to the impervious areas and infrastructures caused by urban expansion; thus, an appropriate pattern of urban development is required to mitigate the negative effects of river loss.

Study on the Spatiotemporal Evolution of Urban Land Use Efficiency in the Beijing–Tianjin–Hebei Region

The Beijing–Tianjin–Hebei region (BTH) is one of the crucial areas for economic development in China. However, rapid urban expansion and industrial development in this region have severely impacted the surrounding ecological environment. The air quality, water, and soil resources face significant pressure. Due to the close relationship between land utilization, population, investment, and industry, effective land use is a key factor in the coordinated development of the region. Therefore, clarifying the patterns of urban land use change and revealing its influencing factors can provide important scientific evidence for the coordinated development of the BTH region. This study aims to improve urban land use efficiency (ULUE) in the BTH region. Firstly, based on the input and output data of land elements for the 13 cities in the BTH region, the Data Envelopment Analysis (DEA) method is used to quantify the ULUE of the BTH urban agglomeration and analyze the spatiotemporal characteristics of ULUE. Input indicators includes capital, labor, and land. Output indicators includes economy, society, and environment. The results show that the overall ULUE in the BTH region has increased, albeit with notable fluctuations. Between 2000 and 2010, ULUE rose swiftly across all cities except Beijing and Tianjin, where changes were minimal. Post-2010, cities exhibited varied trends: steady growth, slow growth, sustained growth, step-wise growth, and initial growth followed by decline. Spatially, before 2010, the BTH showed a “high in the northeast and low in the southwest” pattern, transitioning post-2010 to a smoother “core-periphery” pattern. Mid-epidemic, high ULUE values reverted to the core area, shifting southward post-epidemic. Secondly, panel data analysis is conducted to explore the factors influencing ULUE. The results indicate that fiscal balance, the level of openness, the level of digitalization, industrial structure, and the level of green development are significant factors affecting ULUE. Finally, strategies are proposed to improve ULUE in the BTH region, including national spatial planning, industrial layout, existing land use, infrastructure construction, optimization of local fiscal revenue, and improvement in the business environment, aiming to enhance ULUE and promote the coordinated development of industries in the BTH region.

Scenario-based statistical analysis for PM2.5 concentration: A case study of Seoul, South Korea

Rapid urban expansion and active economic development significantly contribute to increased levels of PM2.5, which degrades the urban environment. This study aims to establish a foundation for practical policy guidance on the impact of urban factors on PM2.5 concentrations in Seoul, South Korea. To achieve this objective, we utilized various urban factors, including socio-demographic data, three-dimensional urban geometry, land use, and traffic volume, in conjunction with PM2.5 concentrations estimated by satellite images. According to our statistical models, all urban development-related factors, except for Forest and Open Space (FOS), showed a statistically significant increase in PM2.5 concentration. However, FOS demonstrated an effective mitigation capability, with a 1% increase in FOS corresponding to an approximate 5% decrease in PM2.5 levels. In addition, five scenario analyses based on statistical results were conducted to evaluate the potential reduction of PM2.5 and associated spatial implications resulting from the removal of batching plants, decreased traffic volume, and the substitution of transportation network with green spaces in Seoul. They highlighted the importance of reducing traffic and increasing green spaces in order to lower PM2.5 levels. The findings suggest that a multifaceted strategy is necessary to develop efficient policies for mitigating PM2.5 for a sustainable environment.

The role of boarding houses in the urban housing system funds of Moscow at the turn of the XIX–XX centuries

The subject of this study is apartment buildings in Moscow during the turn of the 19th and 20th centuries, and their significance in the context of the urbanization and industrialization of the city. The research aims to investigate the architectural features, functional characteristics, and socio-economic impact of these apartment buildings on the urban landscape. Special attention is paid to the quantitative and qualitative growth of these structures, as well as their contribution to addressing the issue of housing shortages in light of rapid urban population expansion. The focus of the study is on apartment buildings in Moscow during this period. The article examines specific examples of these buildings, their architectural design, construction stages, ownership, and occupancy. Attention is given to analyzing how these buildings were integrated into the city's infrastructure and influenced Moscow's appearance. The research employs diachronic, statistical, and chronological methods. The novelty of this study lies in its exploration of the previously understudied history of apartment houses in Moscow from a financial, economic, and social perspective. Apartment buildings played a significant role in Moscow's urban life. On the one hand, they provided housing for different segments of the population, making housing more accessible and helping to solve the problem of housing shortages. It was common to rent a room or apartment. On the other hand, apartment buildings became not only a social, but also an economic phenomenon. They were attractive for investing capital and contributed to their proliferation. The success of constructing such buildings led to the formation of joint-stock companies that focused on building apartments. These companies invested in real estate projects, expecting to generate significant profits from renting out apartments. The emergence of these companies indicates that the residential real estate market was a lucrative business.

Soil Adjusted Vegetation Index, Normalize Difference Buildup Index, and Land Surface Temperature between 1987 and 2023 in Abuja Municipal Area Council, Nigeria

Abuja Municipal Area Council (AMAC) is experiencing rapid urban expansion, which is expected to impact land surface temperatures (LST). This paper evaluates the trends in soil adjusted vegetation index (SAVI), normalize difference buildup index (NDBI), and land surface temperature (LST) between 1987 and 2023 in AMAC using Landsat 4 Thematic Mapper and Landsat 8 Operational Land Imager/Thermal Infrared Sensor imagery, respectively. Results show that in 1987, SAVI ranged from -0.126 to 0.477, NDBI from -0.186 to 0.678, and LST from 27.18 to 46.4 oC. In 2023, SAVI ranged from -0.253 to 0.71, NDBI from -0.308 to 0.619, and LST from 23.89 to 46.57 oC. Analysis showed an increase in vegetation in 2023 compared to 1987. Built-up and bareland areas became more concentrated in the northeast in 2023 compared to 1987, and temperature reductions were observed in areas with increased vegetation, notably in the south and southwest. Correlation analysis indicated a strong negative relationship (-0.772) between SAVI and LST in 1987, weakening in 2023 (-0.389). NDBI and LST remained moderately positively correlated (0.645 in 1987, 0.621 in 2023). Significant differences (P<0.01) were observed between 1987 and 2023 SAVI, NDBI, and LST values. These findings have important implications for environmental monitoring, and urban planning in rapidly urbanizing areas such as AMAC

Fluid Diplomacy: Managing water disputes in South Asia

Water disputes in South Asia represent complex challenges stemming from competing demands, population growth, climate change impacts, and geopolitical tensions. This study examines the multifaceted nature of water conflicts in the region, focusing on transboundary rivers such as the Indus, Ganges, and Brahmaputra, which serve as lifelines for millions of people across borders. It explores the historical context of water disputes in South Asia, tracing their origins to colonial-era water management practices and contemporary factors such as rapid urbanization and agricultural expansion. It analyzes the geopolitical dynamics underlying water conflicts, highlighting issues of sovereignty, power asymmetries, and the role of hydro-diplomacy in fostering cooperation. Moreover, the research focuses on the environmental implications of water disputes, including ecosystem degradation, biodiversity loss, and climate change vulnerability. Despite these challenges, the abstract identifies opportunities for collaborative solutions, emphasizing the importance of international mediation, legal frameworks, and sustainable water management practices. By fostering dialogue, trust-building, and equitable resource allocation, South Asian countries can work towards resolving water disputes and promoting regional peace, stability, and prosperity.

Impact of Urban built-up volume on Urban environment: A Case of Jakarta

In this paper, the spatial patterns of urban form (e.g., 2D and 3D characteristics) from 2000 to 2020 in Jakarta are assessed and the interdependent relationships between urban built-up volume and urban environment are examined. Jakarta experienced rapid urban built-up land expansion of 19 %, from 483 km2 in 2000 to 574 km2 in 2020 but with moderate urban built-up volumetric expansion at 4 %, from 23.6 × 108 m3 in 2000 to 24.5 × 108 m3 in 2020. The inverse S-shaped function revealed that urban land density declined from the city center to surrounding areas in Jakarta. Urban built-up area expanded outward at a much faster rate than upward, reflected by the D value, i.e., the radius of the central city area. The D value remained around 17 km from 2000 to 2020 for 3D but grew substantially from 28 km to 50 km for 2D during the same period. Furthermore, structural equation model (SEM) analysis showed that, while increases in urban built-up volume are associated with increases in urban green space, with a path coefficient of 0.620, they also are linked with worsening air pollution and urban heat islands, with statistically significant path coefficients of 0.304 and 0.440, respectively.

River–Spring Connectivity and Hydrogeochemical Processes in a Karst Water System of Northern China: A Case Study of Jinan Spring Catchment

Frequent surface water–groundwater interactions and prevalent anthropogenic inputs make karst water systems vulnerable to human disturbance. As a typical karst region in North China, the Jinan Spring Catchment has become increasingly threatened due to rapid population growth and urban expansion. In this study, the local river–spring interaction and its interference with the hydrogeochemical evolution of groundwater are evaluated based on water stable isotopes and hydrochemistry. Twenty-two karst groundwater, eleven Quaternary pore water, sixteen spring water, and thirty-two surface water samples were collected during low- and high-flow conditions over the course of a year. The isotopic signatures of four different water types display significant differences, reflecting the recharge–discharge relationship of the karst water system. Mountainous springs feature lighter isotopes, whereas urban springs have significantly heavier isotopes. The result of end-member mixing analysis shows that the surface–groundwater interaction varies spatially and temporally within the spring catchment. Urban springs receive considerable replenishment from the surface water, especially after rainy episodes (up to 50%), while mountainous springs show little hydraulic dependence on surface water leakage (4~6%). Local mineral dissolution (including calcite, dolomite, gypsum, and halite), CO2 dissolution/exsolution, and cation exchange are the main hydrogeochemical processes constraining water chemistry in the spring catchment. The deterioration of water quality can be attributed to anthropogenic influences involving the discharge of domestic effluents, agricultural activities, and irrigation return flow. The findings of this work can improve our understanding of the complex karst water system and serve as a reference for sustainable groundwater management in other karst areas of northern China.

GIS-Enabled Multi-Criteria Assessment for Hospital Site Suitability: A Case Study of Tehran

In developing countries, the interaction between rapid urban expansion and population growth brings forth a host of challenges, particularly concerning essential services like healthcare. While interest in site suitability analysis for identifying optimal hospital locations to ensure equitable and secure healthcare access is on the rise, the absence of a holistic study that encompasses social and environmental aspects in the assessment of hospital site suitability is evident. The objective of this research is to introduce a hybrid methodology that combines Geographic Information Systems (GIS) with Multi-Criteria Decision-Making (MCDM) weighting methods. This methodology aims to create hospital site suitability maps for districts 21 and 22 in Tehran, taking into account socio-environmental factors. In addition to the conventional Analytical Hierarchical Process (AHP) weighting method, this study employs two relatively less-explored methods, the Best-Worst Method (BWM) and Step-wise Weight Assessment Ratio Analysis (SWARA), to enhance the analysis of hospital site suitability. In the SWARA method, there are minimal variations in weights among criteria, indicating that all socio-environmental factors (e.g., distance from existing hospitals, distance from main roads, distance from green spaces) hold significant importance in the decision-making process. Additionally, the findings indicate that the western part of the study area is the most suitable location for the construction of a new hospital. To achieve the average hospital bed availability in Tehran, an additional 2206 beds are required in the studied area, in addition to the existing facilities. Considering the ongoing urban development, population growth, and the potential for natural disasters and epidemics, it becomes essential to enhance the healthcare system by increasing the number of hospitals and available hospital beds. The sensitivity analysis showed that GIS-based SWARA-WLC was the most suitable and stable model for determining hospital site suitability in the study area. This methodology can be adapted for use in other regions and further improved by incorporating additional criteria. In conclusion, the study recommended three specific alternative sites for establishing a new hospital in the study area.