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The objective of this research was to examine the influence of urban configuration on the mitigation of land surface temperature (LST) and the prediction of land use and land cover change through the utilization of convolutional neural network modeling. The results indicate that the formation of different urban heat island patterns is significantly influenced by both urban geometry and land use land cover (LULC) types. However, there is no significant correlation between these factors and LST across all configuration metrics. The associations between landscape configuration and land cover types exhibit variability contingent upon the particular forest cover categories under examination. Furthermore, the application of predictive LULC mapping reveals a divergent pattern, characterized by a rise in the overall extent of vegetation but a decline in the inner context of the Shiraz metropolitan area. The projected trajectory of built-up areas indicates a continued trend of urban expansion. The unique landscape patterns are a result of the distinct characteristics of each LULC. According to recommendations, to address the issue of mean LST, it is advisable for urban landscape planning to give priority to cohesion, density, and continuity while simultaneously minimizing fragmentation, variability, and complexity. Practical Applications: This research provides valuable insights into the following aspects for urban planners, policymakers, and practitioners to address the following. (1) Selecting appropriate landscape metrics: this study identifies suitable landscape metrics to represent and interpret different landscape structures and land use land cover changes (LULCCs) over time. (2) Understanding regional variations: this research highlights that different landscape metrics have distinct effectiveness in different regions. This knowledge helps urban planners and policymakers to tailor their strategies and interventions based on specific regional characteristics, ensuring more effective mitigation of the urban heat island effect. (3) Different correlations with configuration metrics: this study reveals that the correlations between landscape configuration and LST differ in land cover types. (4) Anticipating future changes: this research utilizes machine learning models to predict future LULCC and landscape metrics. This information is valuable for urban planners and policymakers in anticipating and preparing for future urban expansion and changes in vegetation areas. It enables them to proactively design and implement strategies to manage the surface urban heat island effect. Urban planners and policymakers can utilize these insights to develop comprehensive strategies that integrate land-use design, landscape configuration, and urban form to mitigate the negative impacts of urbanization. [ABSTRACT FROM AUTHOR]

Surface waters are essential for meeting the needs of the world. In many regions, stream water quality is a major concern due to contamination from multiple sources. Stream water is also susceptible to climatic events and land-use practices influencing its catchment. Understanding the impact of such events on stream water quality is crucial for managing and protecting aquatic ecosystems and providing safe drinking water to communities that rely on these streams. Hence, monitoring and evaluating stream water quality holds significance in identifying potential hazards and implementing suitable management strategies. In this paper, a novel effort was made to determine the relative feature importance of a set of watershed characteristics (precipitation, temperature, urban land use, agricultural land use, and forest land-use factors) on four important water quality parameters (WQPs): fecal coliforms (FC), turbidity, pH, and conductivity of the Upper Green River watershed, Kentucky, USA. Random forest (RF), an ensemble learning method, was used to predict the WQPs from the causal parameters and determine the feature importance characteristics of the four WQPs previously mentioned. This model demonstrated that precipitation and temperature are the most influential factors on FC, turbidity, and pH. Forest land use and temperature are the two most important factors for conductivity. The novel feature importance factors of the RF model have likewise been confirmed for each WQP. In modeling stream WQPs, the developed the RF model outperformed the artificial neural network (ANN) model. Using the RF model, we obtain regression coefficients of (0.93, 0.74, and 0.94) for pH in training, testing, and overall. We obtain regression coefficients of (0.60, 0.64, and 0.61) using the ANN model. ⁠⁠⁠⁠⁠⁠⁠Overall, the RF model was more effective than the ANN model in modeling stream WQPs. The model identified precipitation and temperature as the most influential factors on FC, turbidity, and pH, while forest land use and temperature were the most important factors in determining conductivity. It is also found that land use factors are important to improve the accuracy of WQPs predictions from climate variables. The results of this study can be used by authorities to better understand and control pollution at the watershed scale. [ABSTRACT FROM AUTHOR]

Exploring the regional differences and convergence of urban land green use efficiency (ULGUE) is of great significance for urban green development and the goal of carbon neutrality. Based on the panel data of 282 prefecture-level cities in China from 2006 to 2019, this paper uses the SBM-Undesirable model to calculate ULGUE in China, then uses Dagum Gini coefficient decomposition, coefficient of variation and panel data model to reveal the regional differences and convergence of ULGUE. The results show that ULGUE in China increased from 0.441 to 0.555 in 2006–2019. The number of cities in the medium–low efficiency range is dominant, accounting for more than 54%. There are differences in ULGUE among the three major regions, which shows the distribution pattern of west > east > central. ULGUE in China has significant spatial agglomeration characteristics, and its overall, intra-regional and inter-regional differences show a downward trend. Over-variable density is the main source of the overall difference, with an average contribution rate of 49.71%. ULGUE across the country and in the three regions of east, central and west in China exist significant σ convergence, absolute β and conditions β convergence. The research results are helpful to objectively evaluate ULGUE in China, and provide decision-making reference for promoting the green, low-carbon and sustainable use of urban land and achieving the goal of carbon neutrality. [ABSTRACT FROM AUTHOR]

In order to study the deep learning model of urban planning image data processing and health intelligent system, based on existing remote sensing image change detection methods, the author introduces and proposes the use of deep belief networks in deep learning to classify high-resolution remote sensing images and analyze urban expansion change detection. Compared with traditional methods, deep learning has the highest overall accuracy and Kappa coefficient. Deep learning has the highest producer accuracy and relatively low misjudgment rate, making it the most suitable for studying the trend of urban built-up areas. By calculating the information entropy of the image to predict the number of hidden layer nodes, the time for deep learning is greatly reduced. Under the same experimental conditions, the training time for each image can be shortened by 12 525 seconds has improved classification efficiency and made a significant contribution to research on urban expansion applications. Finally, the improved deep belief network was applied to classify and detect changes in the three phase remote sensing images of Beijing, and the urban expansion trend and characteristics of Beijing were analyzed. Provide technical reference and inspiration for urban planning and land use protection. [ABSTRACT FROM AUTHOR]

Located in the southwest of Jakarta, Pagedangan has been known as one of the hotspots for large-scale residential complexes or 'new town' in the Jakarta Metropolitan Area, Indonesia. By using a diachronic approach, we aim to examine spatial transformations of rural Pagedangan at micro-scale from 1901 to 2022 which shows the trajectory of new-build gentrification in the study area. This study thoroughly examines how land conversion transforms the rural Pagedangan into gentrifying urban landscape using historical maps and multitemporal imageries. During the last decade, Pagedangan has experienced massive agricultural land conversion which increased land price in the area. It has become gentrified seen by the rise of new town's urban economy. Meanwhile, pre-existing irregular settlements, or kampungs, have remained as an assemblage of enclaves in a new town, a realm that completely differs from their previous rural environment. Despite displacement has not yet been the main issue in Pagedangan, kampungs are still possibly at risk of disappearance. This study delivers a comprehensive empirical study on physical gentrification process to provide insights into urban studies discourse, especially in urban Asia. This study proposes kampung as an important spatial entity which government should consider in Indonesian land use planning and urban policy making. [ABSTRACT FROM AUTHOR]

Unplanned urbanization continues to threaten the sustainability of cities in the global south. This study seeks to assess the urban planning response to the effects of sprawl on the urban form and land use pattern of Kumasi. The study relied on geospatial techniques to determine changes in land use patterns, landforms, and sprawl. A qualitative research approach was used to examine urban planning response to the causes and effects of urban sprawl in Kumasi. The results of this study show that the higher the urbanization rate, the more the built-up area increases, causing a significant loss of natural assets such as farmlands. In terms of shape, the research showed that the Greater Kumasi Metropolis has shifted from the historically monocentric city structure to a polycentric city. The city currently has multiple centers or subcentres for commercial, cultural, and social activities. In spite of all the threats posed by urban sprawl on the metropolis, there no clear policy intervention put in place to address the adverse effects of sprawl in the Greater Kumasi Metropolis. The researchers recommend that city authorities should adopt the compact city approach to control the high rate of sprawl to promote densification. [ABSTRACT FROM AUTHOR]

Introduction: Coastal areas are densely populated, economically developed, and form complex social-ecological systems. Any regional changes within these areas have profound consequences for their socio-economic development and ecological environments. Methods: Based on multi-source remote sensing image data, a detailed analysis of the coastline of the Ningbo-Taizhou-Wenzhou region (Yong-Tai-Wen region) from 1980 to 2020 was conducted, and the spatiotemporal changes of the coastline were analyzed. Regression analysis was employed to investigate the correlation between the coastline length and various factors, including the degree of industrialization, GDP, urban land, and arable land. Results and Discussion: The results show that: 1) From 1980 to 2020, the overall length of the coastline in the Yong-Tai-Wen region exhibited a decreasing trend, accompanied by a continual increase in the degree of artificial coastline. Consequently, the coastline became increasingly fragmented and tortuous. Notably, the intensity of coastline change fluctuated significantly, peaking in 2010. 2) At the regional scale, there is a strong negative correlation between the length of the coastline in the Yong-Tai-Wen region and GDP and land use, whereas the correlation with cultivated land area remains relatively low. Conversely, the proportion of human-made coastlines demonstrates a strong positive correlation with GDP and urban land use but a significant negative correlation with cultivated land area. 3) At the city scale, the length of the coastline in Ningbo shows a significant negative correlation with GDP while exhibiting a certain correlation with urban land use. Similarly, the coastline length in Taizhou also displays a strong negative association with both GDP and urban land use. In contrast, the correlation patterns observed in Wenzhou are opposite to those in Taizhou. Notably, the correlation between the length of the coastline and cultivated land area remains relatively weak across all three cities. Additionally, the proportion of artificial coastlines in Ningbo and Taizhou aligns with the overall trend in the Yong-Tai-Wen region. Specifically, the proportion of artificial coastlines in Wenzhou exhibits a positive correlation with GDP and urban land use and a negative correlation with cultivated land area. [ABSTRACT FROM AUTHOR]

The rapid expansion of informal settlements poses significant challenges to urban ecosystems and their services, a pressing issue that this study addresses by examining its impacts in Addis Ababa. This study delves into the impact of informal settlements on ecosystem services in Addis Ababa, comparing them with formal settlements. Utilizing geographic information systems (GIS) and remote sensing, it employed Landsat imagery, aerial photography, and base maps to track spatiotemporal changes and analyze trends. Through a GIS overlay approach, informal settlements and associated land use changes were identified, while the benefit transfer method assessed ecosystem service values. The findings revealed a significant increase in informal settlements on the city's outskirts, expanding from 77 ha in 2009 (2% of the total area) to 765.6 ha in 2023 (21% of the total area). Nearly half (48.5%) of these informal settlements were established on previously natural land covers through encroachment. The research highlighted the ongoing conversion of agricultural land, forests, and urban green spaces into informal settlements, particularly on the city's outskirts, leading to significant encroachment on these areas. This transformation caused an annual loss of $1,665,033.7 in ecosystem services from 2009 to 2023. Significant impacts were identified on food production, climate regulation, and habitat ecosystem services. Overall, the annual loss in ecosystem services due to land use changes amounted to $1,933,320.08. Informal settlements accounted for 86.1% of this total loss, highlighting the urgent need for targeted interventions to mitigate their disproportionate effects on ecosystem services. The study underscores the urgency of addressing the impact of informal settlements on ecosystem services through effective urban planning, sustainable land management practices, prevention of encroachment on natural land covers, and promotion of sustainable ecosystem management and utilization. [ABSTRACT FROM AUTHOR]

Land is inelastic in supply. The judicious use of land within the urban land space is thus critical. Regrettably, little research has been done on planning and managing public cemeteries in Kumasi, Ghana. This study, incorporating insights from four public cemeteries and feedback from 79 participants, assesses the legislative and policy frameworks governing cemetery management in Kumasi. It also examines the condition of these cemeteries and identifies the challenges to their proper upkeep. Data were gathered through structured interviews and direct observation and were analysed thematically. Findings indicate that cemetery management in Kumasi is a collaborative task between Traditional Authorities and the local government, each operating under their respective but similar laws. Some of these cemeteries need more essential facilities, making them substandard in their current state, primarily due to financial limitations that impede effective management. This study makes recommendations to guide the effective and sustainable management of public cemeteries in Kumasi and beyond. [ABSTRACT FROM AUTHOR]

In the context of accelerated urbanization, assessing the quality of the existing built environment plays a crucial role in urban renewal. In the existing research and use of deep learning models, most categories are urban construction areas, forest land, farmland, and other categories. These categories are not conducive to a more accurate analysis of the spatial distribution characteristics of urban green space, parking space, blue space, and square. A small sample of refined land use classification data for urban built-up areas was produced using remote sensing images. The large-scale remote sensing images were classified using deep learning models, with the objective of inferring the fine land category of each tile image. In this study, satellite remote sensing images of four cities, Handan, Shijiazhuang, Xingtai, and Tangshan, were acquired by Google Class 19 RGB three-channel satellite remote sensing images to establish a data set containing fourteen urban land use classifications. The convolutional neural network model EfficientNetV2 is used to train and validate the network framework that performs well on computer vision tasks and enables intelligent image classification of urban remote sensing images. The model classification effect is compared and analyzed through accuracy, precision, recall, and F1-score. The results show that the EfficientNetV2 model has a classification recognition accuracy of 84.56% on the constructed data set. The testing set accuracy increases sequentially after transfer learning. This paper verifies that the proposed research framework has good practicality and that the results of the land use classification are conducive to the fine-grained quantitative analysis of built-up environmental quality. [ABSTRACT FROM AUTHOR]

High spatio-temporal resolution estimates of electricity consumption are essential for formulating effective energy transition strategies. However, the data availability is limited by complex spatio-temporal heterogeneity and insufficient multi-source feature fusion. To address these issues, this study introduces an innovative downscaling method that combines multi-source data with machine learning and spatial interpolation techniques. The method's accuracy showed significant improvements, with determination coefficients (R2) increasing by 30.1% and 33.4% over the baseline model in two evaluation datasets. With this advanced model, we estimated monthly electricity consumption across 1 km x 1 km grid for 280 Chinese cities from 2012 to 2019. Our dataset is highly consistent with officially released electricity consumption of different industries (Pearson correlation coefficients within 0.83 - 0.91). Moreover, our data can reflect the electricity consumption patterns of different urban land uses compared to other datasets. This study bridges a significant gap in fine-grained electricity consumption data, providing a robust foundation for the development of sustainable energy policies. [ABSTRACT FROM AUTHOR]

This document provides a list of references to scientific articles and studies that explore various aspects of land use change and urban development in China and other regions. The articles cover topics such as modeling urban open spaces, simulating future land use scenarios, analyzing the impact of land use change on ecosystem services, and predicting land surface temperature under climate change scenarios. These articles offer valuable insights into the complex relationship between land use, urbanization, and environmental sustainability. [Extracted from the article]

Understanding the complex influencing factors of soil erosion is critical for maintaining regional ecological security. The revised wind erosion equation (RWEQ) and partial least squares regression (PLSR) model were used to reveal the primary factors affecting soil erosion. Based on the results of the RWEQ model, the wind erosion area was 8,439.3 km2 in 2018, accounting for 54.3% of the total planning area, and mild erosion, moderate erosion, intense erosion, very intense erosion, and fierce erosion accounted for 18.22%, 11.43%, 11.78%, 10.16%, and 2.74% of the total planning area, respectively. Based on the results of the PLSR model, the results indicate that the proportion of mining land, meteorological indicators, and mean square deviation of slope difference were positively correlated with the soil erosion area, intensity, and severity, respectively. The proportion of grassland and forest land was negatively correlated with the soil erosion area, intensity, and severity. The mean square deviation of slope difference, the mean square deviation of difference in elevation, and the proportion of urban land use contributed the most to the soil erosion severity index, with variable importance in projection (VIP) scores of 1.55, 1.44 and 1.43, respectively. The mean square deviation of slope difference, the proportion of urban land, and the mean square deviation of difference in elevation contributed the most to the soil erosion area, with VIP scores of 1.53, 1.26 and 1.24, respectively. The results provide new insights into wind erosion and the influences of weather conditions and human influences, which can guide regional soil and water conservation planning in wind erosion regions. [ABSTRACT FROM AUTHOR]

[Objective] The aims of this study are to explore the response of ecosystem service value (ESV) to land use change, and to improve the sustainability of ecosystem service function in central Guizhou. [Methods] In this study, urban agglomeration of central Guizhou was taken as an example. Statistical analysis and spatial autocorrelation method were used to assess the land use change and ESV spatial and temporal evolution characteristics of urban agglomeration of central Guizhou from 2000 to 2020, and the spatial pattern of land use and its ESV change under different development scenarios in 2030 was predicted by coupling with PLUS model. [Results] (1) The land use change in the study area from 2000 to 2020 was mainly manifested in the transformation of cropland and grassland to construction land and waters, and affected by the land use change, the ESV of the study area increased by 11.28 hundred million yuan from 2000 to 2020, showing a fluctuating upward trend, and the expansion of waters and construction land area was the main reason for the change of ESV in the study area. (2) The decrease area of ESV from 2000 to 2020 was mainly distributed in the center urban area with better economic development, and the increase area was mainly distributed near rivers, lakes and other waters. The spatial autocorrelation analysis showed that the high and low agglomeration areas in the study area were widely distributed and strongly clustered, with the high and high agglomeration areas mainly concentrated in the northwestern part of the study area and the low and low agglomeration areas mainly concentrated in the central part of the study area. (3) The ESV under the nature scenario, cropland protection and ecological protection scenarios in 2030 are 710.22 hundred million, 705.33 hundred million and 720.62 hundred million yuan, respectively, and the ecological protection scenario has an obvious positive effect on the growth of ESV in the study area. [Conclusion In the future. the urban agglomeration of central Guizhou can continue to strengthen the policy of returning farmland to forests to improve the value of ecosystem services in terms of ecological environment, and it should formulate a more reasonable and comprehensive development strategy in terms of urban development, which can take into account ecological protection while the economy develops. [ABSTRACT FROM AUTHOR]

The global population aging poses new challenges in allocating care facilities for the elderly. This demographic trend also influences economic development and the quality of urban life. However, current research focuses on the supply of elderly care facilities and primarily uses administrative divisions as a scale, resulting in low spatiotemporal sensitivity in evaluating the spatial equilibrium of elderly care facilities (SEECF). The relationship between the SEECF and economic development is not clear. In response to these problems, we proposed a spatial equilibrium model of elderly care facilities with high spatiotemporal sensitivity (SEM-HSTS) and explored the spatiotemporal associations between the SEECF and economic development. Considering the spatial accessibility rate of elderly care services (SARecs) and the spatiotemporal supply–demand ratio for elderly care services (STSDRecs), two types of supply–demand relationship factors were constructed. Then, a spatiotemporal accessibility of medical services (STAms) factor was obtained based on a modified two-step floating catchment area (M2SFCA) method. On this basis, the SEM-HSTS was constructed based on the theory of coordinated development. Further, a panel threshold model was employed to evaluate the influence relationships among population aging, SEECF, and gross domestic product (GDP) in different phases. Finally, spatial autocorrelation and Geodetector explored the spatial associations between SEECF and GDP across complex urban land use categories (ULUC). The experimental results at a 100-m grid scale showed that the SEM-HSTS exhibited higher spatiotemporal heterogeneity than the classical accessibility method, with elevated spatiotemporal sensitivity. Effectively identified various spatial imbalances, such as undersupply and resource waste. The panel model captured phased relationship changes, showing that SEECF had inhibitory and promotional effects on GDP in pre- and post-aging societies, with stronger effects as balance approached. Moreover, the combined interaction of ULUC and GDP had a more significant influence on SEECF than any individual factor, with GDP exerting a more significant influence. This study provides an empirical basis for creating resource-efficient elderly care facility systems and optimizing layouts. [ABSTRACT FROM AUTHOR]

We clarify the relationship between greening and gentrification by examining the sociospatial dynamics that characterize and drive "green gentrification." Through a conversation with the growing literature on green gentrification, we show that this relationship is nuanced and contingent upon contextual factors and we depict the exclusions at stake. In short, green gentrification is a process that generates urban green sacrifice zones, by which historically marginalized residents are forced away from greener neighborhoods, often segregated to greyer and climate-insecure areas, and which includes feedback loops of accelerated greening and exclusive investments. We conclude with future policy directions to address these green inequalities. [ABSTRACT FROM AUTHOR]

Urban land consumption negatively impacts ecosystem services such as food production, carbon regulation, and water absorption. Despite indications of densification in some large cities, evidence shows that built-up land has been increasing faster than population globally. However, existing research disproportionally focuses on large cities, overlooking intermediate and rural territories. Our study examines the trajectories of urban land consumption along the urban-rural gradient in France between 1975 and 2020. We quantify built-up land per capita (BPC) and the changes therein and compare it to a 7-level classification of territories according to their density. BPC increased 59%, combining a 95% increase in built-up land and a 23% population growth. Yet, BPC change varied considerably across the seven territory classes: very scattered rural areas experienced the largest growth (+190 m2) while large cities grew more efficiently (+11 m2). Intermediate territories, such as peri-urban areas and small cities, increased BPC by 65% and 78%, respectively. Our findings confirm the hypothesis of urban land use polarization, as rural areas were sparser than large cities in the base year, and this difference increased over time. This underlines the urgency to address the distinct land use trajectories for effective no net land take policies. [ABSTRACT FROM AUTHOR]

Land use can affect energy consumption by changing the economic and social structure of cities. Thus, the optimization of land use patterns is key to promoting energy sustainability. In this study, we explored the spatiotemporal evolution of China's urban energy consumption and its driving factors from the role of land use, with the application of high-precision nighttime light images and land use data acquired from remote sensing satellites. A deep clustering network in deep learning was used for clustering analysis of urban energy consumption. The results indicated that the economic and structural effects of land use were the primary driving factors of the increasing urban energy consumption, whereas the decrease in the energy intensity (caused by technological progress) restrained the growth rate of energy consumption. With the exception of economically developed cities, generally, the contribution of the population size to the temporal increase in energy consumption was relatively small. The spatial difference in urban energy consumption was mainly due to the between-group differences among the diversified cluster groups, which were strongly influenced by land urbanization and population size. These conclusions can help the Chinese government formulate differentiated urban energy policies. [ABSTRACT FROM AUTHOR]

Increasing population density leads to higher building density and significant alterations in urban land use and land cover (LULC). Particularly, the expansion of built-up areas substantially influences land surface temperature (LST), contributing to the formation of urban heat islands (UHI). This study aims to determine the relationship between UHI formations and the presence of urban grey infrastructure versus green spaces over a 22-year period. The research involves developing maps of NDVI, NDBI, LULC, LST, UHI, and UTFVI using Landsat 4–5 TM and 8–9 OLI/TIRS satellite images for the years 2000 and 2022. Data processing was conducted using ArcGIS Desktop and ERDAS Imagine, with results assessed in MATLAB and Excel. The findings reveal significant changes in NDVI, NDBI, and LST in the study area over time, highlighting the UHI effect characterized by a temperature increase of approximately 5–6 °C. Conversely, the UTFVI study indicated an improvement in ecological conditions in some areas by 2022 due to increased NDVI. This study underscores the importance of comprehensive land-use strategies to promote a sustainable and climate-resilient future for Chandigarh by mitigating the UHI effect through the enhancement of green vegetation in regions with rising LST. Furthermore, the LULC mapping accuracy is tested with an outstanding precision of 95%. [ABSTRACT FROM AUTHOR]

Urban perception is a multifaceted process, spanning from vision to cognitive interpretation. Earlier studies on urban perception assessment have primarily concentrated on the analysis of graphic features of street view images such as color or semantic elements, neglecting the vital human sensory fixation features in cognitive processes. This study leveraged eye-tracking technology to accumulate human visual attention data during emotion scoring of street view images. Additionally, a deep learning network model was proposed to forecast human visual attention areas by assimilating environmental features such as image color, depth, and semantic elements, and subsequently amalgamating the aforementioned environmental features and visual attention to establish a perception prediction model, capable of predicting urban perception on a larger scale. Finally, the reliability and superiority of the urban perception prediction method were confirmed through ablation experiments and bias analysis. On the one hand, the method enhances the prediction accuracy of urban perception; on the other, it investigates the comprehensive influence of multiple features on human subjective emotions from the external environment perspective and individual perspective. This approach transcends the former limited reliance on single-image features, providing a novel and scientific approach for assessing urban perception. [ABSTRACT FROM AUTHOR]

The promotion of community resilience is a multifaceted process that warrants further exploration. This article aims to contribute to this literature stream by assessing the role of citizen science (CS) approaches in the development of community resilience, since CS is considered a promising approach for generating new knowledge by fostering the participation of citizens (non-professional scientists) in research activities. The results show that CS approaches can contribute to community resilience at the institutional level, improving emergency and recovery planning capacity; at the infrastructural level, by contributing to land use planning and urban design; and at the social level, through the creation of community ties and social capital. This contribution is relevant for the development of public policies that are more shaped to local contexts and aligned with communities' needs and expectations. [ABSTRACT FROM AUTHOR]

Background: Urban areas are unique ecosystems with stark differences in species abundance and composition compared with natural ecosystems. These differences can affect pathogen transmission dynamics, thereby altering zoonotic pathogen prevalence and diversity. In this study, we screened small mammals from natural and urban areas in the Netherlands for up to 19 zoonotic pathogens, including viruses, bacteria, and protozoan parasites. Materials and Methods: In total, 578 small mammals were captured, including wood mice (Apodemus sylvaticus), bank voles (Myodes glareolus), yellow-necked mice (Apodemus flavicollis), house mice (Mus musculus), common voles (Microtus arvalis), and greater white-toothed shrews (Crocidura russula). We detected a wide variety of zoonotic pathogens in small mammals from both urban and natural areas. For a subset of these pathogens, in wood mice and bank voles, we then tested whether pathogen prevalence and diversity were associated with habitat type (i.e., natural versus urban), degree of greenness, and various host characteristics. Results: The prevalence of tick-borne zoonotic pathogens (Borrelia spp. and Neoehrlichia mikurensis) was significantly higher in wood mice from natural areas. In contrast, the prevalence of Bartonella spp. was higher in wood mice from urban areas, but this difference was not statistically significant. Pathogen diversity was higher in bank voles from natural habitats and increased with body weight for both rodent species, although this relationship depended on sex for bank voles. In addition, we detected methicillin-resistant Staphylococcus aureus, extended-spectrum beta-lactamase/AmpC-producing Escherichia coli, and lymphocytic choriomeningitis virus for the first time in rodents in the Netherlands. Discussion: The differences between natural and urban areas are likely related to differences in the abundance and diversity of arthropod vectors and vertebrate community composition. With increasing environmental encroachment and changes in urban land use (e.g., urban greening), it is important to better understand transmission dynamics of zoonotic pathogens in urban environments to reduce potential disease risks for public health. [ABSTRACT FROM AUTHOR]

The Western Taiwan Strait (WTS) Economic Zone connects the Yangtze River Delta and the Pearl River Delta, playing a significant role in China's coastal economy and forming part of the East Asian economic structure. This study used panel data from 20 cities in the WTS Economic Zone, spanning 2011 to 2020, to investigate urban land use efficiency and its dynamic evolution characteristics. The study used a super-efficiency EBM model, which accounts for undesirable outputs, combined with kernel density estimation and Malmquist–Luenberger (ML) index analysis, to thoroughly examine the changes in total factor productivity (TFP) of urban land use and the factors driving these changes within the WTS Economic Zone. The findings are as follows: (1) From 2011 to 2020, the overall trend of urban land use efficiency in the WTS Economic Zone was upward, with coastal areas generally exhibiting higher urban land use efficiency compared to inland areas. (2) The urban land use efficiency of cities in the WTS Economic Zone displayed four types of changes: rising, stable, "U"-shaped, and inverted "U"-shaped. (3) The TEP index of the WTS Economic Zone exhibited a right-leaning "M" trend. Technological change was the primary driver of enhanced urban land use efficiency, although there is still room for improvement in technical efficiency. Based on these findings, this study proposes policy insights to foster high-quality development of urban land use efficiency in the WTS Economic Zone. [ABSTRACT FROM AUTHOR]

Given the challenges of restricted land resources and net-zero carbon city initiatives, it is crucial to seek a balance between intensive land use and carbon neutrality during the construction of development zones. By incorporating net-zero carbon balance into the land use efficiency evaluation system and utilizing a quasi-natural experiment based on the 2009 provincial development zone upgrading policy, this study investigates the policy's impact on urban land use efficiency under the net-zero carbon city goal. The study finds that the upgrading of provincial development zones significantly enhances urban land use efficiency, while exhibiting the dual effects of reducing carbon emissions and increasing carbon sinks. Mechanism analysis reveals that the upgrade policy improves land use efficiency by enhancing land-use and environmental regulations, optimizing resource allocation, and fostering green technological innovation. Heterogeneity analyses show that the policy effect is more significant in eastern and central cities, with the impact being strongest in central cities. Additionally, the impact of upgrading to a national high-tech development zone is greater than that of upgrading to a national economic development zone. This article provides insights into how to use industrial policies effectively to achieve intensive land use and high-quality development while aiming for carbon neutrality. [ABSTRACT FROM AUTHOR]

Land use conflicts (LUCs) have become a significant global issue. Accurately identifying potential LUCs is crucial for mediating these conflicts, optimizing land use structure, and enhancing land use function. The necessary conditions of LUCs are land use multi-suitability (LUMS), land resource scarcity (LRS), and diversity of demands (DD). However, few studies have approached LUC identification from these three dimensions simultaneously. In addition, when assessing the diversity of demand, only human needs are considered and wildlife needs are ignored. In order to address this gap in the research, this paper constructs a novel framework for LUC identification and proposes an induction-oriented governance path. LUMS was evaluated from three aspects: construction suitability, cultivation suitability, and ecological suitability. LRS is measured from three dimensions: construction land, cultivated land, and ecological land scarcity. The DD is expanded into human and wildlife demand diversity. By analyzing the combination of LUMS, LRS, and DD, LUCs are classified using the potential LUC identification Rubik's cube model, and corresponding governance paths are suggested. In Shandong Province, potential LUCs are relatively high, with strong, medium, and weak conflicts accounting for 27.39%, 57.10%, and 13.06%, respectively. Potential strong conflicts are mainly distributed in the metropolitan suburbs and in the western plain of Shandong Province. Cultivated land is the main potential land use conflict space. The new framework of LUC identification proposed in this paper can effectively identify potential LUCs. Our research provides scientific reference for sustainable land use. [ABSTRACT FROM AUTHOR]

The evaluation of ecosystem service value (ESV) is crucial for decision making in regional sustainable development. The close relationship between ecosystem services and land use/cover change (LUCC) is well acknowledged. However, the impact of the mutual transformation among different land use types on the temporal and spatial differences in the ESV is still unclear. To fulfill this gap, this study evaluates the ESV in the Wuhan Urban Agglomerations based on LUCC, taking the spatiotemporal characteristics into consideration. The results show that (1) The land use structure in the Wuhan Urban Agglomerations has undergone great changes from 2012 to 2021, and the area of cultivated land converted to forest land is the largest, which may be related to policies such as returning farmland to forests. (2) The total amount of ESV shows a downward trend, and the spatial distribution of ESV is "low in the west and high in the central and eastern regions", which may be related to the natural factors in study area. (3) The spatial distribution of ESV in the study area will remain unchanged in the future. However, the transformation among land use types may exacerbate the reduction in the total ESV, which will have an adverse impact on the ecological environment and sustainable development of the region. This study initiates a more comprehensive framework to better reflect the real scenario of ESV, which will hopefully provide a reference for regional sustainable development. [ABSTRACT FROM AUTHOR]

Despite great interest in land use mix and the set of benefits that it supposedly provides, there still is a gap in the understanding of how land uses interact to promote urban vitality. This article examines land use from a temporal perspective, analysing both the frequency of visits throughout the day and the average duration of visits. The results show that even land uses in the same conventional functional category have different daily visitation patterns. Furthermore, the temporal combination and complementarity of some land uses seemed to directly influence the intensity and distribution of urban life. [ABSTRACT FROM AUTHOR]

Land use land cover (LULC) change, global environmental change, and sustainable change are frequently discussed topics in research at the moment. It is important to determine the historical LULC change process for effective environmental planning and the most appropriate use of land resources. This study analysed the spatial autocorrelation of the land use structure in Konya between 1990 and 2018. For this, Global and Local Moran's I indices based on land use data from 122 neighbourhoods and hot spot analysis (Getis-Ord Gi*) methods were applied to measure the spatial correlation of changes and to determine statistically significant hot and cold spatial clusters. According to the research results, the growth of urban areas has largely destroyed the most productive agricultural lands in the region. This change showed high spatial clustering both on an area and a proportional basis in the northern and southern parts of the city. On the other hand, the growth in the industrial area suppressed the pasture areas the most in the north-eastern region of the city, and this region showed high spatial clustering on both spatial and proportional scales. [ABSTRACT FROM AUTHOR]

This study aimed to assess the relationship between landscape characteristics and water quality in two distinct basins. Through the utilization of multiple stepwise regression analyses and redundancy analysis, the quantitative association between landscape metrics at both the watershed and riparian buffer scales was examined. The findings revealed that metrics at the riparian buffer scale exhibited greater effectiveness in predicting water quality compared to those at the watershed scale. At the 100-m buffer scale, specific variables such as forest edge density, and effective mesh size of urban areas in the Khorramabad basin, as well as forest aggregation index, urban edge density, and agricultural patch splitting in the Chalus basin, were identified as significant factors influencing water quality. In contrast, at larger scales, only metrics related to agriculture and urban land uses demonstrated dominance, indicating that these land-use classes play a decisive role in driving changes in water quality within the study areas. Moreover, as the scale increased, the influence of dominant variables on water quality exhibited a decreasing trend. Despite the minimal human activities observed in the Chalus basin, their impact on the quality of the Chalus River was substantial. Urban and agricultural land uses were consistently identified as dominant factors across all scales, suggesting that even a substantial amount of forest cover cannot fully mitigate the effects of human activities in a basin. This research underscores the significance of considering both the composition and configuration of the landscape when assessing water quality. [ABSTRACT FROM AUTHOR]

Land intensive use reflects the spatial structure, agglomeration characteristics, and internal mechanisms of urban economic, social, and ecological system development, significantly impacting urban resilience. Based on panel data from 287 cities in China from 2010 to 2020, this paper measures the levels of land intensive use and urban resilience, and empirically examines the impact mechanism of land intensive use on urban resilience through baseline regression and panel quantile regression. The results reveal that: (1) During the study period, China's urban land intensive use level has significantly improved. The land intensive use level shows a trend of "the strong become stronger, and the weak are always weak" and "high in the east and low in the west" spatial differentiation, while the urban resilience level showed a trend of accelerated "catching up" of low-resilience cities towards high-resilience cities and "high in the east and low in the west" spatial differentiation as well. (2) Land intensive use significantly promotes effect on urban resilience, and the effect depends on different conditions. (3) Among all dimensions of land intensive use, both land input intensity and land use benefits significantly promote urban resilience, while land use intensity shows an insignificant effect. (4) The impact of land intensive use on urban resilience demonstrates significant scale heterogeneity and geographic regional heterogeneity. Based on these findings, the paper proposes relevant policy suggestions for land intensive use aimed at improving urban resilience, offering guidance for promoting high-quality land use and sustainable urban resilience development. [ABSTRACT FROM AUTHOR]

Improving 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. [ABSTRACT FROM AUTHOR]

Urban green spaces provide several benefits related to the quality of urban life. The existence and spatial arrangement of these spaces within neighbourhoods and functional land uses have significant implications for the well-being of urban dwellers. Previous studies on green spaces in urban areas of Malawi have focused on a broader and macro-level perspective, offering insightful information on general trends in different cities. However, there is a significant research shortage in localised understanding, which requires carrying out micro-level assessments concentrating on land use zones and neighbourhoods within these cities. In this study, we used remote sensing data and landscape metrics to understand the distribution and configuration of urban green spaces in the city's neighbourhoods and functional land uses and their relationship with urban form. The study revealed that 20% of neighbourhoods fail to meet the WHO-recommended standard of 9 m2 of green space per person, with a predominant concentration of these undersupplied areas in high-density and quasi-residential zones. In addition, 56.2% of Lilongwe City's total green area was contained under functional land uses. Particularly, high-rise residential, medium-density residential, low-density residential, quasi-residential, high-rise flat area, commercial class, high-rise commercial, heavy industry, light industry, and government land use zones contained 17.3%, 12.0%, 22.2%, 12.0%, 4.1%, 6.4%, 6.1%, 5.0%, 1.6%, and 13.3% of the total green spaces in functional land uses, respectively. Importantly, this research found significant correlations between urban form metrics, namely building coverage, building density, building perimeter area ratio, road density, and the distribution and configuration of urban green spaces. This necessitates an integrated approach to urban planning and design, emphasising the importance of balancing development with green space preservation. [ABSTRACT FROM AUTHOR]

AbstractUrban land use is central to urban planning. With the emergence of urban big data and advances in deep learning methods, several studies have leveraged graph convolutional networks (GCNs) with local functional characteristics from points of interest data and spatial features from flow data to infer urban land use. However, these studies cannot distinguish spatial interaction and spatial dependence in terms of conceptualization and modeling mechanisms and overlook the inadequacy of GCNs in modeling spatial interaction. This study proposes a novel framework—a heterogeneous graph convolutional network (HGCN)—to explicitly account for the spatial demand and supply components embedded in spatial interaction data. Several experiments, including 19 different models and datasets from Shenzhen and London, were conducted to validate the proposed framework and its generalizability within the same and different spatial contexts. The HGCN can distinguish heterogeneous mechanisms in supply- and demand-related modalities of spatial interactions, incorporating both spatial interaction and spatial dependence for urban land-use inference. Empowered by HGCN, we found that spatial interaction features play a distinctively crucial role in urban land-use inference compared to local attributes and spatial dependence features. In addition, our findings highlight the superiority of HGCN-based models in boosting performance and enhancing model transferability. [ABSTRACT FROM AUTHOR]

An expansion of impervious surfaces in urban areas leads to increases of nutrient loads discharged with the surface runoff to receivers. A study of a different density of urban development impact on total nitrogen (TN) and phosphorus (TP) loads from the city of Lublin (eastern Poland) with the use of the SWAT (Soil & Water Assessment Tool) model was performed. To distinguish between areas with high and low density of urban development (UHD and ULD), a special analysis of hydrological parameters has been proposed. Moreover, to investigate the impact of climate change, four variant scenarios were taken into account, combining the RCP (representative concentration pathway) 4.5 and 8.5 forecasts and the adopted time horizons (2026–2035 and 2046–2055). The results showed a much higher share of TN and TP from UHD compared to ULD (86%—32 022 kg/year and 89%—2574 kg/year, respectively). In addition, the variant scenarios showed that the forecasted increase in precipitation and temperature will result in increased loads of nutrients from UHD and ULD up to 30%. Furthermore, the current increase of inhabitant number, due to the Ukrainian war migration and the common tendency to convert agricultural land to residential areas, could contribute to further expansion of UHD and ULD areas and an additional increase of nutrient loads. [ABSTRACT FROM AUTHOR]

The growth of African cities is characterised by sprawl, significantly impacting social, economic and environmental systems. The change in land use due to urban sprawl often dispossesses farmers in peri-urban communities, resulting in income loss. Focusing on social and ecological changes in peri-urban communities of Ghana, this paper sheds light on land use and land cover change stemming from urban sprawl. It is argued that land governance systems that shape resource access in peri-urban areas have been transformed with farming being the most impacted. Emerging livelihoods like sand winning further compounds a precarious situation. Women and youth are the most affected, with limited options for alternative occupations and uncertain futures. It is thus imperative that policy interventions prioritise sustainable land governance and urban planning, taking into account the needs and vulnerabilities of peri-urban communities, particularly women and youth. [ABSTRACT FROM AUTHOR]

As a new product of rapid urbanization, the sprawl of urban construction land can objectively reflect urban land use efficiency, which is of great significance to China's new urban construction. This study aimed to summarize the expansion patterns and utilization efficiency of urban construction land in China from the perspectives of the status, speed and trends of expansion, and to uncover the key factors that lead to the differential distribution of the expansion of construction land. It can also provide land management experience for other countries with rapid expansion of construction land. The results show the following. (1) The expansion of China's construction land presents a "point–line–plane" pattern of evolution, forming changing stages of point-like aggregation, linear series and planar spread. (2) China's construction land shows the characteristics of disorderly spread, a low utilization rate and low output efficiency. The speed of expansion presents clear characteristics of being high in the east and low in the west, mostly concentrated in the Yangtze River Delta, Pearl River Delta and the Beijing–Tianjin–Hebei urban agglomeration. Shanghai, Beijing, Shenzhen and Guangzhou have the highest intensity of construction land use. In Shandong Peninsula and eastern coastal areas, the intensity of the construction land use is generally high. In Xinjiang and Xizang, the intensity of construction land use is relatively low. (3) The urban economic level, population size, industrial structure, foreign investment and land policies have significant effects on the spatial distribution of the expansion of construction land. [ABSTRACT FROM AUTHOR]

Urban land serves as the medium for urban economic and residential activity. The degree of intensive and efficient use of urban land and the coordinated growth of the economy and society are significantly impacted by utilization efficiency. Northwest China's temperature, geography, water, and soil characteristics make less of the region suited for urban development. Thus, it is imperative to investigate Northwest China's urban land use efficiency (ULUE). This study applies the efficiency loss model to highlight the discrepancy between the optimal and actual values of each input-output variable of the ULUE, and uses the Super-SBM model to compute the ULUE of 39 cities. Additionally, the internal driving elements of the ULUE are examined using the Global Malmquist-Luenberger (GML) index. This study discovered that Northwest China had a low ULUE, with a modest upward trend seen between 2004 and 2018. The overall shape of the region was similar to an 'N' curve, with high efficiency values concentrated in the southeast of the region in 2018. When considering the agglomeration impact of urban agglomeration, these results are dependable. Moreover, the efficiency loss model discovered that pollution and wasteful resource usage were the main reasons behind the drop in ULUE in Northwest China. Finally, the GML index and its constituents revealed that the main force behind ULUE's growth in Northwest China is technological developments. This research provides important policy implications for reducing the gap between eastern and western regions, supporting high-quality development in northwest China, and protecting and intensively using urban land. [ABSTRACT FROM AUTHOR]

The sustainability of social–ecological systems within river deltas globally is in question as rapid development and environmental change trigger "negative" or "positive" tipping points depending on actors' perspectives, e.g. regime shift from abundant sediment deposition to sediment shortage, agricultural sustainability to agricultural collapse or shift from rural to urban land use. Using a systematic review of the literature, we show how cascading effects across anthropogenic, ecological, and geophysical processes have triggered numerous tipping points in the governance, hydrological, and land-use management of the world's river deltas. Crossing tipping points had both positive and negative effects that generally enhanced economic development to the detriment of the environment. Assessment of deltas that featured prominently in the review revealed how outcomes of tipping points can inform the long-term trajectory of deltas towards sustainability or collapse. Management of key drivers at the delta scale can trigger positive tipping points to place social–ecological systems on a pathway towards sustainable development. [ABSTRACT FROM AUTHOR]

Urban land use multi-objective optimization aims to achieve greater economic, social, and environmental benefits by the rational allocation and planning of urban land resources in space. However, not only land use reconstruction, but renovation, which has been neglected in most studies, is the main optimization direction of urban land use. Meanwhile, urban land use optimization is subject to cost constraints, so as to obtain a more practical optimization scheme. Thus, this paper evaluated the renovation and reconstruction costs of urban land use and proposed a cost-heuristic genetic algorithm (CHGA). The algorithm determined the selection probability of candidate optimization cells by considering the renovation and reconstruction costs of urban land and integrated the renovation and reconstruction costs to determine the direction of optimization so that the optimization model can more practically simulate the actual situation of urban planning. The reliability of this model was validated through its application in Shenzhen, China, demonstrating that it can reduce the cost consumption of the optimization process by 35.86% at the expense of sacrificing a small amount of economic benefits (1.18%). The balance of benefits and costs enhances the applicability of the proposed land use optimization method in mature, developed areas where it is difficult to demolish buildings that are constrained by costs. [ABSTRACT FROM AUTHOR]

Numerous studies have examined land surface temperature (LST) changes in Thailand using remote sensing, but there has been little research on LST variations within urban land use zones. This study addressed this gap by analyzing summer LST changes in land use zoning (LUZ) blocks in the 2012 Chiang Mai Comprehensive Plan and their relationship with surface biophysical parameters (NDVI, NDBI, MNDWI). The approach integrated detailed zoning data with remote sensing for granular LST analysis. Correlation and stepwise regression analyses (SRA) revealed that NDBI significantly impacted LST in most block types, while NDVI and MNDWI also influenced LST, particularly in 2023. The findings demonstrated the complexity of LST dynamics across various LUZs in Chiang Mai, with SRA results explaining 45.7% to 53.2% of summer LST variations over three years. To enhance the urban environment, adaptive planning strategies for different block categories were developed and will be considered in the upcoming revision of the Chiang Mai Comprehensive Plan. This research offers a new method to monitor the urban heat island phenomenon at the block level, providing valuable insights for adaptive urban planning. [ABSTRACT FROM AUTHOR]

Geospatial data has proven useful for monitoring urbanization and guiding sustainable development in rapidly urbanizing regions. The United Nations' (UN) Sustainable Development Goal (SDG) Indicator 11.3.1 leverages geospatial data to estimate rates of urban land and population change, providing insight on urban land use expansion patterns and thereby informing sustainable urbanization initiatives (i.e., SDG 11). Our work enhances a UN proposed delineation method by integrating various open-source datasets and tools (e.g., OpenStreetMap and openrouteservice) and advanced geospatial analysis techniques to automate the delineation of individual functional urban agglomerations across a country and, subsequently, calculate SDG Indicator 11.3.1 and related metrics for each. We applied our automated geospatial approach to three rapidly urbanizing countries in Africa: Ethiopia, Nigeria, and South Africa, to conduct multi-level examinations of urban land use expansion, including identifying hotspots of SDG Indicator 11.3.1 where the percentage growth of urban land was greater than that of the urban population. The urban agglomerations of Ethiopia, Nigeria, and South Africa displayed a 73%, 14%, and 5% increase in developed land area from 2016 to 2020, respectively, with new urban development being of an outward type in Ethiopia and an infill type in Nigeria and South Africa. On average, Ethiopia's urban agglomerations displayed the highest SDG Indicator 11.3.1 values across urban agglomerations, followed by those of South Africa and Nigeria, and secondary cities of interest coinciding as SDG Indicator 11.3.1 hotspots included Mekelle, Ethiopia; Benin City, Nigeria; and Polokwane, South Africa. The work presented in this study contributes to knowledge of urban land use expansion patterns in Ethiopia, Nigeria, and South Africa, and our approach demonstrates effectiveness for multi-level evaluations of urban land expansion according to SDG Indicator 11.3.1 across urbanizing countries. [ABSTRACT FROM AUTHOR]

This study evaluates nine Planetary Boundary Layer (PBL) turbulence parameterization schemes from the Weather Research and Forecasting (WRF) mesoscale meteorological model, comparing hourly values of meteorological variables observed and simulated at the surface of the Metropolitan Region of São Paulo (MRSP). The numerical results were objectively compared with high-quality observations carried out on three micrometeorological platforms representing typical urban, suburban, and rural land use areas of the MRSP, during the 2013 summer and winter field campaigns as part of the MCITY BRAZIL project. The main objective is to identify which PBL scheme best represents the diurnal evolution of conventional meteorological variables (temperature, relative and specific humidity, wind speed, and direction) and unconventional (sensible and latent heat fluxes, net radiation, and incoming downward solar radiation) on the surface. During the summer field campaign and over the suburban area of the MRSP, most PBL scheme simulations exhibited a cold and dry bias and overestimated wind speed. They also overestimated sensible heat flux, with high agreement index and correlation values. In general, the PBL scheme simulations performed well for latent heat flux, displaying low mean bias error and root square mean error values. Both incoming downward solar radiation and net radiation were also accurately simulated by most of them. The comparison of the nine PBL schemes indicated the local Mellor-Yamada-Janjic (MYJ) scheme performed best during the summer period, particularly for conventional meteorological variables for the land use suburban in the MRSP. During the winter field campaign, simulation outcomes varied significantly based on the site's land use and the meteorological variable analyzed. The MYJ, Bougeault-Lacarrère (BouLac), and Mellor-Yamada Nakanishi-Niino (MYNN) schemes effectively simulated temperature and humidity, especially in the urban land use area. The MYNN scheme also simulated net radiation accurately. There was a tendency to overestimate sensible and latent heat fluxes, except for the rural land use area where they were consistently underestimated. However, the rural area exhibited superior correlations compared to the urban area. Overall, the MYJ scheme was deemed the most suitable for representing the convectional and nonconventional meteorological variables on the surface in all urban, suburban, and rural land use areas of the MRSP. [ABSTRACT FROM AUTHOR]

Urbanization is a complex phenomenon that has a profound impact on natural resources, economies, climate dynamics, and community structures. This study sets out to analyze the effects of urban sprawl on key urban regions in Bangladesh, covering urban, suburban, and rural landscapes. We used Landsat images from 1992 to 2022, processed and classified using the Google Earth Engine and Random Forest algorithm. Spatial metrics, Tupu method, ANOVA, and spatial regression models helped us quantify and explain land cover changes, their drivers, and consequences. Our findings show that the total built-up area in the five districts expanded from 1,200 km2 in 1992 to 2,800 km2 in 2022, with an overall yearly expansion rate of 3.5%. Meanwhile, vegetation cover declined from 2,500 km2 in 1992 to 1,500 km2 in 2022, with an average yearly loss rate of 2.5%. We identified population growth, economic development, and infrastructure expansion as the main drivers of urbanization, while land degradation, air and water pollution, and loss of biodiversity were the main consequences. Urbanization also had a significant impact on environmental functions, including carbon sequestration, water flow control, and urban heat mitigation, with varying effects across different urban areas and land use types. For instance, we found that carbon storage capacity decreased by 20% in urban areas, while it increased by 10% in rural areas. Our research highlights the crucial role of preserving and enhancing green spaces, including vegetation cover and water bodies, to mitigate urban heat and promote urban resilience. The findings underscore the need for sustainable urbanization, balancing economic growth with environmental protection and climate resilience, using geospatial and remote sensing techniques. [ABSTRACT FROM AUTHOR]

Aim: The development of natural habitats into urban land uses has greatly accelerated in the recent past due to human activities. This habitat development disrupts species' natural dispersal processes and can lead to both direct and indirect impacts on dispersal. Whether human activities result in restricted or facilitated dispersal may depend on a species' development tolerance; however, this premise has not been tested. We examined the impact of urbanization and road networks on the dispersal of three lizard species in the context of their development tolerance. Location: Curaçao. Methods: To quantify species' development tolerance, we modelled three lizard species abundances at sites based on surrounding landscape development. Using microsatellite genotypes, we conducted individual‐based resistance surface analyses and modelled the effect of habitat development on genetic admixture to assess indirect dispersal restriction and facilitation. We explored direct facilitation of dispersal using network analysis of mitochondrial haplotypes. Results: Phyllodactylus martini, a native gecko species, was the least tolerant of development and experienced indirect dispersal restriction due to roads, according to resistance surface analyses. Anolis lineatus, a native anole species, exhibited a neutral relationship with development. Resistance surfaces and Structure analyses showed that A. lineatus faced indirect dispersal restrictions from roads and developed areas, while mitochondrial haplotype networks suggested they benefited from occasional human‐facilitated long‐distance dispersal events. Hemidactylus mabouia, an introduced gecko species, was the most tolerant of development, and experienced no dispersal restriction, but mitochondrial haplotypes suggest direct long‐distance dispersal facilitation. Main Conclusions: Our findings highlight development tolerance as a key predictor of dispersal impact for these species and future work should test whether these patterns are upheld in other systems. Understanding how human activities affect species' dispersal will aid in managing introduced species while promoting connectivity for native species navigating dispersal challenges in dynamic landscapes. [ABSTRACT FROM AUTHOR]

To develop a specific watershed scenario, the quantity and quality of groundwater resources must be assessed and monitored locally. In the present study, an attempt has been made to identify possible groundwater potential zones, determine the quality of groundwater resources in this region, and evaluate their suitability for drinking and irrigation purposes. This goal has been achieved with the combined use of the weighted index overlay analysis (WIOA), groundwater quality index (GWQI), Remote Sensing (RS), and Geographic Information System (GIS) techniques. The proposed study area, Shanmuganadhi, is marked with superior rainfall, oscillating temperature, and runoff with litho-units encompassing charnockite (CHK) and hornblende biotite gneiss (HBG). Over-abstraction of groundwater and intensive agricultural practices have resulted in declining and degrading water quantity and quality in this area. The resulting integrated thematic map has been classified into five groundwater potential zones, namely poor, low, moderate, high, and very high, covering 3.2, 45.49, 15.3, 27.9, and 8.1% area, respectively. Sixty groundwater samples were collected during the pre-monsoon (PRM) and analyzed for major Physico-chemical parameters. From the water quality index assessment, over 28.0% of the samples fall within the “excellent,” 8.0% “good” and 4.0% “poor” in CHK, followed by 5.71% “excellent,” 48.57% “good,” 37.14% “poor,” 5.71% “very poor” and 2.87% “unsuitable” for drinking purposes in HBG terrain of this region. Irrigation indices also demonstrated that most of the groundwater samples in the CHK and HBG exposed zones exhibited good classes for irrigation purposes, as evidenced by the SAR and %Na+. The outcome, which shows the research area’s groundwater potential zones, is beneficial for improved groundwater resource planning and management. It is concluded that for larger-scale groundwater-quality investigation and assessment, the groundwater quality index-making approach (GWQI) is more practical and dependable. Water planners and decision-makers may find it helpful in effectively controlling and monitoring groundwater quality at the basin or watershed scale. Reducing urban land use and natural runoff from farms can help prevent water contamination in some regions. To ensure the safe use of groundwater, long-term monitoring of these groundwater was suggested. [ABSTRACT FROM AUTHOR]

Inferring urban functions using street view images (SVIs) has gained tremendous momentum. The recent prosperity of large-scale vision-language pretrained models sheds light on addressing some long-standing challenges in this regard, for example, heavy reliance on labeled samples and computing resources. In this paper, we present a novel prompting framework for enabling the pretrained vision-language model CLIP to effectively infer fine-grained urban functions with SVIs in a zero-shot manner, that is, without labeled samples and model training. The prompting framework UrbanCLIP comprises an urban taxonomy and several urban function prompt templates, in order to (1) bridge the abstract urban function categories and concrete urban object types that can be readily understood by CLIP, and (2) mitigate the interference in SVIs, for example, street-side trees and vehicles. We conduct extensive experiments to verify the effectiveness of UrbanCLIP. The results indicate that the zero-shot UrbanCLIP largely surpasses several competitive supervised baselines, e.g. a fine-tuned ResNet, and its advantages become more prominent in cross-city transfer tests. In addition, UrbanCLIP's zero-shot performance is considerably better than the vanilla CLIP. Overall, UrbanCLIP is a simple yet effective framework for urban function inference, and showcases the potential of foundation models for geospatial applications. [ABSTRACT FROM AUTHOR]

The study of the factors affecting the heat island effect was significantly influenced by the effect of the modifiable areal unit problem (MAUP), which led to uncertainty in the results. Taking the main urban area of Wuhan City as an example, we constructed a multidimensional urban spatial morphology index system based on multi-source spatial data of urban land use and buildings, explored the response characteristics of geographic detectors to the modifiable areal unit problem (MAUP) effect, analyzed the driving forces and factors of the spatial differentiation of urban thermal environment, proposed optimal regulation strategies to mitigate urban surface thermal environment. The results show that MAUP has strong sensitivity to the detection results of urban heat island effect factors, and different research units and partitioning methods will affect the research results. Factor detection analysis shows that the explanatory power of 3D spatial morphological indicators on urban heat island effect is greater than that of 2D urban land use indicators, and building density is the dominant driver of spatial differentiation of surface thermal environment. The interaction detection analysis shows that the spatial differentiation of the surface thermal environment in the main urban area of Wuhan is a synergistic process between different influencing factors, and the interaction between two-dimensional indicators and between two-dimensional and three-dimensional indicators is significantly greater than the single-factor effect. The study of the spatial differentiation of urban spatial morphology on the surface thermal environment provides theoretical support for the coordinated optimization of multi-dimensional urban spatial morphology to mitigate the heat island effect. [ABSTRACT FROM AUTHOR]

Studying urban land use and its impact on carbon emissions is crucial for achieving China's dual carbon goals. This research utilized the Shared Socio-economic Pathways (SSPs) scenarios 126, 245, and 585 from the Sixth International Coupled Model Intercomparison Project (CMIP6), along with a coupled System Dynamics (SD) and Patch-generating Land Use Simulation (PLUS) model and a carbon emission coefficient method to simulate and predict Xi'an's land use carbon emissions from 2020 to 2040. The results indicate the following: (1) Cultivated and forest lands are the predominant land use types in Xi'an, with cultivated and grassland areas projected to decline under all three SSP scenarios by 2040. The most significant expansion of construction land, primarily at the expense of farmland, is projected under the SSP585 scenario, with an increase of 515.92 km2 by 2040. (2) Land use carbon emissions increased from 414.15 × 104 t in 2000 to 2376.10 × 104 t in 2020, with construction land being the primary source of emissions and forest land serving as the main carbon sink. However, the carbon sink capacity remained low at only 21.38 × 104 t in 2020. (3) Carbon emissions are expected to continue increasing under all scenarios through 2030 and 2040, though at a decreasing rate. The SSP126 scenario predicts the lowest emissions, reaching 9186.00 × 104 t by 2040, while SSP585 predicts the highest at 14,935.00 × 104 t. The findings of this study provide theoretical support for future low-carbon and high-quality urban development strategies. [ABSTRACT FROM AUTHOR]

High-quality utilization of urban land (HUUL) is essential for optimizing urban land use and promoting high-quality development. Previous research has mainly focused on examining urban land use efficiency, neglecting the connection between urban land use and high-quality development. This study reveals the intrinsic association mechanism between high-quality development and urban land use, which can provide comprehensive theoretical and empirical support for high-quality land use and high-quality urban development. This study constructed an evaluation system for HUUL that comprehensively adopted the entropy method, kernel density estimation, and the geodetector model to analyze the spatio-temporal evolution and driving factors of the HUUL levels of 284 Chinese cities from 2006 to 2020. The measurement results showed that during 2006–2020, the HUUL level showed an apparent upward trend, and the eastern region > the central region > the overall region > the western region > the northeast region. From the kernel density map, there was a noticeable trend of varying degrees of increase in the difference of the main peak position of the HUUL level among cities in all regions except the west. Furthermore, some cities in the eastern and western regions had significantly higher HUUL levels than the others. According to the results of the factor analysis, it is evident that innovative use and open use are the internal primary factors that drive the enhancement of the HUUL level. Moreover, the level of economic development is the external primary factor that facilitates the improvement in HUUL level. [ABSTRACT FROM AUTHOR]