Search

Globally, urbanization is accelerating, with China witnessing a significant 40% rise in urbanization rate over the past 4 decades. However, the dynamic changes in the spatial coupling between infrastructure and utilization intensity during the early, middle, and late stages of urbanization are not clear. The trajectory of development and coupling within the urbanization process is crucial for understanding issues such as urban over-saturation and urban shrinkage. Using Hegang in Northeastern China as an example, we utilized high-resolution remote sensing data, examined the construction intensity of urban land use, analyzed the degree of coupling with utilization efficiency, and clarified the dynamic evolution of the binary relationship system between development and coupling. Results show that Hegang's construction intensity has seen a continuous rise from 1992 to 2000, with a 200.06% increase over 28 years, while its coupling with utilization efficiency has experienced a significant drop in the 21st century, suggesting a persistent decline in the utilization of buildings and a notable urban shrinkage phenomenon. Considering development status and coupling degree, we delineate a characteristic urbanization state curve for Hegang, reflecting its progression through stages of "Underdeveloped, Highly coupled," to "Underdeveloped, Weakly coupled", and finally to "Highly developed, Weakly coupled", offering insights into its urban development path. This research not only establishes a foundational data groundwork for future land-use planning in Hegang but also presents a replicable template for urbanization path analysis in other cities, contributing to a broader understanding of urban development dynamics. [ABSTRACT FROM AUTHOR]

The development of spatial interactions of land resources enhances virtual built‐up land flow, which contributes to China's inter‐regional trade inequality. Little is known about the degree of inequality among regions. This work seeks to estimate the degree of interregional trade inequality through environmental‐economic benefits. We combined a multiregional input–output model at the city level with a new classification to calculate the virtual built‐up land flow among cities and analyzed its implications for the regional economy and carbon balance. The results indicate that developed regions were the main beneficiaries of inter‐regional trade, as reflected in land‐use efficiency. China's economic hub has been progressively shifting southward, and the inter‐regional trade inequality has continuously increased. The flow of virtual service industry land among developed regions rose, while underdeveloped regions remained suppliers of raw materials, further increasing inter‐regional trade inequality. [ABSTRACT FROM AUTHOR]

Built‐up land changes along slope gradients (BCSG) are widespread globally, driven by natural environmental and socio‐economic variations. This process has profound effects on vegetation cover and is closely related to the United Nations Sustainable Development Goals. However, the mechanisms involved in the BCSG remain to be elucidated, and the impacts of BCSG on vegetation cover need to be quantified. The BCSG from 1990 to 2020 was described through slope spectrum analysis by taking the Three Gorges Reservoir Area (TGRA) as an example. Then, the Normalized Difference Vegetation Index (NDVI) was used as an indicator of vegetation cover, and its influence by BCSG was explored through a multiple linear regression model. The built‐up land in the TGRA from 1990 to 2020 was first dominated by slope climbing (SC) and then by horizontal expansion, and the intensity of built‐up land SC showed a general trend of weakening over time. During the 30 years, the intensity of built‐up land SC weakened and then strengthened in townships with mainly intermountain plains, while gradually decreasing in townships with mainly hills and townships with mainly mountains. Socio‐economic factors, natural factors, and regional special events drive the BCSG in TGRA. Built‐up land SC in the TGRA will have a negative impact on NDVI but to a progressively lesser degree from 1990 through 2020. The built‐up land SC in townships with mainly hills and mountains has a negative effect on NDVI. The built‐up land SC in townships with mainly intermountain plains has a positive impact on NDVI. These results can provide a scientific basis for formulating reasonable vertical management policies for built‐up land and help reduce the ecological risks caused by land development. [ABSTRACT FROM AUTHOR]

Globally, urbanization is accelerating, with China witnessing a significant 40% rise in urbanization rate over the past 4 decades. However, the dynamic changes in the spatial coupling between infrastructure and utilization intensity during the early, middle, and late stages of urbanization are not clear. The trajectory of development and coupling within the urbanization process is crucial for understanding issues such as urban over-saturation and urban shrinkage. Using Hegang in Northeastern China as an example, we utilized high-resolution remote sensing data, examined the construction intensity of urban land use, analyzed the degree of coupling with utilization efficiency, and clarified the dynamic evolution of the binary relationship system between development and coupling. Results show that Hegang’s construction intensity has seen a continuous rise from 1992 to 2000, with a 200.06% increase over 28 years, while its coupling with utilization efficiency has experienced a significant drop in the 21st century, suggesting a persistent decline in the utilization of buildings and a notable urban shrinkage phenomenon. Considering development status and coupling degree, we delineate a characteristic urbanization state curve for Hegang, reflecting its progression through stages of “Underdeveloped, Highly coupled,” to “Underdeveloped, Weakly coupled”, and finally to “Highly developed, Weakly coupled”, offering insights into its urban development path. This research not only establishes a foundational data groundwork for future land-use planning in Hegang but also presents a replicable template for urbanization path analysis in other cities, contributing to a broader understanding of urban development dynamics.

This study is an effort of geo-spatial assessment of pluvial floods in District Lahore, Pakistan, caused by urban expansion and the growing frequency and intensity of high-intensity rainfall events. The use of geospatial techniques such as watershed modeling, maximum likelihood image classification, and weighted overlay analysis based on secondary data has enabled the researchers to assess the extent and severity of pluvial floods in the study area. The study's findings highlight the high risk of pluvial floods in the central part of the study area, which is dominated by built-up land and concrete roads. The increase in the area of built-up land from 34.913 km2 in 2018 to 37.442 km2 in 2022 has further intensified the risk of pluvial floods. The findings of this study can assist policymakers in developing effective strategies to reduce the risks associated with pluvial floods. Alongside, it also highlights the importance of geospatial techniques to better understand and address the complex challenges of urbanization and climate change. Flood risk zone-specific strategies are recommended to reduce the risk of pluvial floods. [ABSTRACT FROM AUTHOR]

Rapid urbanization in cities is crafting major environmental problems, leading to degradation of urban ecosystems and is responsible for creating an imbalance between demand and supply of resources. Ecological Footprint Analysis (EFA) is a tool that can be used to assess this imbalance scientifically and determine the sustainability of a particular area. Our study aims to determine the urban sustainability of Kangra district in Himachal Pradesh, a hilly state in North Western Himalayas, India situated in North western Himalayas by using one of the Ecological Footprint Analysis (EFA) components, the built-up land footprint, as a pragmatic tool for analysis and planning of the urban region. The total built-up land footprint, total biocapacity and total ecological deficit are 18146.095 g ha,15968.564 g ha and 2177.531 g ha respectively whereas built-up land footprint per capita, built-up land biocapacity per capita and ecological deficit per capita are 1.371 g ha, 1.206 g ha, and 0.164 g ha respectively in different urban areas. Consequently, it is concluded that the built-up land results in an ecological deficit, and the system is considered unsustainable because its ecological footprint exceeds its bio capacity. It is suggested that urban sustainability should move and work on ecological principles so that the vision encompassing global goals and agenda 2030 for sustainable development can be achieved. [ABSTRACT FROM AUTHOR]

The study's primary objective is to measure the rate and pattern of land use and land cover changes in Dimapur city, as well as their impact on land surface temperature (LST). Landsat TM (Thematic mapper) data from 2000 and 2007, as well as Landsat OLI (Operational land imager) and TIR (Thermal infrared sensor) data from 2020, were used in the study. In order to examine the city's population patterns, the study was supplemented using LandScan global gridded data for the pre-defined years (1KM × 1KM). The urban sprawl index (USI) was employed to detect urban sprawl in Dimapur, while the urban thermal field variant index (UTFVI) was utilized to investigate surface urban heat islands. Dimapur's built environment grew from 14.74 percent to 39.36 percent between 2000 and 2020, while green spaces shrank from 33.21 percent to 19.44 percent. Between 2000 and 2007, the USI value increased from 0.0037 to 0.0055, indicating substantial urban sprawl in recent years. Between 2000 and 2020, these changes resulted in an increase in mean LST of 17.27 °C (winter) and 26.86 °C (summer) to 19.01 °C (winter) and 31.43 °C (summer). According to UTFVI, the number of locations classified as ecologically bad or worse in Dimapur has increased in recent years. The larger positive correlation between population and built-up areas and LST, as well as the stronger negative correlation between vegetation and population and LST, support the impact of population-induced land use and land cover change on LST development in Dimapur urban area. [ABSTRACT FROM AUTHOR]

The threat of environmental degradation of the Martapura River as a result of an increase in built-up land has become a serious problem, so it is important to implement a new method using the integration of calculations of changes in built-up land and the sustainability of river area environmental management. This study aimed to calculate the change in built-up land directly integrated through Rap-RiverBuiltUp quantitative analysis on the environmental sustainability of the Martapura river area, Banjarmasin City. The research method used is the technique of spatial analysis of ETM/Landsat 8 OLI satellite landsat images and analysis of ecological, social and economic sustainability with Rap-RiverBuiltUP analysis. The results of the analysis of built-up land around the Martapura river, Banjarmasin City, have increased by 2.31% over the last 12 years, followed by a growth in population density of ±1.5% annually. The implementation of sustainable environmental management needs to be prioritized with the efforts to periodically revise regional spatial planning regulations, especially the boundaries of built-up land to reduce the development of built-up land around the Martapura River. The sustainability status of the built-up area around the Martapura river is currently not sustainable. The ecological dimension indicates a less sustainable status, while the economic and social dimensions indicate a fairly sustainable status. Increasing the sustainability index value of the Martapura river from each dimension in the future is by making the lever factor an input for the management policy of the Martapura river, Banjarmasin City. [ABSTRACT FROM AUTHOR]

During rapid economic development and urbanisation, land expansion in built-up areas is China's dominant land-use change type, resulting in the loss of ecosystem service value (ESV). Economic development is China's main driving force for built-up land expansion. Under the trend of the spatial separation of production and consumption, expanded built-up land embodied in trade flows between regions as a scarce land resource. Through trade, a region can indirectly use built-up land from outside areas, which may affect land use within the user and provider regions. Regional ESV loss may be affected by outer regions, although previous studies have seldom considered it. Accordingly, this study quantified ESV for the whole of China in high resolution and determined ESV loss caused by expanded built-up land for each province and ESV loss flows embodied in interregional interactions. The results found that China's total ESV of terrestrial ecosystems was 37.44 trillion yuan in 2015, and the expanded built-up land resulted in a loss of 13.7 billion yuan in ESV. Due to the north–south differences in natural and economic levels in China, there was significant spatial heterogeneity in ESV and ESV loss caused by built-up land expansion, with the high-value areas mainly in the southern coastal areas. With regional interaction, the leading regional flow direction of built-up land and ESV loss was from north to south, mainly from economically developing regions to economically developed regions. However, there was a discrepancy between the actual users of the built-up land and the ESV loss-bearers. Evident regional inequalities existed in several provinces with regional interactions. Overall, this study provides a reference for developing China's interregional economic and ecological harmony strategies in the context of sustainable development.

Rapid urbanization in cities is crafting major environmental problems, leading to degradation of urban ecosystems and is responsible for creating an imbalance between demand and supply of resources. Ecological Footprint Analysis (EFA) is a tool that can be used to assess this imbalance scientifically and determine the sustainability of a particular area. Our study aims to determine the urban sustainability of Kangra district in Himachal Pradesh, a hilly state in North Western Himalayas, India situated in North western Himalayas by using one of the Ecological Footprint Analysis (EFA) components, the built-up land footprint, as a pragmatic tool for analysis and planning of the urban region. The total built-up land footprint, total biocapacity and total ecological deficit are 18146.095 g ha,15968.564 g ha and 2177.531 g ha respectively whereas built-up land footprint per capita, built-up land biocapacity per capita and ecological deficit per capita are 1.371 g ha, 1.206 g ha, and 0.164 g ha respectively in different urban areas. Consequently, it is concluded that the built-up land results in an ecological deficit, and the system is considered unsustainable because its ecological footprint exceeds its bio capacity. It is suggested that urban sustainability should move and work on ecological principles so that the vision encompassing global goals and agenda 2030 for sustainable development can be achieved.

Zhang, T., 2023. Using satellite imagery to determine spatiotemporal patterns of built-up land use in relation to the coastline: An example from Xiamen, China. Journal of Coastal Research, 39(1), 103–113. Charlotte (North Carolina), ISSN 0749-0208. This study used four Landsat-TM satellite imageries (1989, 2000, 2010, and 2018) to detect the spatiotemporal change characteristics of built-up land by using variance and correlation analysis to ensure the ecological capacity and urban sustainable development in Xiamen. The results show that during the rapid urbanization period of 1989 to 2018, a large amount of farmland (70.7%) and the water body (64.4%) were lost. Among them, 43.8% of farmland and 33.6% of the water body have been converted to built-up land, producing great pressure on ecological security and sustainable development. On spatial distribution pattern, this research found that the built-up land expansion in Xiamen mainly occurred along the coastline. Preliminary statistics found that the built-up land is mainly concentrated in the coastal zone as far as 5 km (reaches maximum density of 0.37 ± 0.16) from the coastline. In this zone, the built-up land is most compact and intensive, whereas most of the new built-up land increased 5 km to 9 km away to the coastline. Variance analysis shows that built-up land density at all distances of buffer lines are very significant differences (P < 0.01), and the difference reaches the maximum of 0.289 at a buffer line of 7 km. Correlation analysis shows that the built-up land density varies significantly and negatively correlated with the distance to the coastline (P < 0.01), indicating that the farther away from the coastline, the smaller the density of built-up land is. The final regression analysis shows that a significant relationship with cubic regression equation occurs between the built-up land area in 1989, the built-up land density in 2018, and the distance from the coastline. Based on this analysis, the possible impact factors of the spatial pattern and approaches to a compact city are discussed. [ABSTRACT FROM AUTHOR]

Understanding the dynamics of built-up land amidst the urban-rural transformation process is crucial for balancing the benefits of urbanization against the challenges of uncontrolled expansion. Yet, how built-up land develops across different types of human settlements, particularly within emerging Global South megaregions (GSMs), is not well documented. Employing an urban-rural gradient (URG) approach, we investigate built-up land dynamics across six representative emerging GSMs spanning 1985–2020, contextualizing our findings within urbanization theory and sustainable development discourse. Our analysis reveals that urban center growth and peri-urbanization drive a substantial proportion of built-up land expansion (36.47% and 27.39%, respectively), in contrast to the minimal increases observed in rural clusters and semi-dense areas (2.48% and 2.44%, respectively). The predominant expansion mode is sprawling growth, notably evident in peripheral areas, while densifying growth is mainly confined to urban centers and mostly uninhabited areas. Sprawling shrinkage is observed in dense and semi-dense urban areas, as well as rural clusters. These nuanced dynamics illustrate the varied ways in which regional territories engage with and are shaped by the urbanization process. Through the lens of the URG analysis, our study enhances understanding of spatial transformations in the GSMs, offering informative insights for fostering sustainable cities and human settlements. • Revealing nuanced dynamics of built-up land in emerging Global South megaregions spanning 1985–2020. • Using an urban-rural gradient approach to unveil diverse patterns of built-up land across a spectrum of human settlements. • Identifying varied expansion modes shaping built-up landscapes, including densification, sprawl, and shrinkage. • Offering informative insights guiding locally adaptive strategies for sustainable urban development. [ABSTRACT FROM AUTHOR]

The increase of the land surface temperature (LST) caused by an urban expansion poses a great threat to the humanity and society. However, the heating characteristics of built-up land and the environmental impacts on these mechanisms remain poorly understood over large areas. Therefore, the change trend (k) and structural distribution of LST during the process of increasing the built-up area in 172 cities in China was quantified. Using correlation analysis and statistical methods to analyze the correlation and possible driving characteristics of influencing factors (climate, topography, land use type, and soil) on k. The results indicated that k varied from −5.955 to 8.240 and showed a spatial characteristic of small in the northwest and large in the southeast. The research emphasized the heating difference of built-up land varied significantly in cities with different natural environmental conditions, with the maximum difference reaching 6 °C. The heating mechanism of built-up land under the interference of influencing factors was explained from the perspective of land surface heat flux, and the mitigation strategies for urban temperature were proposed. Besides, the threshold for the impact of environmental factors on the heating of built-up land was found, which provides a reference for environment-adapted urban design and planning standards tailored by considering the specific characteristics of each city. • The effects (k) of built-up land on LST are analyzed and quantified. • The impact of land use type on heating characters of built-up are found. • The impact threshold of natural environmental factors is discovered. • The possible driving mechanism of influencing factors on k is proposed. • Urban planning suggestions are proposed for thermal mitigation. [ABSTRACT FROM AUTHOR]

In China, airports have a profound impact on people's lives, and understanding their dimensions has great significance for research and development. However, few existing airport databases contain such details, which can be reflected indirectly by the built-up land in the airport. In this study, a deep learning-based method was used for extraction of built-up land of airports in China using Sentinel-2 imagery and for further estimating their area. Here, a benchmark generation method is introduced by fusing two reference maps and cropping images into patches. Following this, a series of experiments were conducted to evaluate the network architectures and select the positive impact bands in Sentinel-2 imagery. A well-trained model was used to extract the built-up land for China airports, and the relationship between China airports' built-up land and the carrying capacity of air transportation was further analysed. Results show that ResUNet-a outperformed U-Net, ResUNet, and SegNet, and the B2, B4, B6, B11, and B12 bands of Sentinel-2 had a positive impact on built-up land extraction. A well-trained model with an overall accuracy of 0.9423 and an F1 score of 0.9041 and 434 China airports' built-up land was extracted. The four most developed airports are located in Beijing, Shanghai, and Guangzhou, which matches China's political and economic development. The area of built-up land influenced the passenger throughput and aircraft movements. The total area influenced the cargo throughput, and we found a certain correlation among the built-up land, carrying capacity, and nighttime light. [ABSTRACT FROM AUTHOR]

Settlements and built-up areas can lead to the degradation of ecological systems. Good quality and efficient regional planning is therefore needed for urban areas. Spatial data and satellite imagery can be used for mapping and monitoring urban growth. Unfortunately, mapping urban areas can sometimes be difficult due to local variations, and different algorithms can provide varying results. Urban indices often rely on remote sensing reflectance, the accuracy of which can be influenced by land characteristics. No studies have examined the impact of land characteristics on the accuracy of remote sensing urban indices in the humid tropics. The purpose of this study was to compare urban and built area indices, namely EBBI, NDBI, UI, and IBI, in two climatically and topographically different cities. This study also examined the stability and relationship between these indices with environmental factors such as slope, elevation, and temperature. The results showed that EBBI was the index with the highest accuracy in both study areas: 85% for Batu City and 89.17% for Pasuruan City. Also, EBBI was the most stable index for the temporal studies. Environmental factors, especially slope and elevation, had a strong relationship with the index value applied. Therefore, these findings need to be considered in applying the index in areas that have topographical variations. [ABSTRACT FROM AUTHOR]

This paper analyzes the interactions between land development policies in Cotonou (Benin) – in particular so-called subdivision and land consolidation operations – and the city’s significant exposure to environmental constraints, in particular flooding. It is based on fieldwork that covers several vulnerable city neighborhoods, and relies on qualitative interviews with a whole chain of actors involved at different levels, from the offices of surveyors and town planners to the various municipal and ministerial services dealing with land and land development policies. This work shows that these policies reinforce rather than reduce the vulnerability of the city and its inhabitants to environmental risks.

Accurate, long time-series, high-resolution mapping of built-up land dynamics is essential for understanding urbanization and its environmental impacts. Despite advances in remote sensing and classification algorithms, built-up land mapping which only uses spectral data and derived indices remains prone to uncertainty. We mapped the extent of built-up land in the North China Plain, one of China’s most important agricultural regions, from 1990 to 2019 at three-yearly intervals and 30 m spatial resolution. We applied Discrete Fourier Transformation to dense time-stack Landsat data to create Fourier predictors to reduce mapping uncertainty. As a result, we improved the overall accuracy of built-up land mapping by 8% compared to using spectral data and derived indices. In addition, a temporal correction algorithm applied to remove misclassified pixels further improved mapping accuracy to a consistently high level (>94%) over the time periods. A cross-product comparison showed that our maps achieved the highest accuracies across all years. The built-up land area in the North China Plain increased from 37,941 km2 in 1990–1992 to 131,578 km2 in 2017–2019. Consistent, high-accuracy, long time-series built-up land mapping provides a reliable basis for formulating policy and planning in one of the most rapidly urbanizing regions on this planet.

Accurate mapping of built-up land is essential for urbanization monitoring and ecosystem research. At present, remote sensing is one of the primary means used for real-time and accurate surveying and mapping of built-up land, due to the long time series and multi-information advantages of existing remote sensing images and the ability to obtain highly precise year-by-year built-up land maps. In this study, we obtained feature-enhanced data regarding built-up land from Landsat images and phenology-based algorithms and proposed a method that combines the use of the Google Earth Engine (GEE) and deep learning approaches. The Res-UNet++ structural model was improved for built-up land mapping in Guangdong from 1991 to 2020. Experiments show that overall accuracy of built-up land map in the study area in 2020 was 0.99, the kappa coefficient was 0.96, user accuracy of built-up land was 0.98, and producer accuracy was 0.901. The trained model can be applied to other years with good results. The overall accuracy (OA) of the assessment results every five years was above 0.97, and the kappa coefficient was above 0.90. From 1991 to 2020, built-up land in Guangdong has expanded significantly, the area of built-up land has increased by 71%, and the proportion of built-up land has increased by 3.91%. Our findings indicate that the combined approach of GEE and deep learning algorithms can be developed into a large-scale, long time-series of remote sensing classification techniques framework that can be useful for future land-use mapping research. [ABSTRACT FROM AUTHOR]

Reasonable quantitative assessment on urban ecosystem health is conducive to the sustainable development of the economy and human society. This paper quantitatively evaluated the impact of land use change on ecosystem services and ecosystem health by building a comprehensive evaluation system (vigor–organization–resilience–ecosystem services), and then analyzed the spatial-temporal pattern, evolution characteristics, and driving factors in the Shanghai–Hangzhou Bay area (SHB) over the 2000–2015 period. The results show that: the area of cropland and forest accounted for more than 65% and was mainly converted into built-up land in the past 15 years. The overall ESV showed a trend of first increasing and then decreasing. Forest accounted for the largest proportion of the total ESV, more than 60% in each year. The ecosystem health value of SBH decreased from 2000 to 2015. At the city scale, the ecosystem health was significantly deteriorated. All cities reached the lowest value by 2015. At the districts/counties scale, the number with the relatively well or well level decreased from 32 in 2000 to 20 in 2015 by 24.64% of the total area. Overall, inland regions of SBH had better ecosystem health situation than coastal areas. The rapid urbanization of population and economy were driving factors for the decline of the ecosystem health. The indicator system of integrating the vigor, organization, resilience, and ecosystem service for ecosystem health assessment is a potential method which could provide a quantitative and comprehensive way for evaluating ecological and environmental effects in the future. [ABSTRACT FROM AUTHOR]

In order to measure and detect land-use changes, it is necessary to know the pace at which land-use changes from one type of land to another. However, due to limited resources, researchers are having difficulty doing statistical analyses on polygonal data structures. The digital data structure lends itself to statistical analysis using general-purpose software, whereas land-use change was assessed solely by counting grid cells. The polygonal data were converted to digital data using the grid-digitized approach. This study compares land-use changes in Thailand's Krabi province in 2000–2009, and 2009–2018. Thematic maps and the bubble plot were used to depict land-use change across Krabi province, with a digitized grid (100 by 100 m) encompassing the entire region. A logistic regression model was used to examine the probability of built-up land. According to the findings, total built-up land was 5164 hectares (1.1% of all areas) in 2000, 9881 hectares (2.1% of all areas) in 2009, and 18,832 hectares in 2018. (4% of all areas). Built-up land rose by 91.3% and 90.6%, respectively, between 2009 and 2018. Each location's land-use was related to the probability of built-up land. Rubber plantation and agricultural land provided the majority of the built-up land. Furthermore, areas closer to metropolitan centers saw a higher percentage rise in built-up land than rural areas. Receiver operating characteristic curves and F-scores indicated that the models were accurate enough. [ABSTRACT FROM AUTHOR]

Copyright of Economic & Ecohistory / Ekonomska i Ekohistorija is the property of Society for Croatian Economic & Environmental History and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Rapid and unplanned urbanization leads to temperature rise, urban vegetation decrease and built-up land increase, forming an urban heat island (UHI). This study investigated the effects of changes in vegetation and built-up land on land surface temperature(LST) in summer, based on remotely sensed images. LST was first retrieved by means of the Radiative Transfer Model (RTM). Scatter-plots and an univariate linear regression model (ULRM) were first employed to independently measure the influence of NDVI on LST, and of NDBI on LST, respectively. In order to assess the effects of changes in vegetation and built-up land on LST, a multivariate linear regression model (MLRM) was finally employed to improve the accuracy of the predicted model in the identificationof the joint effect of both the normalized difference vegetation index (NDVI) and the normalized difference built-up index (NDBI) on LST. The result from the case from the Hanoi Metropolitan Area (HMA), Vietnam using Landsat-5 TM and Landsat-8 OLI/TIRS time-series images during the 1996-2016 period shows that there exists a negative effect of built-up land and a positive effect of vegetation on LST. In addition, indications of intensifying UHI effects were detected in the HMA, especially tending to expand faster and wider to the parts of western, north-western and south-western HMA during the 1996-2007 period. These findings suggest that vegetation weakens the effect of UHIs, whereas, built-up land greatly strengthens the effect of UHIs in the HMA.

Abstract Population concentration and built‐up land expansion are two prominent features of contemporary urbanization. Existing literature on the population aspect of urbanization has mostly focused on national and regional aggregates, and literature on the land development aspect has often relied on spatial case studies of individual cities or their meta‐analyses. Using newly‐available data, here we conduct the first global‐coverage, spatial analysis of the relationship between (changes in) population and built‐up land at multiple spatial scales, and compare to existing common beliefs about urbanization based on individual city studies. We find that population and built‐up land show distinctly different spatial and temporal patterns (with a global correlation coefficient around 0.6). Contrary to common impressions, our results show that during recent decades, developed and developing regions across the world experienced comparable amounts of built‐up land expansion. While meta‐analyses have reported that built‐up land in urban areas expands globally on average twice as fast as population grows, our results show the global change rates of built‐up land and population are similar. Also, most global population, including what national statistics agencies call urban population, reside in areas with low land development levels (which are frequently less than 5% built up). These changes in perspective suggest that urbanization's potential large‐scale impacts may need to be re‐evaluated, and lead to best‐practice recommendations for urbanization modeling and analysis. Especially, the common practice in large‐scale earth system modeling of assuming demographically‐defined urban population resides in areas with medium to high built‐up land development levels should change.

Population concentration and built‐up land expansion are two prominent features of contemporary urbanization. Existing literature on the population aspect of urbanization has mostly focused on national and regional aggregates, and literature on the land development aspect has often relied on spatial case studies of individual cities or their meta‐analyses. Using newly‐available data, here we conduct the first global‐coverage, spatial analysis of the relationship between (changes in) population and built‐up land at multiple spatial scales, and compare to existing common beliefs about urbanization based on individual city studies. We find that population and built‐up land show distinctly different spatial and temporal patterns (with a global correlation coefficient around 0.6). Contrary to common impressions, our results show that during recent decades, developed and developing regions across the world experienced comparable amounts of built‐up land expansion. While meta‐analyses have reported that built‐up land in urban areas expands globally on average twice as fast as population grows, our results show the global change rates of built‐up land and population are similar. Also, most global population, including what national statistics agencies call urban population, reside in areas with low land development levels (which are frequently less than 5% built up). These changes in perspective suggest that urbanization's potential large‐scale impacts may need to be re‐evaluated, and lead to best‐practice recommendations for urbanization modeling and analysis. Especially, the common practice in large‐scale earth system modeling of assuming demographically‐defined urban population resides in areas with medium to high built‐up land development levels should change. Plain Language Summary: Cities and towns across the world have been expanding (a process known as urbanization) both in terms of population size and land areas. These two expressions of urbanization (i.e., population concentration and built‐up land expansion) have often been assumed to be strongly associated. This assumption is influential for understanding people's vulnerability to natural disasters (for example, heatwaves, coastal storms) in urban areas, but has not been tested globally, largely due to the lack of data. Recently new global‐coverage maps of population and built‐up land became available. Using the newly‐available data, we examine the relationship between population and built‐up land across the world. We find the correlation between population and built‐up land is about 60%, with the two showing some distinctly different spatial and temporal patterns. Contrary to common impressions, we find developed and developing regions across the world experienced similar amounts of built‐up land expansion during recent decades. Moreover, most people in the world (including those considered urban people by national agencies, such as census) live in areas with less than 5% built‐up land. These changes in perspective suggest that urbanization's potential large‐scale impacts may need to be re‐evaluated. Key Points: The developed and the developing world experienced comparable amounts of built‐up land expansion during recent decadesMost global population (including urban population) reside in areas with low land development levels (frequently less than 5% built up)Population and built‐up land show distinctly different spatiotemporal patterns globally (with a correlation coefficient around 0.6) [ABSTRACT FROM AUTHOR]

Abstract By using the latest China population grid and land-use data, we assess the changing exposure of China’s population and land uses to the hazards of storm surges, droughts, earthquakes, floods, and landslides from 1995 to 2015. We found that the single-hazard areas and the multi-hazard areas covered 43% and 26% of China’s territory, respectively. Population grew faster in the hazard-prone areas than in the non-hazard areas. Built-up area expanded more rapidly in the areas prone to earthquakes and landslides. Cropland changed rapidly in many hazard-prone areas. The hazard-prone areas affected by floods featured the highest cropland loss rates, while the areas prone to earthquakes and landslides featured the highest cropland growth rates. We detected areas with significant exposure changes by using hot spot analysis. It was found that population and built-up land in the Pearl River Basin were increasingly exposed to storm surges, floods, and landslides. The Haihe River Basin and Huaihe River Basin also showed a consistent increase of population and built-up land exposure to droughts and earthquakes. These findings can provide a foundation for the design and implementation of protection and adaptation strategies to improve the resilience of Chinese society to natural hazards.

Accurate mapping of built-up land is essential for urbanization monitoring and ecosystem research. At present, remote sensing is one of the primary means used for real-time and accurate surveying and mapping of built-up land, due to the long time series and multi-information advantages of existing remote sensing images and the ability to obtain highly precise year-by-year built-up land maps. In this study, we obtained feature-enhanced data regarding built-up land from Landsat images and phenology-based algorithms and proposed a method that combines the use of the Google Earth Engine (GEE) and deep learning approaches. The Res-UNet++ structural model was improved for built-up land mapping in Guangdong from 1991 to 2020. Experiments show that overall accuracy of built-up land map in the study area in 2020 was 0.99, the kappa coefficient was 0.96, user accuracy of built-up land was 0.98, and producer accuracy was 0.901. The trained model can be applied to other years with good results. The overall accuracy (OA) of the assessment results every five years was above 0.97, and the kappa coefficient was above 0.90. From 1991 to 2020, built-up land in Guangdong has expanded significantly, the area of built-up land has increased by 71%, and the proportion of built-up land has increased by 3.91%. Our findings indicate that the combined approach of GEE and deep learning algorithms can be developed into a large-scale, long time-series of remote sensing classification techniques framework that can be useful for future land-use mapping research.

Reasonable quantitative assessment on urban ecosystem health is conducive to the sustainable development of the economy and human society. This paper quantitatively evaluated the impact of land use change on ecosystem services and ecosystem health by building a comprehensive evaluation system (vigor–organization–resilience–ecosystem services), and then analyzed the spatial-temporal pattern, evolution characteristics, and driving factors in the Shanghai–Hangzhou Bay area (SHB) over the 2000–2015 period. The results show that: the area of cropland and forest accounted for more than 65% and was mainly converted into built-up land in the past 15 years. The overall ESV showed a trend of first increasing and then decreasing. Forest accounted for the largest proportion of the total ESV, more than 60% in each year. The ecosystem health value of SBH decreased from 2000 to 2015. At the city scale, the ecosystem health was significantly deteriorated. All cities reached the lowest value by 2015. At the districts/counties scale, the number with the relatively well or well level decreased from 32 in 2000 to 20 in 2015 by 24.64% of the total area. Overall, inland regions of SBH had better ecosystem health situation than coastal areas. The rapid urbanization of population and economy were driving factors for the decline of the ecosystem health. The indicator system of integrating the vigor, organization, resilience, and ecosystem service for ecosystem health assessment is a potential method which could provide a quantitative and comprehensive way for evaluating ecological and environmental effects in the future.

Faced with a global biodiversity crisis, we need to concentrate our collective efforts on safeguarding Key Biodiversity Areas (KBAs), which serve as essential habitats for the world's threatened species. Clarifying the disturbance and protection requirements of KBAs is vital to the global persistence of biodiversity, which is not yet clear. Here, we evaluated the extent and severity of human disturbance in KBAs. Specifically, we analyzed the spatial patterns of disturbance and their potential effects on habitats. Roughly a quarter of terrestrial KBAs are challenged by crop production and urban construction activities, especially in Europe. The mean Human Footprint Index (HFI) for KBAs worldwide is 12.3, indicating a high level of human disturbance. On average, 62 % of each KBA is identified as Human Threatened Areas, signifying intense human impacts on these areas. 57 % of KBAs are subdivided by human disturbance, which can lead to substantial habitat fragmentation and loss of connectivity compared to other forms of disturbance. The halving of mean patch size and the tripling of the perimeter-area ratio for active habitats in KBAs provide evidence of the difficulties faced in conserving these areas. More importantly, increased coverage of Protected Areas fails to reduce HFI in KBAs, indicating some deficiencies in current protection systems. Therefore, we emphasize the importance of focusing on disturbance patterns for more impactful interventions, which potentially offer new pathways to mitigate adverse habitat impacts in post-2020 biodiversity conservation efforts. [Display omitted] • A quarter of KBAs are challenged by crop production and urban construction activities. • An average Human Footprint Index of 12.3 means high human disturbance in KBAs. • 57 % of KBAs are impacted by subdivision-related human disturbance. • A tripling of active habitats' perimeter-area ratio signals a high challenge in KBA protection • A method is explored to identify spatial patterns of human disturbance. [ABSTRACT FROM AUTHOR]

The paper integrates low-carbon development into the context of economic resilience, thus proposing "Low-carbon Economic Resilience" (LER). We establish an analysis framework to analyze LER based on regional interactions. The framework indicates that regions achieve LER by transferring the development burden to others, which will result in inter-regional trade inequality. An empirical analysis focused on inter-regional trade in cities of China is carried out to illustrate this framework. We calculate the degree of economic resilience and low-carbon development in cities of China. Then we trace the environmental-economic benefits embodied in virtual built-up land flow in regions. The characteristics of virtual built-up land flow exert an impact on the spatial distribution of regional economic resilience to a certain extent. The results show that, in China, many cities achieved only economic resilience or low-carbon development, while a few cities were able to achieve LER. The latter imported built-up land with high carbon emissions or low economic benefits from others, while developing "high-quality" built-up land themselves, which was reflected in the benefits per hectare of built-up land. The differences in environmental-economic benefits from inter-regional trade cause trade inequality, and major cities are the main beneficiaries, which contributes to their achievement of LER. • Low-carbon economic resilience is proposed. • Quantifying the environmental-economic benefits of inter-regional trade of cities in China. • Dividing built-up land into 4 categories to match MRIO model. • Analyzing low-carbon economic resilience based on regional interactions. [ABSTRACT FROM AUTHOR]

Urban growth and development can be interpreted as a combined process of “urban spillover” and “local urban sprawl”, from overall urban–rural development to urban–rural integration (URI). The process of suburban development in western China is a complex system, which reflects the characteristics of industrialization and urbanization in western China. Chengdu is the most representative of the big cities for economic and social structure change in western China. To analyze the changes on URI degree based on the built-up land change, and to explore the practical URI paths in both the suburbs and exurbs of Chengdu, we use land-use remote-sensing monitoring data from 2000, 2005, 2010, and 2015 in this paper, whereafter URI indexes are built from space, economy, and society. The land-use change of the suburbs and exurbs of Chengdu from 2000 to 2015 are analyzed by ArcGIS. Results indicate that the biggest growth part of built-up land is other built-up land, followed by commercial/industrial land, and the last is residential land. The built-up land spreads quickly from 2000 to 2005, and shows distinct separation characteristics in the suburbs of Chengdu. It is relatively slow in the exurbs. Moreover, built-up land connects better in the suburbs than in the exurbs. Based on the change of built-up land in Chengdu from 2000 to 2015, spatial integration data are calculated, economic integration and social integration data are chosen from statistics, and the change of URI levels in the suburbs and exurbs of Chengdu is calculated. The results show that first, economic integration and social integration have great influence on URI, and their effects are increasing. The significance of spatial integration in URI has gradually reduced. Second, URI levels in counties of the suburbs and exurbs of Chengdu rose from 2000 to 2015, more highly in the suburbs than in the exurbs. URI in counties of the exurbs showed a marked difference. URI in the southeast counties of the exurbs is generally high. The foundation of URI is weaker in the counties and districts in the southwest counties of the exurbs in Chengdu, but it is growing steadily in URI, and the northern counties in the exurbs of Chengdu are in the process of rapid URI. The paths of URI in the suburbs and exurbs in Chengdu can be roughly divided into an industry-developing model in the suburbs, service-industry-developing model in the suburbs, agriculture-developing model in the exurbs, service-industry-developing model in the exurbs and infrastructure-developing model in the exurbs.

Extracting built-up areas from remote sensing data like Landsat 8 satellite is a challenge. We have investigated it by proposing a new index referred as built-up land features extraction index (BLFEI). The BLFEI index takes advantage of its simplicity and good separability between the four major component of urban system, namely built-up, barren, vegetation and water. The histogram overlap method and the spectral discrimination index (SDI) are used to study separability. BLFEI index uses the two bands of infrared shortwaves, the red and green bands of the visible spectrum. OLI imagery of Algiers, Algeria, was used to extract built-up areas through BLFEI and some new previously developed built-up indices used for comparison. The water areas are masked out leading to Otsu's thresholding algorithm to automatically find the optimal value for extracting built-up land from waterless regions. BLFEI, the new index improved the separability by 25% and the accuracy by 5%. [ABSTRACT FROM AUTHOR]

By using the latest China population grid and land-use data, we assess the changing exposure of China's population and land uses to the hazards of storm surges, droughts, earthquakes, floods, and landslides from 1995 to 2015. We found that the single-hazard areas and the multi-hazard areas covered 43% and 26% of China's territory, respectively. Population grew faster in the hazard-prone areas than in the non-hazard areas. Built-up area expanded more rapidly in the areas prone to earthquakes and landslides. Cropland changed rapidly in many hazard-prone areas. The hazard-prone areas affected by floods featured the highest cropland loss rates, while the areas prone to earthquakes and landslides featured the highest cropland growth rates. We detected areas with significant exposure changes by using hot spot analysis. It was found that population and built-up land in the Pearl River Basin were increasingly exposed to storm surges, floods, and landslides. The Haihe River Basin and Huaihe River Basin also showed a consistent increase of population and built-up land exposure to droughts and earthquakes. These findings can provide a foundation for the design and implementation of protection and adaptation strategies to improve the resilience of Chinese society to natural hazards. [ABSTRACT FROM AUTHOR]

Establishing the usual rent for a built-up land with different landowners and owners of the buildings standing on it is a very specific phenomenon that has been widespread in the past. The aim of our paper is to compile a valid methodology for determining the usual amount of rent for 2016 and verify this procedure on a model example. For the determination of the usual amount of rent for the use of built-up land in 2016, the so-called simulated rent method was used, which is based on the rate of performance of immovable properties. The immovable property performance for 2016 was set at 5%. The usual amount of annual rent for a model built-up land should be, according to the usual prices from 2016, CZK 33,809 according to the used method. [ABSTRACT FROM AUTHOR]

Although research relating to the urban heat island (UHI) phenomenon has been significantly increasing in recent years, there is still a lack of a continuous and clear recognition of the potential gradient effect on the UHI—landscape relationship within large urbanized regions. In this study, we chose the Beijing-Tianjin-Hebei (BTH) region, which is a large scaled urban agglomeration in China, as the case study area. We examined the causal relationship between the LST variation and underlying surface characteristics using multi-temporal land cover and summer average land surface temperature (LST) data as the analyzed variables. This study then further discussed the modeling performance when quantifying their relationship from a spatial gradient perspective (the grid size ranged from 6 to 24 km), by comparing the ordinary least squares (OLS) and geographically weighted regression (GWR) methods. The results indicate that: (1) both the OLS and GWR analysis confirmed that the composition of built-up land contributes as an essential factor that is responsible for the UHI phenomenon in a large urban agglomeration region; (2) for the OLS, the modeled relationship between the LST and its drive factor showed a significant spatial gradient effect, changing with different spatial analysis grids; and, (3) in contrast, using the GWR model revealed a considerably robust and better performance for accommodating the spatial non-stationarity with a lower scale dependence than that of the OLS model. This study highlights the significant spatial heterogeneity that is related to the UHI effect in large-extent urban agglomeration areas, and it suggests that the potential gradient effect and uncertainty induced by different spatial scale and methodology usage should be considered when modeling the UHI effect with urbanization. This would supplement current UHI study and be beneficial for deepening the cognition and enlightenment of landscape planning for UHI regulation.

Abstract Urban expansion and the consequent reduction in cultivated land have disrupted the balance between humans and the land. This study was conducted to characterize landscape patterns and understand how zoning and socioeconomic factors have impacted land-use change. Landscape metrics at the zoning area level were used to quantify changes in landscape patterns for both cultivated and built-up land in Guangzhou, China, from 1980 to 2015. The shift in the centroid tracks and regression analysis were applied to determine the impact of zoning and socioeconomic factors on land-use dynamics. Our results demonstrate an unprecedented period of urban expansion in Guangzhou. A substantial area of cultivated land has been transformed into built-up land, which has led to increasingly aggregated patterns for built-up land and fragmented patterns for cultivated land. The "general urban planning" zoning schemes drive urban expansion in different directions and cause multi-center urban spatial patterns, while increases in GDP and population are not always the main driver for different land use types. Highlights • Substantial areas of cultivated land have been transformed into built-up land. • Cultivated land has become increasingly fragmented, and built-up areas have consolidated. • The zoning scheme has impacted on urban space patterns. • Built-up land was significantly correlated with GDP and population, while cultivated land was not significantly related with either GDP or population. • A comprehensive evidence base should be compiled to support general urban planning. [ABSTRACT FROM AUTHOR]

To study the expansion in the built-up area of Nantong's main urban area during the past 20 years, Landsat multitemporal remote images at 5-year intervals were considered. Further, the index of expansion area and expansion intensity were used to conduct correlation analyses of expansion index and expansion direction. The research results showed that the built-up area of Nantong city expanded remarkably, with the expansion intensity index showing an upward trend initially, followed by a downward trend from 1995 to 2015. Nantong's excellent geographical location and rich cultural history played an important role in the expansion of the built-up area. In addition, Sutong Bridge and other transport constructions constituted the extension direction of the built area traction. Most importantly, the close attention paid to coastal areas by the government and the state has significantly promoted the development of built-up areas. [ABSTRACT FROM AUTHOR]

[Display omitted] • Affected by natural and economic factors, there are differences in the value of ecosystem services and expanded built-up land in China between North and South. • The multi-regional input–output (MRIO) model is used to quantify virtual land transfer among regions. • Part of expanded built-up land serves external regions, with build-up land and ecological costs shifting from south to north. • Economically developed regions dominate regional trade, and regional inequities exist in a few regions. During rapid economic development and urbanisation, land expansion in built-up areas is China's dominant land-use change type, resulting in the loss of ecosystem service value (ESV). Economic development is China's main driving force for built-up land expansion. Under the trend of the spatial separation of production and consumption, expanded built-up land embodied in trade flows between regions as a scarce land resource. Through trade, a region can indirectly use built-up land from outside areas, which may affect land use within the user and provider regions. Regional ESV loss may be affected by outer regions, although previous studies have seldom considered it. Accordingly, this study quantified ESV for the whole of China in high resolution and determined ESV loss caused by expanded built-up land for each province and ESV loss flows embodied in interregional interactions. The results found that China's total ESV of terrestrial ecosystems was 37.44 trillion yuan in 2015, and the expanded built-up land resulted in a loss of 13.7 billion yuan in ESV. Due to the north–south differences in natural and economic levels in China, there was significant spatial heterogeneity in ESV and ESV loss caused by built-up land expansion, with the high-value areas mainly in the southern coastal areas. With regional interaction, the leading regional flow direction of built-up land and ESV loss was from north to south, mainly from economically developing regions to economically developed regions. However, there was a discrepancy between the actual users of the built-up land and the ESV loss-bearers. Evident regional inequalities existed in several provinces with regional interactions. Overall, this study provides a reference for developing China's interregional economic and ecological harmony strategies in the context of sustainable development. [ABSTRACT FROM AUTHOR]

Inter-regional trade contributes to the expansion of built-up land and carbon storage loss, which results in inequality in unequal exchange. Revealing this inequality can help socio-environmental sustainability be better achieved. This paper uses a multi-regional input-output model to analyze the virtual built-up land flows embodied in the inter-provincial trade in China, and calculates the carbon storage loss caused by the expansion of built-up land. The inter-provincial trade inequality in China is discussed subsequently. The results show that regional unfair trade exists in China, and less developed regions are in an inferior position. Compared to less developed regions, developed regions obtain more benefits from inter-provincial trade, in both economic and environmental aspects. Regionally, the expansion of built-up land mainly occurs in the eastern and southern regions, which lost much carbon storage, especially Guangdong and Yunnan. Coastal regions had a high built-up land utilization efficiency, followed by the central regions. The built-up land interactions are mainly concentrated in the central and eastern regions, and the degree of trade participation in less developed regions is low. [ABSTRACT FROM AUTHOR]

The existence of Mount Merapi in Sleman Regency makes the agricultural land so fertile and that becomes the attraction for humans to occupy the region. A high population growth will lead to the people demand of the availability built-up land higher. However, the volcanic activity of Mount Merapi becomes a threat to the people who live in the area of Disaster Prone Areas of Mount Merapi. This study presented an application of multi criteria analysis technique as an approach to deal with the built-up land suitability. Physical and accessibility data such as slope, landform, distance from the river, distance from road, distance from the center of economic activities, and Mount Merapi disaster-prone area will be used as limiting factor of built-up land. The result shows that the majority of Sleman Regency is suitable for built-up land.

The mega cities of China are faced with great pressure from conflict between huge land demand for construction use and limited resources. To improve this situation, it is necessary to slow the increasing rate of built-up land and even reduce the existing built-up land by improving land use efficiency. Herein, land use planning with urban sprawl deceleration is proposed. Land quotas are important tools for the control of land use planning in China, but the current quotas are mainly in the form of increment, thus cannot support land use planning with urban sprawl deceleration. To address these issues, we developed a model named “current-plan-requirement response (CPRR)”, to optimize the land quotas. With this model, we investigated the current status of land use, the process of land use planning, and the requirements of land use planning with urban sprawl deceleration in Shanghai. It was found that the current land quotas have provided somewhat inhabited conversion of arable land to built-up land, but scarcely any regulation of land use efficiency or protection of natural environment. Then, the land quotas were optimized and quota management recommendations were made. The optimized land quotas included four aspects of quotas: arable land protection, ecological conservation, scale constraint on built-up land and economical and intensive land use. These new land quotas could be used to guide reduction of built-up land and increase ecological land in China’s mega cities. It might also be beneficial for easing conflict between supply and demand of built-up land, for building an eco-friendly city land-use structure. [ABSTRACT FROM AUTHOR]

This study proposed a new framework that combines pixel-level change detection and object-level recognition to detect changes of built-up land from high-spatial resolution remote sensing images. First, an adaptive differencing method was designed to detect changes at the pixel level based on both spectral and textural features. Next, the changed pixels were subjected to a set of morphological operations to improve the completeness and to generate changed objects, achieving the transition of change detection from the pixel level to the object level. The changed objects were further recognised through the difference of morphological building index in two phases to indicate changed objects on built-up land. The transformation from changed pixels to changed objects makes the proposed framework distinct with both the pixel-based and the object-based change detection methods. Compared with the pixel-based methods, the proposed framework can improve the change detection capability through the transformation and successive recognition of objects. Compared with the object-based method, the proposed framework avoids the issue of multitemporal segmentation and can generate changed objects directly from changed pixels. The experimental results show the effectiveness of the transformation from changed pixels to changed objects and the successive object-based recognition on improving the detection accuracy, which justify the application potential of the proposed change detection framework. [ABSTRACT FROM AUTHOR]

• We appraise built-up land efficiency and discern inefficient land at multi scales. • We analyze the coupling between BUI and LUE based on multi-source spatial data. • Overloaded built-up land distributes in South YRD, while inefficient in West. • For where built-up land is overloaded, appropriate new urban area is necessary. • Redevelopment is more suitable for where built-up land is inefficient. Irrational built-up land expansion debilitates urban sustainability and leads to environmental decay, food security, and climate change. Using the Yangtze River Delta (YRD) urban agglomeration as an example, this research identifies the mismatch between the intensity and use efficiency of built-up land at multiple scales. Specifically, the study gauges built-up land intensity (BUI) using horizontal layout and vertical height data. Land use efficiency (LUE) is calculated by fusing multi-source spatial data, including nighttime light (NTL), land surface temperature (LST), population density (PD), gross domestic product (GDP), and points of interest (POI). The coupling index (CI) between BUI and LUE determines the misallocation of built-up land resources. The results indicate that BUI and LUE match well in YRD, whereas well-coupled built-up land with high BUI and LUE is concentrated in the eastern YRD. Based on the coupling findings, built-up land can be divided into three categories: overloaded, well-coupled, or inefficient. When built-up land is overloaded, it is essential to notice the excessive concentration of urban functions. On the other hand, reducing land resource waste should be a priority where built-up land is inefficient. This research helps confine irrational urban expansion, deploy rational urban expansion plans, and foster sustainable cities and communities. [ABSTRACT FROM AUTHOR]

Mining is environmentally disruptive which requires tons of earth materials to be removed and causes modification in original land cover. The processing of materials also requires huge amount of energy. In this study, we calculated the Ecological Footprint (EF) of built-up and carbon absorption land for global mining activities with a dataset provided by Werner and colleagues. We first corrected the yield factor and equivalence factor of built-up land. The life cycle inventory to calculate the EF of carbon absorption land was obtained from literatures. According to the findings, tailings storage facility, waste rock dump and riverine tailings disposal had higher EF of built-up land. EF of carbon absorption land was significantly huge, and underground mines had generally higher values than surface mines whereas surface mines had higher EF of built-up land. We also discussed some mechanisms regarding how to reduce the EF of carbon absorption land. [Display omitted] [ABSTRACT FROM AUTHOR]