A comparative analysis of urban impervious surface and green space and their dynamics among 318 different size cities in China in the past 25 years

Evaluation of vegetation restoration effectiveness along the Yangtze River shoreline and its response to land use changes

Assessing the effectiveness of vegetation restoration along the Yangtze River shoreline and exploring its relationship with land use changes are imperative for providing recommendations for sustainable management and environmental protection. However, the impact of vegetation restoration post-implementation of the Yangtze River Conservation Project remains uncertain. In this study, utilizing Sentinel-2 satellite imagery and Dynamic World land use data from pre- (2016) and post- (2022) Yangtze River Conservation Project periods, pixel-based binary models, transition matrices, and geographically weighted regression models were employed to analyze the status and evolution of vegetation coverage along the Yangtze River shoreline. The results indicated that there had been an increase in the area covered by high and high-medium vegetation levels. The proportion of vegetation cover shifting to better was 4201.87 km2 (35.68%). Hotspots of vegetation coverage improvement were predominantly located along the Yangtze River. Moreover, areas witnessing enhanced vegetation coverage experienced notable land use changes, notably the conversion of water to crops (126.93 km2, 22.79%), trees to crops (59.93 km2, 10.76%), and crops to built area (59.93 km2, 10.76%). Notably, the conversion between crops and built area emerged as a significant factor influencing vegetation coverage improvement, with average regression coefficients of 0.68 and 0.50, respectively. These outcomes underscore the significance of this study in guiding ecological environmental protection and sustainable management along the Yangtze River shoreline.

Spatiotemporal variation in sensitivity of urban vegetation growth and greenness to vegetation water content: Evidence from Chinese megacities

Understanding the sensitivity of vegetation growth and greenness to vegetation water content change is crucial for elucidating the mechanism of terrestrial ecosystems response to water availability change caused by climate change. Nevertheless, we still have limited knowledge of such aspects in urban in different climatic contexts under the influence of human activities. In this study, we employed Google Earth Engine (GEE), remote sensing satellite imagery, meteorological data, and Vegetation Photosynthesis Model (VPM) to explore the spatiotemporal pattern of vegetation growth and greenness sensitivity to vegetation water content in three megacities (Beijing, Shanghai, and Guangzhou) located in eastern China from 2001 to 2020. We found a significant increase (slope > 0, p < 0.05) in the sensitivity of urban vegetation growth and greenness to vegetation water content (SLSWI). This indicates the increasing dependence of urban vegetation ecosystems on vegetation water resources. Moreover, evident spatial heterogeneity was observed in both SLSWI and the trends of SLSWI, and spatial heterogeneity in SLSWI and the trends of SLSWI was also present among identical vegetation types within the same city. Additionally, both SLSWI of vegetation growth and greenness and the trend of SLSWI showed obvious spatial distribution differences (e.g., standard deviations of trends in SLSWI of open evergreen needle-leaved forest of GPP is 14.36 × 10-2 and standard deviations of trends in SLSWI of open evergreen needle-leaved forest of EVI is 10.16 × 10-2), closely associated with factors such as vegetation type, climatic conditions, and anthropogenic influences.

Exploring the regional differences of ecosystem health and its spatial relationships with urban forms in China

A deeper understanding of the regional differences and driving factors behind ecosystem health (EH) is of vital for ecosystem management and restoration. Although a considerable number of studies have focused on this topic, few studies have explored the spatial relationship and scale effect between urban forms and EH from the perspective of urban scale, agglomeration and irregularity. Therefore, this study first constructed an improved evaluation framework by integrating vigor, organization, resilience and ecosystem services supply-demand ratio to measure the EH level in China at the county scale during 1995-2015, and then evaluated and compared the spatial relationships between five urban form metrics and EH based on the spatial regression model at the national, regional, urban agglomeration and city scales. The results showed that the level of EH in China spatially decreased from the southeast to the northwest, and displaying significant spatial agglomeration. At the national scale, the fragmentation and complexity of urban form exerted the greater negative influence on EH than urban expansion scale. At the regional scale, controlling urban expansion scale and enhancing landscape connectivity were conducive to the improving of EH in the central and eastern regions. At the urban agglomeration scale, the regularity and compactness of urban form played a key role in the sustainable development of regional and national urban agglomerations. At the city scale, large cities can improve environmental quality by limiting the size of core patches and reducing the complexity of urban shape. This paper can provide a scientific guidance for ecosystem protection and urban high-quality development.

A simplified model for analyzing rainwater retention performance and irrigation management of green roofs with an inclusion of water storage layer

Rainwater retention and water content in green roofs are primarily influenced by structural configurations (i.e., soil layer, vegetation layer, and water storage layer) and climatic factors (i.e., rainfall and evapotranspiration (ET)). Based on the principle of water balance, this study proposes a conceptual model for simulating water flow in green roofs with water storage layers. Three green roof model experiments were conducted from August 1st, 2020 to July 31st, 2021 for calibrating and verifying the conceptual model. The proposed model was solved iteratively using a newly developed program in Visual Basic. The results showed that the conceptual model can capture the dynamic variations in the rainwater retention and water content of green roofs well. The average Nash-Sutcliffe efficiency coefficient is 0.65 and the average error is 6%. The annual rainwater retention capacity (RRC) of green roofs in the perennial rainy climate model was on average 28% higher than that in the seasonal rainy climate model. At the expense of water stress, high ET plants significantly increased the annual RRC of green roofs at a low level. As the water storage layer depth increased from zero to 150 mm, the annual RRC of green roofs increased by 41%, and the water stress decreased by 49%. Compared with an increase in water holding capacity and soil depth, the response of the annual RRC and water stress of green roofs for increasing water storage layer depth is much greater. As per climate of Southern China region, the water storage layer depth of 100 mm is found to obtain optimal rainwater retention and irrigation management in green roof with similar soil thickness (100 mm).

Urban Land-Cover Changes in Major Cities in China from 1990 to 2015

The accelerated urbanization process in China has led to land-cover changes, triggering a series of environmental issues as one of the major drivers of global change. We studied the land-cover changes in the built-up areas of 50 major cities in China from 1990 to 2015 with Landsat data combined with spectral unmixing methods and decision tree classification. The overall accuracy of urban land-cover type products with 30 m resolution was obtained as 84%, which includes impervious surfaces, bare soil, vegetation, and water bodies. Based on these land-cover type products, the results show that the urbanization of major cities in China manifests itself as a steep expansion of impervious surfaces (+32.91%) and vegetation (+36.93%), while the proportion of bare soil (-68.64%) and water bodies (-1.20%) decreases. The increase in vegetation indicates an increasing emphasis on greening during urbanization, which is especially vital for the sustainability of urban ecosystems. Increasing economic standards and population sizes are significantly correlated with impervious surface expansion and may be the main drivers of urbanization. Nationwide, there is a decreasing trend of shape complexity among different large cities, which indicates that landscape shapes will gradually become regular when cities grow to a certain level. Greenspace areas in the cities increased significantly during 1990-2015 and became more fragmented and tended to disperse across cities. These changes reflect the government's efforts to enhance urban ecosystem functions to serve the rapidly increasing urban population in China over the past three decades.

Spatial assortment of soil organisms supports the size-plasticity hypothesis

The size-plasticity hypothesis posits that larger size organisms are less plastic in their metabolic rates and, therefore, are more strongly environmental-filtered than smaller organisms. Many studies have supported this hypothesis by evaluating the relative roles of environmental filtration and dispersal for different taxonomic groups of soil organisms. Most observations are made at large spatial scales, which are assumed to have a wide array of varying habitats. However, since urbanization causes habitat fragmentation at smaller regional scales, testing the size-plasticity hypothesis at this scale would help better understand the spatial assortment of urban soil organisms which, in turn, would help to develop improved management and conservation strategies for urban soil health. Here, we used DNA metabarcoding on five groups of soil biota (bacteria, fungi, protists, nematodes, and invertebrates) to assess the relative importance of dispersal and environmental filters to examine the size-plasticity hypothesis at this spatial scale in an urban environment. We observed strong distance-decay of community similarities associated with higher levels of stochastic changes in bacteria, nematode, and protist communities but not fungal or invertebrate communities. Bacterial communities occupied the widest niche followed by protists and nematodes, potentially because of their higher dispersal abilities compared to the larger soil organisms. Null deviation of communities varied with taxonomic groups where bacteria and nematodes were mainly driven by homogenizing dispersal, protists and fungi by drift, and soil invertebrates by environmental selection. We further identified a small percentage of locally-adapted taxa (2.1%) that could be focal taxa for conservation and restoration efforts by, for example, restoring their habitats and enhancing their regional connectivity. These results support the size-plasticity hypothesis at the relatively unexplored regional scale in an urbanization context, and provide new information for improving urban soil health and sustainable city models.

Evaluation of the Thermal Environmental Effects of Urban Ecological Networks—A Case Study of Xuzhou City, China

Urban heat islands (UHIs) constitute an important ecological problem in cities. Ecological space has a positive effect on UHI mitigation, which can be effectively organized in the form of ecological networks. In this study, the framework for structural UHI improvement based on ecological networks considering the source-corridor model is proposed to examine the spatial threshold of the thermal effect of ecological network factors. Additionally, the cooling mechanism of each constituent element in the ecological network context is further explored. The results demonstrate that (1) an obvious cold and heat island spatial aggregation distribution exists in the Xuzhou main urban area, and land of the same land use type exhibits the dual thermal environmental properties of cold and heat islands through its spatial distribution and characteristics. Ecological space is the main bearing area of cold islands. (2) The ecological network in the main urban area of Xuzhou city occurs at a moderately complex level, and the overall network efficiency is acceptable; the network connectivity is low, while the network loop distribution is uneven. (3) Ecological networks represent an effective spatial means to improve overall UHI patterns. The ecological source area cooling threshold is 300 m, and the optimal threshold is 100 m, while the ecological corridor width threshold is 500 m and 60 m, respectively. (4) Within the optimal threshold in the context of ecological networks, the temperature of ecological sources in category G land is influenced by NDBI and FVC; ecological corridors are mainly influenced by NDBI. The results can provide a quantitative basis for urban ecological network planning considering UHI improvement and a reference for urban thermal environment research within different ecological substrates and planning and control systems in other countries and regions worldwide.

Exploring the Relationship between the Spatial Distribution of Different Age Populations and Points of Interest (POI) in China

Population spatialization data is crucial to conducting scientific studies of coupled human–environment systems. Although significant progress has been made in population spatialization, the spatialization of different age populations is still weak. POI data with rich information have great potential to simulate the spatial distribution of different age populations, but the relationship between spatial distributions of POI and different age populations is still unclear, and whether it can be used as an auxiliary variable for the different age population spatialization remains to be explored. Therefore, this study collected and sorted out the number of different age populations and POIs in 2846 county-level administrative units of the Chinese mainland in 2010, divided the research data by region and city size, and explored the relationship between the different age populations and POIs. We found that there is a complex relationship between POI and different age populations. Firstly, there are positive, moderate-to-strong linear correlations between POI and population indicators. Secondly, POI has a different explanatory power for different age populations, and it has a higher explanatory power for the young and middle-aged population than the child and old population. Thirdly, the explanatory power of POI to different age populations is positively correlated with the urban economic development level. Finally, a small number of a certain kinds of POIs can be used to effectively simulate the spatial distributions of different age populations, which can improve the efficiency of obtaining spatialization data of different age populations and greatly save on costs. The study can provide data support for the precise spatialization of different age populations and inspire the spatialization of the other population attributes by POI in the future.

The spatiotemporal response of China's vegetation greenness to human socio-economic activities

Climate change and human socioeconomic activities both strongly impact long-term vegetation greenness. It is more a challenge to evaluate the impacts of socioeconomic activities on vegetative greenness than climate change, partially due to the lack of appropriate quantitative indicators of the former. Here we examined the relationship between the remote sensing nighttime light (NTL) data and the Normalized Difference Vegetation Index (NDVI), which in this study are used as the proxies of socioeconomic activities and vegetation greenness, respectively. We first eliminated the vegetation greenness changes in response to climate change and calculated the human-activities-induced NDVI (HNDVI). After explored the spatiotemporal patterns of the HNDVI and NTL data across China from 1998 to 2018, we studied the relationship between the HNDVI and NTL at the grid and county levels, respectively. Our results show that the mean adjusted DN values of the NTL data (NTLI) continuously increase (+0.2938) across our study area from 1998 to 2018, whereas the HNDVI values fluctuate with a general upward trend (+0.0018). Most grids (91.2%) with increased HNDVI were found in rural areas, particularly in the Northeast forest shelterbelt and the Loess Plateau. By contrast, the HNDVI values in rapidly urbanized areas in Chinese major urban agglomerations mainly show a downward trend, especially in the Yangtze River Delta (YRD) urban agglomeration. The relationships between the NTLI and HNDVI are inconsistent over time and across space, which could be attributed to land use conditions, afforestation projects in rural areas, and greening activities in urban areas over different periods and regions.

Spatiotemporal patterns and inequity of urban green space accessibility and its relationship with urban spatial expansion in China during rapid urbanization period

Equitable access to urban green spaces (UGS) is an important component of social justice and can be quantified using indices such as urban green space accessibility (UGSA). However, the spatiotemporal patterns and inequity of UGSA among cities with different developments during rapid urbanization are unclear, especially lack evidence at a macroscopic national scale during rapid urbanization. Therefore, we evaluated the UGSA in 366 cities of China during 1990-2015 by the Gaussian-based two-step floating catchment area method (Gaussian-based 2SFCA). Then, the inequity pattern of UGSA among cities with different economic developments was analyzed by the concentration curve and concentration index. Finally, the relationship between UGSA and urban spatial expansion was explored quantitatively by the spatial econometric model. The results showed that: (1) The overall UGSA in China declined significantly by nearly 57.23% during 1990-2015. From the regional perspective, the UGSA in the southeastern region was always lower than that in the northwestern region, the Eastern zone presented a downward trend. From the perspective of different sizes cities, the UGSA of the megacities kept decreasing during 1990-2015, while UGSA of the large, medium, and small cities had turned to increase since 2010. (2) During rapid urbanization, the equity of UGSA among the cities gradually improved, while the cities with low economic developments tended to have higher UGSA. (3) Urban spatial expansion led to the decrease of UGSA during 1990-2015, while the impact had spatiotemporal heterogeneity, and UGSA had a positive spatial spillover effect. Our research provides a comparative baseline for the improvement of UGSA from a macroscopic perspective for China's urbanization policy in the future and novel insights into the green justice issue. The results can be compared with the development of UGS in other countries at different urbanization stages to promote UGS design and policy.

Decrease in the residents' accessibility of summer cooling services due to green space loss in Chinese cities

Urban green spaces (UGSs) reduce the surrounding temperature and create cooling areas as a buffer between people and high temperatures, thus helping residents adapt to the warming climate. However, the accessibility of UGS cooling services to the residents of cities remains largely unknown, which hinders decision-making regarding the formulation of climate adaptation and urban greening schemes. In the present study, we estimated the number of residents who accessed UGSs for cooling by analyzing the annual changes in such cooling areas during summer across 315 Chinese cities from 2003 to 2015. Approximately 93.3% of the cities showed significant decreasing trends (p < 0.05) of the total UGS area; as such the UGS coverage dropped from 12.23 ± 0.32% in 2003 to 7.69 ± 0.22% in 2015. Consequently, with the prevalent loss of UGS, the coverage of cooling spaces decreased from 32.55 ± 0.76% in 2003 to 24.39 ± 0.60% in 2015. This has formed a spatial mismatch between the growing urban population and the remaining UGSs. Accordingly, the number of residents of areas outside these cooling spaces increased by 4.23 million per year. In particular, the shortage of cooling services was more significant in cities with < 20,000 USD gross domestic product per capita and < 5 million residents than in the rest of the cities. To minimize the adverse impacts of increasing temperatures, focused greening plans are warranted, specifically in underdeveloped cities.

Spatial-temporal patterns and influencing factors of ecological land degradation-restoration in Guangdong-Hong Kong-Macao Greater Bay Area

Despite the fact that urban agglomerations have undergone extensive ecological land coverage modifications, exploration of the patterns and driving mechanisms associated with ecological land degradation (ELD) and ecological land restoration (ELR) in urban agglomerations is still limited. This study combined remote sensing technology, as well as landscape index and geographical detector to characterize the spatiotemporal patterns of ELD (isolating, adjacent, and enclosing degradation) and ELR (outlying, edge-expansion, and infilling restoration) in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) from 1990 to 2019. Subsequently, the contributions, interactions, and driver changes were quantified. The results showed an ecological land shift from over-exploitation to balanced co-existence, which was facilitated by a spatiotemporal pattern transition from adjacent degradation-led (1990-2010) to edge-expansion restoration-led (2010-2019). Land urbanization rate and population density showed a stronger promoting effect on ELD than natural factors, while tertiary industry, topography, and soil conditions were more significant in ELR. The factors' nonlinear interaction enhanced the degradation-restoration pattern evolution and continued to increase over time-particularly the interaction between construction land expansion and other drivers. Additionally, from 2010 to 2019, 80% of the ELR socio-economic factors turned from negative to positive and gradually became to play a significant role. This study is expected to help ecological protection and restoration planners/managers recognize the factors' interactions and variations, and ultimately improve the ecological network structure that is designed to integrate the city with the ecosystem.

Prioritizing sponge city sites in rapidly urbanizing watersheds using multi-criteria decision model

Spatial planning is crucial for sponge city (SC) construction; however, prioritizing SC sites at the watershed scale has not been fully explored. In this study, a multi-criteria decision model, considering demand and suitability of SC construction, was established by monitoring, model simulation, and index calculation. This new model was then tested in a rapidly urbanizing watershed, Beijing, China, and the priority of SC construction at both grid scale (1km×1km) and subwatershed scale was ranked. The results showed that the highest priority was found in emerging regions where urbanization is ongoing and followed by urban core areas. In addition, six indexes were identified by clustering heatmaps as key factors affecting the priority of SC planning, including topographic index, water pollution index, pollution rate based on the state standard of surface water environment quality, urbanization planning, urban levels, and vegetation index, which could guide SC planning in data-lacking regions. The approach and findings in this study cannot only provide helpful references for watershed managers and urban planners but also can be easily used in other regions.

Spatial-Temporal Changes and Driving Force Analysis of Green Space in Coastal Cities of Southeast China over the Past 20 Years

The purpose of this study is to reveal the spatial-temporal change and driving factors of green space in coastal cities of southeast China over the past 20 years. A supervised classification method combining support vector machines (SVMs) and visual interpretation was used to extract the green space from Landsat TM/OLI imageries from 2000–2020. The landscape pattern index was used to calculate geospatial information of green space and analyze their spatial-temporal changes. The hierarchical partitioning analysis was then used to determine the influences of anthropogenic and geographic environmental factors on the spatial-temporal changes in green space. The results indicated that the total area of green space remained constant over the past 20 years in coastal cities of southeast China (1% reduction). The spatial change of green space mainly occurred in the area near the ocean and the southern region. 41.37% of forest land was transferred from cultivated land, while 44.56%, 41.83%, 43.20%, 46.31%, 41.98% and 40.20% of shrub land, sparse woodland, other woodland, high-coverage grassland, moderate-coverage grassland and low-coverage grassland were transferred from forest land. The number of patches, patch density, edge density, landscape shape index and Shannon’s diversity index increased from 2000–2015, and then decreased to the minimum in 2020, while largest patch index continued to decline from 2000–2020. The contribution of anthropogenic factors (0.53–0.61) on the spatial-temporal changes of green space continually increased over the past 20 years, which was also higher than geographical environment factors (0.39–0.41). Our study provides a new perspective to distinguish the impact of anthropogenic activities and geographical environmental factors on the change of green space area, thereby providing a theoretical support for the construction and ecological management of green space.

Impacts of rapid urbanization on characteristics, sources and variation of fecal coliform at watershed scale

Microbial pollution is an environmental problem of growing concern for threatening human health. However, the impacts of rapid urbanization on characteristics, sources and variation of fecal coliform (FC) at watershed scale have not been fully explored. In this study, FC characteristics were monitored monthly for 2 years at 21 river sections in an urbanizing watershed, while the sources and continuously annual variation were quantified by integrating two commonly-used models. The results showed that FC varied from 10³ to 10⁶ MPN/L, indicating a great spatiotemporal variation at watershed scale. Peak FC occurred in summer and autumn among upstream and downstream areas, respectively. Besides, 65% impermeable surface was identified as the threshold of urban level, beyond which the key FC source would shift from agriculture to urban. It was also found that the changes of urban landscape patterns had poor correlation with annual variation of FC. In comparison, urbanization speed was identified as the major driver with the threshold of 30% for deteriorating FC pollution. The Low Impact Development could result in a 5.13%-97.59% reduction of FC at watershed scale.

Impacts of Urban Expansion Forms on Ecosystem Services in Urban Agglomerations: A Case Study of Shanghai-Hangzhou Bay Urban Agglomeration

Exploring impacts of urban expansion on ecosystem services has become a hot topic for regional sustainable development, while analyzing the ecological effects of urban expansion forms under different expansion intensities and city sizes is relatively rare. Therefore, taking a typical urban agglomeration, Shanghai-Hangzhou Bay Urban Agglomeration, as a case study, this study first analyzed the dynamics of urban expansion forms (leapfrogging, edge-expansion, and infilling) and four critical ecosystem services (carbon sequestration, food supply, habitat quality, and soil retention) in three periods from 1990 to 2019. The multiple linear regression model and zonal statistics analysis model were used to quantitatively identify the impacts of urban expansion forms on ecosystem services, taking into account different expansion intensities and city sizes. The results showed that the urban expansion trend in the study area experienced a morphological change from integration to diffusion and then to integration in 1990–2019; edge-expansion was the dominant expansion form. Food supply decreased continuously while other ecosystem services had fluctuating changes, and they all had spatial heterogeneity. The leapfrogging, edge-expansion, and infilling all had negative impacts on ecosystem services, and among them, the edge-expansion intensity had the highest influence degree in the early expansion, and the leapfrogging intensity occupied the dominant position in all influences with the expansion of urban scales. For different city sizes, the impact of edge-expansion in large-scale cities was greater than in small-scale cities in the early expansion, and the impact of leapfrogging in large-scale cities exceeded the edge-expansion in the subsequent expansion. These findings will help further understand the influential mechanisms between urban expansion and ecosystem services and provide a scientific basis for formulating reasonable urban planning.

A Preliminary Study on the Impact of Landscape Pattern Changes Due to Urbanization: Case Study of Jakarta, Indonesia

Urbanization is changing land use–land cover (LULC) transforming green spaces (GS) and bodies of water into built-up areas. LULC change is affecting ecosystem services (ES) in urban areas, such as by decreasing of the water retention capacity, the urban temperature regulation capacity and the carbon sequestration. The relation between LULC change and ES is still poorly examined and quantified using actual field data. In most ES studies, GS is perceived as lumped areas instead of distributed areas, implicitly ignoring landscape patterns (LP), such as connectivity and aggregation. This preliminary study is one of the first to provide quantitative evidence of the influence of landscape pattern changes on a selection of urban ecosystem services in a megacity as Jakarta, Indonesia. The impact of urbanization on the spatiotemporal changes of ES has been identified by considering connectivity and aggregation of GS. It reveals that LP changes have significantly decreased carbon sequestration, temperature regulation, and runoff regulation by 10.4, 12.4, and 11.5%, respectively. This indicates that the impact of GS on ES is not only determined by its area, but also by its LP. Further detailed studies will be needed to validate these results.

Assessing Suitability of Human Settlements in High-Altitude Area Using a Comprehensive Index Method: A Case Study of Tibet, China

With the steady advancement of the United Nations Sustainable Development Goals (SDGs), how to build a sustainable environment for human settlements has become a hot topic of research for scholars from various countries. Rational space utilization and resource allocation are the keys to enhancing human well-being and achieving sustainable human settlements. A comprehensive human settlement environment evaluation system, which includes 14 indicators from the natural environment, infrastructure, and public services, was established in this study. The results showed that the habitat suitability area only accounted for 1.61% (2.05% after removing the nature reserve) and all centered on cities and radiated to the surrounding areas. A belt-like suitability distribution pattern of “Yi Jiang Liang He” (i.e., Brahmaputra, Lhasa, and Nianchu Rivers) is formed, and a point-like suitability distribution pattern of the Chamdo Karub District, Nagqu Seni District, and Ngari Shiquanhe Town are formed. The results of the driving factor analysis indicate that the level of public health development in infrastructure and various indicators in public services are the main factors influencing human settlement. There is not much difference in the natural environment in the populated regions, so the suitability of the natural environment is not a significant driving factor. In addition, the reliability of the assessment results was verified by a questionnaire survey of residents in the three regions, and the subjective satisfaction of the residents agreed with the ranking results of the objective evaluation. The evaluation results of this study provide theoretical and directional guidance for the improvement of human settlements on the Qinghai–Tibet Plateau. It will be a useful tool for evaluating human settlements in the region and has a reference significance for the formulation of macro-policy in high-altitude regions.

Exploring the Dynamics of Urban Greenness Space and Their Driving Factors Using Geographically Weighted Regression: A Case Study in Wuhan Metropolis, China

Urban greenness plays a vital role in supporting the ecosystem services of a city. Exploring the dynamics of urban greenness space and their driving forces can provide valuable information for making solid urban planning policies. This study aims to investigate the dynamics of urban greenness space patterns through landscape indices and to apply geographically weighted regression (GWR) to map the spatially varied impact on the indices from economic and environmental factors. Two typical landscape indices, i.e., percentage of landscape (PLAND) and aggregation index (AI), which measure the abundance and fragmentation of urban greenness coverage, respectively, were taken to map the changes in urban greenness. As a case study, the metropolis of Wuhan, China was selected, where time-series of urban greenness space were extracted at an annual step from the Landsat collections from Google Earth Engine during 2000–2018. The study shows that the urban greenness space not only decreased significantly, but also tended to be more fragmented over the years. Road network density, normalized difference built-up index (NDBI), terrain elevation and slope, and precipitation were found to significantly correlate to the landscape indices. GWR modeling successfully captures the spatially varied impact from the considered factors and the results from GWR modeling provide a critical reference for making location-specific urban planning.

Analysing the Driving Forces and Environmental Effects of Urban Expansion by Mapping the Speed and Acceleration of Built-Up Areas in China between 1978 and 2017

Abundant data sets produced from long-term series of high-resolution remote sensing data have made it possible to explore urban issues across different spatiotemporal scales. Based on a 40-year impervious area data set released by Tsinghua University, a method was developed to map the speed and acceleration of urban built-up areas. With the mapping results of the two indices, we characterised the spatiotemporal dynamics of built-up area expansion and captured different types of expansion. Combined with socioeconomic data, we examined the temporal changes and spatial heterogeneity of driving forces with an ordinary least square (OLS) model and a panel data model, as well as exploring the environmental effects of the expansion. Our results reveal that China has experienced drastic urban expansion over the last four decades. Among all cities, megacities and large cities in eastern China, as well as megacities in central and northeast China have experienced the most dramatic urban expansion. A growing number of cities are categorised as thriving, which means that they have both high expansion speed and acceleration. The overall driving force of urban expansion has significantly increased. More specifically, it was associated with population increase in the early stages; however, since 2000, it has been substantially associated with increases in GDP and fixed asset investments. The major driving factors also differ between regions and urban sizes. Urban expansion is identified as being closely associated with environmental deterioration; thus, speed and acceleration should be included as key indicators in exploring the environmental effects of urban expansion. In summary, the results of the presented case study, based on a data set of China, indicate that speed and acceleration are useful in analysing the driving forces of urban expansion and its environmental effects, and may generate more interest in related research.

Combined Effects of Impervious Surface Change and Large-Scale Afforestation on the Surface Urban Heat Island Intensity of Beijing, China Based on Remote Sensing Analysis

Urban heat island (UHI) attenuation is an essential aspect for maintaining environmental sustainability at a local, regional, and global scale. Although impervious surfaces (IS) and green spaces have been confirmed to have a dominant effect on the spatial differentiation of the urban land surface temperature (LST), comprehensive temporal and quantitative analysis of their combined effects on LST and surface urban heat island intensity (SUHII) changes is still partly lacking. This study took the plain area of Beijing, China as an example. Here, rapid urbanization and a large-scale afforestation project have caused distinct IS and vegetation cover changes within a small range of years. Based on 8 scenes of Landsat 5 TM/7ETM/8OLI images (30 m × 30 m spatial resolution), 920 scenes of EOS-Aqua-MODIS LST images (1 km × 1 km spatial resolution), and other data/information collected by different approaches, this study characterized the interrelationship of the impervious surface area (ISA) dynamic, forest cover increase, and LST and SUHII changes in Beijing’s plain area during 2009–2018. An innovative controlled regression analysis and scenario prediction method was used to identify the contribution of ISA change and afforestation to SUHII changes. The results showed that percent ISA and forest cover increased by 6.6 and 10.0, respectively, during 2009–2018. SUHIIs had significant rising tendencies during the decade, according to the time division of warm season days (summer days included) and cold season nights (winter nights included). LST changes during warm season days responded positively to a regionalized ISA increase and negatively to a regionalized forest cover increase. However, during cold season nights, LST changes responded negatively to a slight regionalized ISA increase, but positively to an extensive regionalized ISA increase, and LST variations responded negatively to a regionalized forest cover increase. The effect of vegetation cooling was weaker than ISA warming on warm season days, but the effect of vegetation cooling was similar to that of ISA during cold season nights. When it was assumed that LST variations were only caused by the combined effects of ISA changes and the planting project, it was found that 82.9% of the SUHII rise on warm season days (and 73.6% on summer days) was induced by the planting project, while 80.6% of the SUHII increase during cold season nights (and 78.9% during winter nights) was caused by ISA change. The study presents novel insights on UHI alleviation concerning IS and green space planning, e.g., the importance of the joint planning of IS and green spaces, season-oriented UHI mitigation, and considering the thresholds of regional IS expansion in relation to LST changes.

Co-Evolution of Emerging Multi-Cities: Rates, Patterns and Driving Policies Revealed by Continuous Change Detection and Classification of Landsat Data

The co-evolution of multi-cities has emerged as the primary form of urbanization in China in recent years. However, the processes, patterns, and coordination are not well characterized and understood, which hinders the understanding of the driving forces, consequences, and management of polycentric urban development. We used the Continuous Change Detection and Classification (CCDC) algorithm to integrate all available Landsat 5, 7, and 8 images and map annual land use and land cover (LULC) from 2001 to 2017 in the Chang–Zhu–Tan urban agglomeration (CZTUA), a typical urban agglomeration in China. Results showed that the impervious surface in the study area expanded by 371 km2 with an annual growth rate of 2.25%, primarily at the cost of cropland (169 km2) and forest (206 km2) during the study period. Urban growth has evolved from infilling being the dominant type in the earlier period to mainly edge-expansion and leapfrogging in the core cities, and from no dominant type to mainly leapfrogging in the satellite cities. The unfolding of the “cool center and hot edge” urban growth pattern in CZTUA, characterized by higher expansion rates in the peripheral than in the core cities, may signify a new form of the co-evolution of multi-cities in the process of urbanization. Detailed urban management and planning policies in CZTUA were analyzed. The co-evolution of multi-cities principles need to be studied in more extensive regions, which could help policymakers to promote sustainable and livable development in the future.

Recording Urban Land Dynamic and Its Effects during 2000–2019 at 15-m Resolution by Cloud Computing with Landsat Series

Cities, the core of the global climate change and economic development, are high impact land cover land use change (LCLUC) hotspots. Comprehensive records of land cover land use dynamics in urban regions are essential for strategic climate change adaption and mitigation and sustainable urban development. This study aims to develop a Google Earth Engine (GEE) application for high-resolution (15-m) urban LCLUC mapping with a novel classification scheme using pan-sharpened Landsat images. With this approach, we quantified the annual LCLUC in Changchun, China, from 2000 to 2019, and detected the abrupt changes (turning points of LCLUC). Ancillary data on social-economic status were used to provide insights on potential drivers of LCLUC by examining their correlation with change rate. We also examined the impacts of LCLUC on environment, specifically air pollution. Using this approach, we can classify annual LCLUC in Changchun with high accuracy (all above 0.91). The change detection based on the high-resolution wall-to-wall maps show intensive urban expansion with the compromise of cropland from 2000 to 2019. We also found the growth of green space in urban regions as the result of green space development and management in recent years. The changing rate of different land types were the largest in the early years of the observation period. Turning points of land types were primarily observed in 2009 and 2010. Further analysis showed that economic and industry development and population migration collectively drove the urban expansion in Changchun. Increasing built-up areas could slow wind velocity and air exchange, and ultimately led to the accumulation of PM2.5. Our implement of pan-sharpened Landsat images facilitates the wall-to-wall mapping of temporal land dynamics at high spatial resolution. The primary use of GEE for mapping urban land makes it replicable and transferable by other users. This approach is a first crucial step towards understanding the drivers of change and supporting better decision-making for sustainable urban development and climate change mitigation.

Investigating the Patterns and Dynamics of Urban Green Space in China’s 70 Major Cities Using Satellite Remote Sensing

Urban green space (UGS) plays a pivotal role in improving urban ecosystem services and building a livable environment for urban dwellers. However, remotely sensed investigation of UGS at city scale is facing a challenge due to the pixels’ mosaics of buildings, squares, roads and green spaces in cities. Here we developed a new algorithm to unmix the fraction of UGS derived from Landsat TM/ETM/8 OLI using a big-data platform. The spatiotemporal patterns and dynamics of UGSs were examined for 70 major cities in China between 2000 and 2018. The results showed that the total area of UGS in these cities grew from 2780.66 km2 in 2000 to 6764.75 km2 in 2018, which more than doubled its area. As a result, the UGS area per inhabitant rose from 15.01 m2 in 2000 to 18.09 m2 in 2018. However, an uneven layout of UGS occurred among the coastal, western, northeastern and central zones. For example, the UGS percentage in newly expanded urban areas in the coastal zone rose significantly in 2000–2018, with an increase of 2.51%, compared to the decline in UGS in cities in the western zone. Therefore, the effective strategies we have developed should be adopted to show disparities and promote green infrastructure capacity building in those cities with less green space, especially in western China.