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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]

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]

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]

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]

Rapid morphological and socioeconomic changes have accelerated the urbanization process and urban land use transformation in China. Megacities comprise clusters of urban cities and exhibit both newly formed and well-developed urban land use development beyond administrative boundaries. It is necessary to distinguish the changing effects of spatial-varying driving factors on newly formed urban land uses from well-developed built-up areas in megacities. This study proposed a multi-spatial urbanization framework to quantify region-level socioeconomics, cluster-level ecological morphologies, and grid-level urban functional morphologies. A three-level Bayesian hierarchical model was developed to investigate the impacts of multi-spatial driving factors on urban land use transformation in megacities. The study period focused on the urbanization process between 2000 and 2018 in Guangdong–Hong Kong–Macao Greater Bay Area (GBA). Results revealed that compared with well-developed urban built-up land, changing impacts of three-level driving factors in urban land use transformation could be captured based on the proposed Bayesian hierarchical model. The region-level total population was associated with increasing possibilities in forming new residential land than the well-developed ones in 35 districts/counties/cities in GBA. Cluster-level ecological attributes with higher proportion, lower edge density of urban built areas, and lower-degree ecological complexity showed increasing probability on newly formed industrial and public land. Grid-level urban functional factors including public transportation density and shopping/dining distribution exhibited significantly decreasing probability (coefficients: −2.12 to −0.51) on contributing newly formed land uses compared with the well-developed areas, whereas business/industry distribution represented higher (coefficients: 0.99 and 0.15) and lower probabilities (coefficient: −0.22) of forming industrial/public land and residential land separately. This research shows a new attempt to distinguish multi-spatial morphological and socioeconomic effects in urban land use transformation in megacities. [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]

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]

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]

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]

This article explores the issue of housing unaffordability in Hong Kong and its connection to spatial planning. Hong Kong has consistently been ranked as the most unaffordable housing market since 2011. While some argue that restrictive land use planning is to blame, the article suggests that historical development patterns and the lack of strategic spatial planning in the rural New Territories are the main factors contributing to the housing shortage and high land prices. The article also discusses the role of rentier capitalism and speculative demand in driving up housing prices. Additionally, the text touches on various topics related to urban planning and governance, including the concept of green plot ratio, urban experiments in South Korea and China, and the importance of collective action and cooperation in governing the physical and digital commons. [Extracted from the article]

The growing processes of urban expansion have led to changes in the biochemical and physical properties of the hydrological systems in watersheds, not only by altering the hydrological conditions of the territory, but also by introducing pollutants into water bodies. Thus, diffuse pollution from stormwater runoff is considered one of the main causes of water quality degradation in receiving waters in urban areas, especially in rainy regions such as the South American tropics, where urban development and management processes are generally poorly planned. This article presents the results of an evaluation of the relationship between land use and runoff water quality, taking into account different rainfall characteristics. Sampling was carried out in Medellín, Colombia, in areas with different land uses. Basic water quality parameters and some sources of urban pollution were studied. The results showed that parameters such as total suspended solids have a high variability, especially in the residential area, which makes it difficult to control the activities carried out there. The highest levels of pollution were found in the industrial area, where the presence of covers with very low or no permeability and the increase in anthropic activity cause a strong alteration in the quality of runoff water. These results open the door to question the impact of land use on the chemical composition of rainwater and promote a better understanding of surface runoff water pollution processes, thus providing a complete vision of the interactions in an urban ecosystem, establishing a key tool for water management in urban watersheds. [ABSTRACT FROM AUTHOR]

In the future, the risk of land subsidence due to water resources shortage crisis and improper water resources management will become more and more dangerous. It is necessary to assess and identify areas susceptible to subsidence risk and take necessary actions to reduce risks related to land subsidence. In this study, first, the risk of land subsidence was identified and evaluated using a radar interferometry method called LiCSBAS. Then, the spatial relationship between the occurrence of land subsidence hazard and effective factors such as ground elevation, slope, slope aspect, lithology, land use, groundwater decline, distance from rivers, distance from faults, topographic moisture index, and arc curvature was investigated using the random forest (RF) model. In the end, the land subsidence hazard sensitivity map was prepared after calibrating the random forest algorithm. The analysis of LiCSBAS interferometric time series data from 2015 to 2022 showed that the center of the Marvdasht-Kharameh plain and adjacent agricultural areas are continuously subsiding and the mean deformation rate map showed a subsidence rate of 11.6 centimeters per year. The results of determining the spatial relationship between subsidence occurrence and effective factors confirmed the positive impact of distance from rivers, urban and agricultural land uses, depth of bedrock (aquifer thickness), groundwater decline, and alluvial and fine-grained formations on this phenomenon. Also, the results of subsidence modeling using the random forest algorithm showed that factors such as bedrock depth, groundwater decline, land use, and geology have the greatest impact on the potential for subsidence occurrence in the study area. Also, based on the results, about 3 to 4 percent of the areas are in the very high and extremely high-risk classes of land subsidence, especially in the center and suburbs of Mervdasht. Therefore, water resources management and control and developing a systematic program to reduce subsidence risk and aquifer recharge conservation in Merudasht-Kharameh Plain is essential. [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]

Land surface temperature (LST) increases and urban heat island (UHI) variability are the major urban climatology problems arising in urban development. This study attempts to assess the effects of urban land use and land cover change on microclimate dynamics in Addis Ababa city. Three different sets of remotely sensed data from Landsat 5 TM (1990), Landsat 7 ETM+ (2005) and Landsat 8 OLI/TIRS (2021) were used for the study. LSTs were retrieved from Landsat5 TM and Landsat7 ETM+ using a mono window,and the thermal infrared band (TR-10) of Landsat–8 was used to retrieve LST. Regression and correlation analyses of the LST, normalized difference vegetation index (NDVI) and normalized difference built-up index (NDBI) were performed in SPSS V23. The study also examined the different residential urban morphology types (UMTs) of the LST and NDVI. The selected built-up blocks of UMTs included apartments, villas and mud houses. These UMTs are extracted by digitizing them from the Google Earth explorer. The results from this study showed that the proportion of urban green space (UGS) to other LULC types decreased from 120.4 km2 in 1990 to 76.26 km2 in 2021. However, the built-up area increased at a rate of 216.5 km2 (39.03%) from 1990 to 2021. The rapid expansion of built-up land in the study area was the main factor influencing the increase in LST. The residential UMTs exhibited significant differences in mean LSTs and NDVIs. The results indicate that UMT inhibited by Villia had the highest mean NDVI value and that the highest mean LST was observed in Apartment. The results of multiple linear regression analysis clearly indicate that built-up and green vegetation contributed 92.2% of the LST variations with R2 = 0.92 and VIF ≤ 10 in Addis Ababa city. The results of the study indicate that strengthening public participation in urban greening and optimizing the NDVI and NDBI are important strategies for mitigating the effects of microclimate change and that sustaining urban development and providing better quality of life for the urban population are important. [ABSTRACT FROM AUTHOR]

In this research, the objective is to study the Spatial Evolution of Smart Cities for Sustainable Tourism in Phuket Province, Thailand from 2005-2024, using the Geo-informatic Technique as information for decision-making in determining the direction of Smart City. The study results found that land use patterns such as Urban and built-up land, Waterbodies, and Forest land have had an increasing trend over the past 20 years. In 2005, Urban and built-up land was found to cover 132.19 km2 (24.10% of the total area). In 2024, it was found to have greatly increased, covering 165.91 km2 (30.25% of the total area), especially in Thalang District, which is north of Phuket. The area has a wide plain landscape, and beautiful wide beaches such as Bang Tao Beach. There has been a change from agricultural land to housing developments, residential areas, restaurants, hotels, resorts and homestays. The results of this study have been prepared as a spatial database for supporting decision-making in monitoring and planning the development of areas to support the expansion of sustainable tourism in the future to become a smart city. [ABSTRACT FROM AUTHOR]

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Based on the panel data of Guangxi from 2005 to 2017, the spatiotemporal characteristics and determinants of urban carbon emissions in Guangxi were analyzed using the extended STIRPAT model and the Geographically and Temporally Weighted Regression (GTWR) model. The main findings of our research can be summarized as follows. While the total carbon emissions of cities in Guangxi consistently increased from 2005 to 2014, the growth trend slowed after 2014, leading to a stabilization in the total emissions. In addition, there are significant differences in the total carbon emissions among the cities. The central and northeastern regions have higher emissions, while the southwestern region has lower emissions. Finally, there are variations in the degrees and directions of the impacts that factors have on carbon emissions among the different time periods and cities. Urban land use is a key factor driving carbon emissions, and it has a negative impact on most cities in Guangxi. Meanwhile, factors such as industrial structure, population urbanization, population concentration, and economic growth have significant positive effects on carbon emissions in Guangxi. The influence of urban roads on carbon emissions is generally positive, while the degree of openness to the outside world and environmental regulations has relatively weaker impacts on emissions. In summary, in order to promote the low-carbon transition of Guangxi and achieve high-quality development, the cities in Guangxi should implement differentiated urban carbon reduction strategies that are focused on optimizing urban land use and industrial structure. [ABSTRACT FROM AUTHOR]

Although the relationship between the size of urban industrial land use and pollutant emissions has been widely discussed from different perspectives (e.g., the scale and crowding effects), the results of various studies have revealed positive, negative, and combined impact relationships. However, how the expansion of urban industrial land use affects SO2 emissions remains unknown. We need to clarify this relationship in order to facilitate the realization of China's pollution reduction and emission reduction goals. This study used the panel data from 294 cities spanning from 2011 to 2019 to construct a spatial econometric model. The objective was to explore the correlation between the scale of urban industrial land and sulfur dioxide emissions in China. The results show that a large scale of urban industrial land use corresponds to lower sulfur dioxide emissions per unit of industrial added value. By gaining a deeper understanding of the relationship between the scale of urban industrial land use and sulfur dioxide emissions, policymakers can further reduce pollutant emissions by rationalizing the planning of urban industrial land use and industrial layout. In addition to promoting industrial agglomeration and economies of scale in cities with extensive industrial land use, this strategy can support the development of efficient and environmentally friendly industries in areas with limited industrial land use. Optimizing the technology and encouraging the development of green industries can help reduce environmental pollution and promote sustainable urban development. [ABSTRACT FROM AUTHOR]

Estimation of human water withdrawals is more important now than ever due to uncertain water supplies, population growth, and climate change. Fourteen percent of the total water withdrawal in the United States is used for public supply, typically including deliveries to domestic, commercial, and occasionally including industrial, irrigation, and thermoelectric water withdrawal. Stewards of water resources in the USA require estimates of water withdrawals to manage and plan for future demands and sustainable water supplies. This study compiled the most comprehensive conterminous United States water withdrawal data set to date and developed a machine learning framework for estimating public supply withdrawals and associated uncertainty for the period 2000–2020. The modeling approach provides service area resolution estimates to allow for annual and monthly water withdrawal estimation while incorporating a complex array of driving factors that include hydroclimatic, demographic, socioeconomic, geographic, and land use factors. Model results reveal highly variable and lognormally distributed per‐capita water withdrawal, spanning from 30 to 650 gallons per capita per day (GPCD), across community, regional, and national scales, with pronounced seasonal variations. Analysis of estimated withdrawal trends indicates that the national annual average withdrawal experienced a decline at a rate of 0.58 GPCD/year during the period from 2000 to 2020. Model interpretation reveals a complex interplay between public supply withdrawal and key predictors, including population size, warm‐season precipitation, counts of large buildings and houses, and areas of urban and commercial land use. The developed models can forecast future public supply driven by various climate, demographic, and socioeconomic scenarios. Key Points: Consistent, reproducible estimates of monthly water withdrawals were generated at the spatial resolution of USA water service areasSpatial and temporal variability of public supply withdrawal is driven by a complex array of explanatory featuresAn operational machine learning framework was developed to estimate water withdrawals, prediction uncertainty, and feature importance [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]

Urban land is the primary location for manufacturing and services, facilitating the expansion and interconnectedness of economic activities and factor flows to shape various urban land-use performances (ULUP). Exploring these spatial linkages of urban land-use performance can play a crucial role in fostering cohesive urban development. Taking 109 prefecture-level cities as research samples, this paper explores the characteristics and influencing factors of the spatial network associated with ULUP in the Yangtze River Economic Belt through modified gravity model, network analysis and QAP analysis. The analysis shows that ULUP has shown an N-shaped trend over the past two decades. It has formed a network of correlations, with Chongqing, Shanghai, and Wuhan emerging as central nodes. Notably, the correlation predominantly occurs between geographically adjacent cities, with weaker links between the Yangtze River Economic Belt's upstream, midstream, and downstream regions. The network can be divided into four distinct types: main inflow plate, main outflow plate, agent plate, and bidirectional spillover plate. Geographic location is the most significant factor influencing network formation, followed by resource mismatch, economic development, and openness. The study provides theoretical guidance and empirical support for improving the utilisation of urban land and promoting coordinated development. [ABSTRACT FROM AUTHOR]

Over the past few decades, China has undergone the largest and fastest urbanization process in world history. By 2023, Chengdu's urbanization rate had reached 80.5%, significantly higher than the national average of 66.16%. Studying the urbanization experience of Chengdu is of great significance for optimizing urban planning policies in Chengdu and other cities in China. Although much literature has explored the urbanization process from macro and micro perspectives, studies using a top-down approach to examine urban fringe expansion are relatively scarce. This study first applies the entropy weight method to analyze the spatial-temporal evolution trends of urban development, identifying areas of imbalanced development and prominent issues. Secondly, the K-means machine learning algorithm and nightlight data are used to reconstruct and classify urban regions, and a comparative analysis is conducted with administrative divisions to further identify unreasonable areas in urban spatial distribution and structure. Finally, POI data and the geographical detector method are used to analyze the micro-driving forces in areas of imbalanced development, identifying major limiting factors and solutions. The study found that the gap between urban and rural development in Chengdu is narrowing during the urbanization process, but there is severe differentiation in the second circle of Chengdu, where economic development is accelerating but residents' happiness is declining. Moreover, analysis based on urban nightlight data and land-use data reveals that the expansion areas on the urban-rural fringe are mainly concentrated in the second circle of Chengdu. Micro-level driving factor analysis found that the western region of the second circle has many but small urban settlements, with a dense road network but scattered functional areas. The eastern region has inefficient and extensive use of construction land. Additionally, the mismatch between student status and household registration has resulted in relatively lagging educational resource development, and high entry barriers have hindered the progress of urbanization, leading to low per capita welfare expenditure. These reasons are the main factors causing the decline in residents' happiness, and this impact shows significant differences at different temporal and spatial scales. Encouraging innovation in research and development or education can serve as a long-term and effective driving force for promoting sustainable urbanization. This study provides valuable insights for scientifically planning sustainable urban development and promoting the urbanization process. [ABSTRACT FROM AUTHOR]

The establishment of the Free Trade (Pilot) Zone (FTZ) is a new attempt by China to embark on modern sustainable urban planning and governmental territorial management at the development stage of a high-quality economy. As urban lands serve as the limited resource foundation for civic production and livelihoods, enhancing land use efficiency becomes a key measure to facilitate metropolitan economies of high quality. Utilizing panel data from prefecture-level cities spanning from 2005 to 2021, this study constructs a multi-period difference-in-differences model to explore the impact of FTZs on urban land use efficiency (ULUE). The results indicate that FTZs can significantly enhance urban land use efficiency, with a more pronounced policy effect observed in central cities, inland cities, and cities with higher urbanization rates. Furthermore, the FTZs also demonstrate spatial spillover effects on urban land use efficiency. This study holds great significance for relevant government departments in formulating policies to optimize land resource allocation, promote FTZ development, and foster high-quality urban planning and territorial management. [ABSTRACT FROM AUTHOR]

The advancement of the big data industry is playing a pivotal role in urban land management refinement. Recently, China initiated a big data strategy, establishing national big data comprehensive pilot zones (NBDCPZs) across diverse regions. These initiatives present substantial opportunities for enhancing the urban land green use efficiency (ULGUE). Consequently, in this study, we utilized the super-efficiency slack-based measure (SBM) model with undesirable outputs to assess the ULGUEs across 281 prefecture-level cities in China from 2006 to 2021. Subsequently, leveraging the NBDCPZ establishment as a quasi-natural experiment, we employed the difference-in-differences (DID) method to empirically explore the impact of the NBDCPZ policy on the ULGUE for the first time. The findings revealed the following: (1) The implementation of the NBDCPZ policy significantly enhances the ULGUE; (2) the effects are mediated through mechanisms such as fostering technological innovation, mitigating resource misallocation, and promoting industrial agglomeration; (3) the heterogeneity analysis emphasizes the increased policy effectiveness in cities characterized by fewer natural resources, lower economic growth pressures, stable development stages, and moderate digital infrastructure and human capital levels; and (4) further analysis demonstrates the significant positive spillover effects of the NBDCPZ policy on the ULGUEs of neighboring non-pilot cities, with a diminishing impact as the proximity between pilot and non-pilot cities decreases. Overall, this study contributes to the literature on the relationship between the digital economy and land utilization, offering valuable insights for achieving sustainable urban development. [ABSTRACT FROM AUTHOR]

Accurate assessment of population trends and factors that limit distributions of threatened species is key to conserving biodiversity. A reduction in impacts of human land use on species habitats may be one of the factors involved in the recolonization of former ranges by native species. The signature of this process could be detected as a temporal reduction of land use effects on species distributions, or as a spatial reduction, with effects persisting only in habitats more sensitive to anthropogenic stressors. We explored these hypotheses in a recolonizing semiaquatic carnivore. Our species of interest was the Eurasian river otter (Lutra lutra) in Italy, a nationally vulnerable species with a restricted but expanding range. Human land use is likely to strongly affect riparian and stream communities through habitat degradation. We used three independent survey datasets collected in 2003, 2009, and 2019 at the southern range periphery, and unpaired‐site occupancy models to account for imperfect detection in otter surveys. To assess how land use affects recolonization by otters, we tested three main model predictions: (1) occupancy increased over years, (2) effects of agricultural and urban land cover on occupancy decreased over years, (3) effects of agricultural and urban land cover were constant across years and changed with stream size and elevation. We found evidence that otter occupancy increased over years, with predicted mean occupancy of 0.27 in 2003 and 0.65 in 2019. An interaction effect of urban land cover with stream size was the strongest predictor of otter occupancy. Interestingly, a higher percentage of urban land cover around streams was predicted to reduce the probability of occupancy at smaller streams, but did not influence occupancy at larger streams. Despite a large increase in occupancy, otters at the southern periphery of the Italian range are still unable to colonize small rivers in urbanized areas. This pattern supports our hypothesis that human land use can affect recolonizing species at sensitive habitats, considering the intrinsic vulnerability of small stream ecosystems to anthropogenic stressors. Restoring small streams impacted by urban areas can be a valuable conservation action to increase habitat connectivity and favor recolonization of otters. [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]

Purpose: Hyporheic biofilms are the central site for biogeochemical cycling in streams and rivers. In view of global warming and increasing human pressures, this study aimed to compare the response of hyporheic biofilm biomass and activities from an unpolluted reference stream reach surrounded by forest with those from a stream reach exposed to agricultural and urban land use using a mesocosm experiment in which the water temperature and dissolved organic carbon (DOC) contents were manipulated. Methods: Hyporheic sediments collected in the field from the two study reaches (i.e. reference and impacted) were incubated in the laboratory at two different temperatures (10 °C, 14 °C) and wetted with three types of synthetic water (control [C] – 0 mg L−1; low DOC – 5 mg L−1; high DOC – 30 mg L−1) for four weeks. The responses of the hyporheic biofilms were measured weekly using structural (total protein content [TPC] as a proxy for biofilm biomass) and functional measures (electron transport system activity [ETSA] and community-level physiological profiling [CLPP]). Results: The response of hyporheic biofilms to temperature changes and DOC enrichment was site-specific for all studied measures (TPC, ETSA and CLPP, including measured average well colour development [AWCD]). The addition of DOC to biofilms from the pristine stream reach significantly heightened the responses at 10 °C, a temperature within the normal environmental temperature ranges of the reference location, but not at 14 °C, which was here, a temperature outside normal environmental range. On the other hand, biofilms from the impacted stream reach exhibited increased responses following DOC enrichment under both temperature regimes, with a particularly pronounced response at 14 ºC, in this case, both experimental temperatures were within the normal environmental temperature ranges of the study locations. Conclusion: Hyporheic biofilms were shown to be, like benthic biofilms, sensitive to temperature changes and organic enrichment, but their response to temperature changes and enrichment caused by climate change and/or other anthropogenic pressures (i.e. point and non-point pollution, removal of the riparian zone, hydromorphological modifications, etc.) was not simply linear but site-specific. The intensity of the response, characterized by increased activity and biomass production, appears to be constrained within the temperature ranges prevalent in the environment from which the biofilms originate. These findings emphasize the importance of site-specific considerations in predicting the impacts of climate change and anthropogenic pressures on these critical components of river and stream ecosystems. [ABSTRACT FROM AUTHOR]

The urban radio‐frequency (RF) noise generated by our cities continues to change with time. Although models exist to describe the RF noise as functions of frequency and urban land use types, very few models describe the spatial character or structure of the noise on the scales of city blocks (50–150 m). The goal of this work is to investigate the connection between urban morphology and the higher‐order spatial statistics of the noise field. To achieve this goal, a large measurement campaign was conducted in Boston, Massachusetts. Many spatial measurements allowed for calculation of spatial correlation functions of noise power in three different neighborhoods, which were used to quantify the spatial structure of the fields. A statistical point source model is then developed, with adjustable parameters relating to urban morphology. Good agreement between the model and the experimental correlation functions suggests the 25 MHz urban noise field is well described by a random network of fixed point sources, radiating with a 1/r power law behavior. Plain Language Summary: Our modern cities are filled with electronic devices. Each device can emit radiation and contribute to what is called the urban radio‐frequency noise field. The noise field is the combined effect from all these devices. If the noise field is strong enough it can negatively impact wireless communication, and the use of other electric devices. It is important to better understand the nature of the noise field in order to mitigate and plan for its negative effects. This paper describes in detail how the noise field is distributed in space, or its spatial structure. A theoretical model or tool is developed to help predict how the noise field looks spatially. Key Points: Radio‐frequency noise spatial correlation functions were calculated for three different neighborhoods in Boston, MassachusettsGood theoretical agreement suggests the noise field is well described by a random network of point sources radiating with a 1/r behavior [ABSTRACT FROM AUTHOR]

Subtropical and tropical islands are undergoing rapid urbanization as the human population expands globally. Urbanization disrupts coastal ecosystems through several pathways—including the replacement of natural habitats with concrete structures that increase runoff pollution—but it remains difficult to isolate and characterize specific impacts of urbanization on marine ecosystems. The historical gradient in urbanization on the subtropical island of Okinawa, Japan, sets up a natural laboratory to study urbanization effects on nearshore ecosystems. Physicochemical parameters and bacterial community composition were assessed every 2 weeks for 1 year at two nearshore sites adjacent to watersheds with > 70% urban land use and two nearshore sites adjacent to watersheds with > 70% rural land use. Urbanization increased freshwater input and nutrient loading—indicated by decreased salinity and elevated nitrate + nitrite, ammonium, and phosphate at urban sites—despite the urban sites being more open to flushing due to land reclamation projects filling in the coral lagoon. Urbanization significantly altered microbial community composition by increasing diversity through the addition of fecal indicator and pathogenic bacteria—eight orders of bacteria were only detected in urban samples, whereas only Verrucomicrobiales was unique to rural samples. The change in microbial community composition at urban sites persisted throughout the seasonal cycle, suggesting a regime change or sustained disturbance. The altered physicochemical conditions and microbial communities at urban sites could degrade nearby coral reefs and their ecosystem services, highlighting the importance of coastal land management in marine conservation efforts. [ABSTRACT FROM AUTHOR]

Purpose: Anthropogenic activities are a major driver of soil and land degradation. Due to the spatial heterogeneity of soil properties and the global nature of most value chains, the modelling of the impacts of land use on soil quality for application in life cycle assessment (LCA) requires a regionalised assessment with global coverage. This paper proposes an approach to quantify the impacts of land use on soil quality, using changes in soil organic carbon (SOC) stocks as a proxy, following the latest recommendation of the Life Cycle Initiative. Methods: An operational set of SOC-based characterisation factors for land occupation and land transformation were derived using spatial datasets (1 km resolution) and aggregated at the national and global levels. The developed characterisation factors were tested by means of a case study analysis, investigating the impact on soil quality caused by land use activities necessary to provide three alternative energy supply systems for passenger car transport (biomethane, ethanol, and solar electricity). Results obtained by applying characterisation factors at local, regional, and national levels were compared, to investigate the role of the level of regionalisation on the resulting impacts. Results and discussion: Global maps of characterisation factors are presented for the 56 land use types commonly used in LCA databases, together with national and global values. Urban and industrial land uses present the highest impacts on SOC stocks, followed by severely degraded pastures and intensively managed arable lands. Instead, values obtained for extensive pastures, flooded crops, and urban green areas often report an increase in SOC stocks. Results show that the ranking of impacts of the three energy systems considered in the case study analysis is not affected by the level of regionalisation of the analysis. In the case of biomethane energy supply, impacts assessed using national characterisation factors are more than double those obtained with local characterisation factors, with less significant differences in the other two cases. Conclusions: The integration of soil quality aspects in life cycle impact assessment methods is a crucial challenge due to the key role of soil conservation in ensuring food security and environmental protection. This approach allows the quantification of land use impacts on SOC stocks, taken as a proxy of soil quality. Further research needs to improve the assessment of land use impacts in LCA are identified, such as the ability to reflect the effects of agricultural and forestry management practices. [ABSTRACT FROM AUTHOR]

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The introduction of the carbon peak and carbon‐neutral targets by many countries' central governments has put low‐carbon‐oriented spatial planning at the forefront of discussions. However, few studies have focused on the balance of carbon emission reduction and economic goals in spatial planning, and the governance influence on land use change simulation. This study addresses this gap by conducting an empirical analysis in the rapidly urbanizing area of Hangzhou, China, taking into consideration low‐carbon constraints and economic development demands. Using the stochastic impacts by regression on population, affluence, and technology (STRIPAT) model and linear programming–Markov, we simulate the governance decision‐making process to calculate the optimal land‐use structures under both low‐carbon and baseline scenario, then simulated land use patterns by using artificial‐neural‐network‐based cellular automata (ANN‐CA). The results showed 12.35% and 2.5% growth in urban and forest land, and 9.69% and 6.4% decline in farm and rural land under the low‐carbon scenario. 92.31% of urban land change occur in the downtown districts and suburbs; while 59.77% of farm land change and 95.53% of forest land change occur in the exurban districts. The low‐carbon performance of land use was reflected in carbon storage release, carbon emission capability change, and low‐carbon capability. The most common conversion of land use categories under the low‐carbon scenario was between farm and forest land, and between rural and urban land, which resulted in less carbon storage release and carbon emissions compared with the baseline scenario. Furthermore, under the low‐carbon scenario, the compactness of construction land increased by 2 × 10−5, while its fragmentation decreased by 0.0027. This study sheds light on the impact of low‐carbon‐oriented land use planning on urban land expansion, providing empirical evidence for city governments in rapid urbanization areas to improve land use efficiency. [ABSTRACT FROM AUTHOR]

Summary: This research deals with a frame‐supported shear wall for urban over‐track building of vehicle depot in Chisha, Guangzhou, China, which is characterized by its remarkable height of 160.8 m. Technical issues are commonly encountered in these kinds of buildings due to discontinuous vertical structural rigidity, large podium, and structural transition. These challenges significantly impact the engineering process, especially when the rigidity difference between transfer story exceeding the threefold, as well as the building height exceeds limit as in code. In this paper, a shaking table test was developed based on a 1:10 scaled model of the structure. Using similarity theory, the dynamic similarity relationship was established for the design of the model. Subsequently, the experimental model was constructed with the configuration of critical parameters such as mass design, sensor placement, and seismic test conditions. This was followed by in‐depth analysis, recording component failures and investigating key aspects such as dynamic characteristics, that is, acceleration and displacement responses and shear force distribution under different earthquake intensities. A theoretical seismic response of the prototype structure was derived from the test results. The shaking table tests confirmed that the structure met the stringent seismic design requirements as prescribed in the Chinese standards, with no damage under minor earthquakes, repairability under moderate earthquakes, and collapse prevention under rare earthquakes. The results of the study provide valuable insights along with improvement measures for the design and development of similar urban over‐track buildings, potentially contributing to more efficient land use in urban China. [ABSTRACT FROM AUTHOR]