Urban expansion dynamics and natural habitat loss in China: a multiscale landscape perspective

Multi-Scale Analysis of Green Space for Human Settlement Sustainability in Urban Areas of the Inner Mongolia Plateau, China

Green space in intra-urban regions plays a significant role in improving the human habitat environment and regulating the ecosystem service in the Inner Mongolian Plateau of China, the environmental barrier region of North China. However, a lack of multi-scale studies on intra-urban green space limits our knowledge of human settlement environments in this region. In this study, a synergistic methodology, including the main process of linear spectral decomposition, vegetation-soil-impervious surface area model, and artificial digital technology, was established to generate a multi-scale of green space (i.e., 15-m resolution intra-urban green components and 0.5-m resolution park region) and investigate multi-scale green space characteristics as well as its ecological service in 12 central cities of the Inner Mongolian Plateau. Results showed that: (1) Total urban areas and urban green space across the studied cities were 1249.87 km2 and 295.40 km2, indicating that the average proportion of green space to urban areas was 24.03%. (2) The proportion of green space to urban areas ranged from 17.09% to 32.17%, and the proportion of parks’ green space to green space ranged from 5.55% to 50.20%, indicating a wide range of quantitative discrepancies. (3) In different climate regions, there were higher proportions of urban/park green space in arid/semi-arid areas to reduce the impacts of dry climate on human settlements; by contrast, lower green space in humid areas mainly displayed a scattered pattern because of the relatively lower influence of climate pressure. (4) Green coverage was an essential indicator of the “Beautiful China” project, and its ratio within 500-m ecological service zones from parks across all cities was 46.14%, which indicated that the ratio of residential land and green space was close to 1:1. Overall, urban/park green space patterns in urban areas adapted to the different climate features in the Inner Mongolian Plateau. For better human settlement sustainability across all studied cities, more greening patches and ecological corridors should be designed in the lower green space regions of the Inner Mongolian Plateau.

Urbanization Impacts on Natural Habitat and Ecosystem Services in the Guangdong-Hong Kong-Macao “Megacity”

The population aggregation and built-up area expansion caused by urbanization can have significant impacts on the supply and distribution of crucial ecosystem services. The correlation between urbanization and ecosystem services has been well-studied, but additional research is needed to better understand the spatiotemporal interactions between ecosystem services and urbanization processes in highly urbanized areas as well as surrounding rural areas. In this paper, the relationships of urbanization with natural habitat and three key regulating ecosystem services—water retention, soil conservation, and carbon sequestration, were quantified and mapped for the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), a rapidly developing urban agglomeration of over 70 million people, for the period of 2000–2018. Our results showed that urbanization caused a general decline in ecosystem services, and urbanization and ecosystem services exhibited a negative spatial correlation. However, this relationship varied along urban-rural gradients and weak decoupling was the overall trend during the course of the study period, indicating a greater need for the protection and improvement of ecosystem services. Our results provide instructive insights for new urbanization planning to maintain regional ecosystem services and sustainable development in the GBA and other large, rapidly urbanized agglomerations.

Transformation of Local People’s Property Rights Induced by New Town Development (Case Studies in Peri-Urban Areas in Indonesia)

New town development as a form of large-scale development is not a new phenomenon, particularly in developing countries. This development mainly takes place in peri-urban areas due to the high pressure caused by the growing population and the lack of facilities and infrastructure in city centres. As an effect, local communities who originally occupied the land often lose their rights over the property their livelihood might have relied on. Property rights can be grouped differently, classified according to different bundles: appropriation, ownership, and formality of rights. This paper investigates to what extent new town development in Indonesia has affected the property rights of local communities, in terms of the transformation of rights and security level. Moreover, it examines to what extent this transformation has been affected by urbanisation pressure. Ample attention is paid to the transformation of various bundles of rights concerning different usage of property, both residential and cultivated land. A total of 252 questionnaires were distributed to three different locations of new towns in Indonesia. A before-after analysis was employed to identify the transformation of the property rights and their security level, followed by multiple linear regression analysis to observe the influence of the urbanisation pressure to the security level. The research reveals that the transformation of property rights of local residents mainly concerns the appropriation rights. The analysis also indicates that there is a tendency that the security level decreases. Statistically, this appears to be affected by urbanisation pressure variables: type of land, land use, and occupation. With this study, we offer on the one hand a conceptual framework for assessing property rights, while on the other hand, we provide empirical evidence regarding the effects of new town development on property rights transformation and its security level.

Vegetation Phenology Influenced by Rapid Urbanization of The Yangtze Delta Region

Impacts of urbanization and climate change on ecosystems are widely studied, but these drivers of change are often difficult to isolate from each other and interactions are complicated. Ecosystem responses to each of these drivers are perhaps most clearly seen in phenology changes due to global climate change (warming climate) and urbanization (heat island effect). The phenology of vegetation can influence many important ecological processes, including primary production, evapotranspiration, and plant fitness. Therefore, evaluating the interacting effects of urbanization and climate change on vegetation phenology has the potential to provide information about the long-term impact of global change. Using remotely sensed time series of vegetation on the Yangtze River Delta in China, this study evaluated the impacts of rapid urbanization and climate change on vegetation phenology along an urban to rural gradient over time. Phenology markers were extracted annually from an 18-year time series by fitting the asymmetric Gaussian function model. Thermal remote sensing acquired at daytime and nighttime was used to explore the relationship between land surface temperature and vegetation phenology. On average, the spring phenology marker was 9.6 days earlier and the autumn marker was 6.63 days later in urban areas compared with rural areas. The spring phenology of urban areas advanced and the autumn phenology delayed over time. Across space and time, warmer spring daytime and nighttime land surface temperatures were related to earlier spring, while autumn daytime and nighttime land surface temperatures were related to later autumn phenology. These results suggest that urbanization, through surface warming, compounds the effect of climate change on vegetation phenology.

Dynamic Changes of Net Primary Productivity and Associated Urban Growth Driving Forces in Guangzhou City, China

Urban growth has caused environmental problems around the world and profoundly altered the terrestrial carbon cycle, especially net primary productivity (NPP). Sustainable urban development requires a better understanding of the impacts of urban growth on ecosystems. We selected Guangzhou City to analyze the impacts of urban development processes and urban geographic changes on NPP, as well as the correlation between urbanization intensity and NPP, using a deep-learning urbanization characteristic index (UCI). The results showed that the NPP in the study area had clear spatial heterogeneity and declined overall from 2001 to 2013. Guangzhou's urbanization became more and more intense, the mean UCI increased significantly from 0.1293 in 2001 to 0.2879 in 2013, and urban geographic type was dominated by urban exurbs in 2001 and 2013 while urban fringe areas increased most significantly and about 2,320.24 km² of urban exurbs were converted to urban fringes. There was a significant negative correlation between UCI and NPP in 2001 and 2013, implying that NPP had been negatively influenced by the increasing urban development intensity. The transition of urban exurbs to urban fringes was associated with the highest NPP losses, which was caused by cropland loss and built-up land expansion.

Future Impacts of Land Use Change on Ecosystem Services under Different Scenarios in the Ecological Conservation Area, Beijing, China

Ecosystem services (ES), defined as benefits provided by the ecosystem to society, are essential to human well-being. However, it remains unclear how they will be affected by land-use changes due to lack of knowledge and data gaps. Therefore, understanding the response mechanism of ecosystem services to land-use change is critical for developing systematic and sound land planning. In this study, we aimed to explore the impacts of land-use change on the three ecosystem services, carbon storage (CS), flood regulation (FR), and soil conservation (SC), in the ecological conservation area of Beijing, China. We first projected land-use changes from 2015 to 2030, under three scenarios, i.e., Business as Usual (BAU), Ecological Land Protection (ELP), and Rapid Economic Development (RED), by interactively integrating the Markov model (Quantitative simulation) with the GeoSOS-FLUS model (Spatial arrangement), and then quantified the three ecosystem services by using a spatially explicit InVEST model. The results showed that built-up land would have the most remarkable growth during 2015–2030 under the RED scenario (2.52% increase) at the expense of cultivated and water body, while forest land is predicted to increase by 152.38 km2 (1.36% increase) under the ELP scenario. The ELP scenario would have the highest amount of carbon storage, flood regulation, and soil conservation, due to the strict protection policy on ecological land. The RED scenario, in which a certain amount of cultivated land, water body, and forest land is converted to built-up land, promotes soil conservation but triggers greater loss of carbon storage and flood regulation capacity. The conversion between land-use types will affect trade-offs and synergies among ecosystem services, in which carbon storage would show significant positive correlation with soil conservation through the period of 2015 to 2030, under all scenarios. Together, our results provide a quantitative scientific report that policymakers and land managers can use to identify and prioritize the best practices to sustain ecosystem services, by balancing the trade-offs among services.

Effects of urban forms on CO2 emissions in China from a multi-perspective analysis

Effectively evaluating the effects of urban forms on CO₂ emissions has become a hot topic in socioeconomic sustainable development; however, few studies have been able to explore the urban form-CO₂ emission relationships from a multi-perspective view. Here, we attempted to analyze the relationships between urban forms and CO₂ emissions in 264 Chinese cities, with explicit consideration of the government policies, urban area size, population size, and economic structure. First, urban forms were calculated using the urban land derived from multiple-source remote sensing data. Second, we collected and processed CO₂ emissions and three control variables. Finally, a correlation analysis was implemented to explore whether and to what extent the spatial patterns of urban forms were associated with CO₂ emissions. The results show that urban form irregularity had a more significant impact on CO₂ emissions in low-carbon pilot cities than in non-pilot cities. The impact of the complexity of urban forms on CO₂ emissions was relatively significant in the small- and large-sized cities than in the medium-sized cities. Moreover, urban form complexity had a significant correlation with CO₂ emissions in all of the cities, the level of which basically increased with the population size. This study provides scientific bases for use in policy-making to prepare effective policies for developing a low-carbon economy with consideration of the associations between urban forms and CO₂ emissions in different scenarios.

A Spatiotemporal Analysis of the Effects of Urbanization’s Socio-Economic Factors on Landscape Patterns Considering Operational Scales

Landscape patterns are significantly affected during the urbanization process. Identifying the spatiotemporal impacts of urbanization’s socio-economic factors on landscape patterns is very important and can provide scientific evidence to support urban ecological management and guide managers to establish appropriate sustainability policies. This article applies multiscale geographically weighted regression (MGWR) to reveal the relationships between landscape patterns and the socio-economic factors of urbanization in Shenzhen, China, from 2000 to 2015, in five-year intervals. MGWR is a powerful extension of geographically weighted regression (GWR) that can not only reveal spatial heterogeneity patterns but also measure the operational scale of covariates. The empirical results indicate that MGWR is superior to GWR. Furthermore, the changes in operational scale represented by the spatial bandwidth of MGWR in different years reflect temporal changes in the spatial relationships of given factors, which is significant information for urban studies. These multiscale relationships between landscape patterns and the socio-economic factors of urbanization, revealed via MGWR, are useful for strategic planning around urban dynamic development and land resource and ecological landscape management. The results can provide additional insight into landscape and urbanization studies from a multiscale perspective, which is important for local, regional, and global urban planning.

Assessing the role of high-speed rail in shaping the spatial patterns of urban and rural development: A case of the Middle Reaches of the Yangtze River, China

China has experienced rapid residential land expansion in both urban and rural areas over the past three decades, causing complex ecological and environmental challenges. Much research attention has been paid on urbanisation, yet little is known about rural development. In this study, we analysed and compared the changes in a selected number of landscape indices describing the spatial patterns of both urban and rural area in the Middle Reaches of the Yangtze River in central China from 2005 to 2015 and explored how these changes could be associated with the development of high-speed rail (HSR) using spatial error models. We found a partial synchronised spatial development pattern between urban and rural areas in central China, with an increasingly fragmented pattern for both urban and rural areas, albeit rural areas were expanded in a less contiguous but more complex and dispersed fashion. The impacts of the provision of HSR services on the region's spatial development were found to be multi-level. It was associated with greater urban expansion and dispersion at the county/district level and amplified rural patch size and complexity at the patch level. The departure frequency of HSR trains and proximity to HSR station were found to have affected the magnitude of the impact of HSR service provision on regional spatial development. Our results shed lights on the spatio-temporal evolution of an ecologically important region, add new evidence into the expanding fields of urban and rural morphological studies in China, and provide valuable decision support information for integrated spatial planning of transportation and land use.

Global projections of future urban land expansion under shared socioeconomic pathways

Despite its small land coverage, urban land and its expansion have exhibited profound impacts on global environments. Here, we present the scenario projections of global urban land expansion under the framework of the shared socioeconomic pathways (SSPs). Our projections feature a fine spatial resolution of 1 km to preserve spatial details. The projections reveal that although global urban land continues to expand rapidly before the 2040s, China and many other Asian countries are expected to encounter substantial pressure from urban population decline after the 2050s. Approximately 50-63% of the newly expanded urban land is expected to occur on current croplands. Global crop production will decline by approximately 1-4%, corresponding to the annual food needs for a certain crop of 122-1389 million people. These findings stress the importance of governing urban land development as a key measure to mitigate its negative impacts on food production.

Spatiotemporal Analysis of the Nonlinear Negative Relationship between Urbanization and Habitat Quality in Metropolitan Areas

Urbanization intensity (UI) affects habitat quality (HQ) by changing land patterns, nutrient conditions, management, etc. Therefore, there is a need for studies on the relationship between UI and HQ and quantification of separate urbanization impacts on HQ. In this study, the relationship between HQ and UI and the direct and indirect impacts of urbanization on HQ were analyzed for the Yangtze River Delta Urban Agglomeration (YRDUA) from 1995 to 2010. The results indicated that the regional relationship between HQ and UI was nonlinear and negative, with inflection points where urbanization reached 20% and 80%. Furthermore, depending on different urbanization impacts, the relationship types generally changed from a steady decrease to stable in different cities. Negative indirect impacts accelerate habitat degradation, while positive impacts partially offset habitat degradation caused by land conversion. The average offset extent was approximately 28.23%, 17.41%, 22.94%, and 16.18% in 1995, 2000, 2005, and 2010, respectively. Moreover, the dependency of urbanization impacts on human demand in different urbanization stages was also demonstrated. The increasing demand for urban land has exacerbated the threat to ecological areas, but awareness about the need to protect ecological conditions began to strengthen after the antagonistic stage of urbanization.

Spatiotemporal Dynamics and Driving Forces of Urban Land-Use Expansion: A Case Study of the Yangtze River Economic Belt, China

It is important to analyze the expansion of an urban area and the factors that drive its expansion. Therefore, this study is based on Defense Meteorological Satellite Program Operational Linescan System (DMSP/OLS) night lighting data, using the landscape index, spatial expansion strength index, compactness index, urban land fractal index, elasticity coefficient, the standard deviation ellipse, spatial correlation analysis, and partial least squares regression to analyze the spatial and temporal evolution of urban land expansion and its driving factors in the Yangtze River Economic Belt (YREB) over a long period of time. The results show the following: Through the calculation of the eight landscape pattern indicators, we found that during the study period, the number of cities and towns and the area of urban built-up areas in the YREB are generally increasing. Furthermore, the variations in these landscape pattern indicators not only show more frequent exchanges and interactions between the cities and towns of the YREB, but also reflect significant instability and irregularity of the urbanization development in the YREB. The spatial expansion intensity indices of 1992–1999, 1999–2006, and 2006–2013 were 0.03, 0.16, and 0.34, respectively. On the whole, the urban compactness of the YREB decreased with time, and the fractal dimension increased slowly with time. Moreover, the long axis and the short axis of the standard deviation ellipse of the YREB underwent a small change during the inspection period. The spatial distribution generally showed the pattern of “southwest-north”. In terms of gravity shift, during the study period, the center of gravity moved from northeast to southwest. In addition, the Moran's I values for the four years of 1992, 1999, 2006, and 2013 were 0.451, 0.495, 0.506, and 0.424, respectively. Furthermore, by using correlation analysis, we find that the correlation coefficients between these four driving indicators and the urban expansion of the YREB were: 0.963, 0.998, 0.990 and 0.994, respectively. Through the use of partial least squares regression, we found that in 1992-2013, the four drivers of urban land expansion in the YREB were ranked as follows: gross domestic product (GDP), total fixed asset investment, urban population, total retail sales of consumer goods.

Expansion of Impervious Surfaces and Their Driving Forces in Highly Urbanized Cities in Kyrgyzstan

The expansion of urban areas due to population increase and economic expansion creates demand and depletes natural resources, thereby causing land use changes in the main cities. This study focuses on land cover datasets to characterize impervious surface (urban area) expansion in select cities from 1993 to 2017, using supervised classification maximum likelihood techniques and by quantifying impervious surfaces. The results indicate an increasing trend in the impervious surface area by 35% in Bishkek, 75% in Osh, and 15% in Jalal-Abad. The overall accuracy (OA) for the image classification of two different datasets for the three cities was between 82% and 93%, and the kappa coefficients (KCs) were approximately 77% and 91%. The Landsat images with other supplementary data showed positive urban growth in all of the cities. The GDP, industrial growth, and urban population growth were driving factors of impervious surface sprawl in these cities from 1993 to 2017.Landscape Expansion Index (LEI) results also provided good evidence for the change of impervious surfaces during the study period. The results emphasize the idea of applying future planning and sustainable urban development procedures for sustainable use of natural resources and their management, which will increase life quality in urban areas and environments.

Spatiotemporal changes in vegetation coverage and its causes in China since the Chinese economic reform

With the rapid development of the economy over 40 years since the initiation of Chinese economic reform, terrestrial ecosystems in China have undergone large-scale changes. In this study, we investigated vegetation dynamics in China and their relationships with climatic factors and anthropogenic drivers over 15 progressive periods of 18-32 years starting in 1982. This was accomplished by using the third-generation global satellite Advanced Very High Resolution Radiometer (AVHRR), Normalized Difference Vegetation Index (NDVI) dataset, night-time satellite data, and climate data. Across China, NDVI increased significantly during 1982-2013; especially significant increases were observed in all periods during the growing season and spring. At the pixel scale, 21-38% of the vegetated area in the 15 periods experienced a significant positive trend in vegetation growth. This increase was mostly located in central and southern China. A significant negative trend was observed in 1-8% of the vegetated area pixels, and this pattern was mainly seen in northwestern China, the Yangtze River Delta region, and the Pearl River Delta region. The contribution of spring NDVI to vegetation improvement increased, while the contribution of summer NDVI decreased. Vegetation activity in China was mainly regulated by thermal factors, especially pronounced in mountainous regions of northern China. However, the restrictive effect of moisture factors was very marked to vegetation growth in areas with less than 400 mm of precipitation. Urbanization in China has led to vegetation degradation in most urban centers and surrounding areas in central and eastern China. The increase of agricultural plantations, the Grain for Green Project, and a series ecological restoration projects in some areas have promoted vegetation coverage.

Spatiotemporal Patterns and Driving Forces of Urban Expansion in Coastal Areas: A Study on Urban Agglomeration in the Pearl River Delta, China

Since the beginning of the 21st century, the spatial pattern of urban expansion and the mechanism of urbanization in coastal areas have undergone significant changes. This study aims to reveal the spatiotemporal patterns of urban land expansion and analyze the dynamic driving forces of urban agglomeration in the Pearl River Delta of China from 2000 to 2015. The urban-land-expansion intensity index, expansion difference index, and fractal dimension were used to study how the urban land in this area was developed, and the geographical detector was applied to explore the relative importance, expansion intensity, and interactions of physical and socioeconomic factors. The results revealed that the urban-land-expansion intensity of the Pearl-River-Delta urban agglomerations exhibit a downward trend, while cities exhibited a trend of developing more coordinately from 2000 to 2015. Physical factors determined the direction and scale of urban development, and the urban land expansion in the Pearl-River-Delta urban agglomeration is mainly distributed in plain areas that have an elevation below 120 m and a slope less than 5°. Socioeconomic factors have a greater influence on the expansion of urban land, and their effects have changed over time. Population growth and economic development has played a significant role in the expansion of urban land before 2005. Subsequently, the factor of GDP and distance to the core cities of Guangzhou and Shenzhen controlled the expansion to the greatest extent. The impacts of various factors tended to become balanced during 2010–2015. The majority of the factors enhanced each other via their interactions, and the distance to the rivers always exhibited a greater enhancement when there was interaction with other factors. The spatial and temporal analysis of the urban expansion and the mechanism of the Pearl River Delta urban agglomeration could provide useful information for coastal urban planning. This study also offers new knowledge regarding the interactions between different drivers of urban land expansion.

Elevated Risk of Ecological Land and Underlying Factors Associated with Rapid Urbanization and Overprotected Agriculture in Northeast China

Ecological land with considerable ecological value can be regarded as an important indicator in guaranteeing ecosystem function and sustainable development. Generally, the urbanization process has been considered to be the primary factor affecting ecological land use. However, the influence of agricultural development, particularly in a typical farming area, has rarely been studied. In this paper, we present a method to assess the ecological risk of ecological land (ELER) in a black soil area in northeastern China. Furthermore, the underlying factors were detected using the geographically weighted regression model, which took into account conditions of natural elements, the urbanization process, and grain production conditions. The results indicate that ecological land experienced remarkable changes with an evident loss and decline from 1996–2015. The ELER progressively increased in the concentrated farming area and the western agro-pastoral ecotone, and the ecological land in the eastern forest area was always at a high risk level. According to the regression coefficients, the relationships between influence factors and ELER could be better explained by the variables of elevation, slope, proportion of rural residential area, and ratio of cultivated land area to residential area. To summarize, agricultural occupation and urban expansion were verified as the two main causes of ecological land loss, as well as elevated risks. In light of the current situation, measures such as policy adjustment and ecological restoration should be taken to avoid risk and optimize land use.

Quantifying Spatiotemporal Patterns and Major Explanatory Factors of Urban Expansion in Miami Metropolitan Area During 1992–2016

Urban expansion is one of the most dramatic forms of land transformation in the world and it is one of the greatest challenges in achieving sustainable development in the 21st century. Previous studies analyzed urbanization patterns in areas with rapid urban expansion while urban areas with low to moderate expansion have been overlooked, especially in developed countries. In this study, we examined the spatiotemporal dynamics of urban expansion patterns in South Florida, United States (US) over the last 25 years (1992–2016) using Remote Sensing and GIS techniques. The main goal of this paper was to investigate the degree and spatiotemporal patterns of urban expansion at different administrative level in the study area and how spatiotemporal variance in different explanatory factors influence urban expansion in this region. More specifically, this research quantifies the rates, types, intensity, and landscape metrics of urban expansion in Miami-Fort Lauderdale-Palm Beach, Florida Metropolitan Statistical Area (Miami MSA) which is the 7th largest MSA and 4th largest urbanized area in the US using remote sensing (satellite imageries) data from National Land Cover Datasets (NLCD) and Coastal Change Analysis Program (C-CAP) at 30 m spatial resolution. We further investigated the urban growth patterns at the county and city areas that are located within this MSA to portray the local ‘picture’ of urban growth in this region. Urban expansion in this region can be divided into two time periods: pre-2001 and post-2001 where the former experienced rapid urban expansion and the later had comparatively slow urban expansion. Results suggest that infilling was the dominant type of urban expansion followed by edge-expansion and outlying. Results from landscape metrics represent that newly developed urban lands became more aggregated and simplified in form as the time progressed in the study region. Also, new urban lands were generated away from the east coast and historic cities which eventually created new urban cores. We also used correlation analysis and multiple linear stepwise regression to address major explanatory factors of spatiotemporal change in urban expansion during the study period. Although the influence of factors on urban expansion varied temporally, Population and Distance to Coast were the strongest variables followed by Distance to Roads and Median Income that influence overall urban expansion in the study area.

Impacts by expansion of human settlements on nature reserves in China

Expansion of human settlements affects nature reserves in various ways. Planning ahead can help to divert or mitigate the impacts but a good understanding of these impacts is a prerequisite. In this study, we estimated the impacts caused by the expansion of human settlements on nature reserves in China by 2050 under different development and conservation scenarios. Our results show that 5016 km² of nature reserves may be encroached by the expansion of human settlements under the scenario of high growth and weak protection, a ten-fold increase compared to 2010. In addition, new settlements may fragment landscapes in 243 nature reserves and increase the level of fragmentation in 109 nature reserves. Furthermore, expansion of human settlements in surrounding areas may expose 164 nature reserves to threats of human activities and increase the threat levels to 540 nature reserves. The impacts will be lower if protection is stronger or economic growth is slower. Among all nature reserves, those administered at the county level will be affected the most. Nature reserves that protect forests and inland wetlands will be affected more than nature reserves protecting other objects. Nature reserves in East and South China will be influenced more than reserves in other regions. Findings from China show that the expansion of human settlements poses serious challenges to nature reserves in the future, especially in places where economic growth is fast and nature reserves are weakly protected. Proactive conservation strategies have to be developed and implemented forcefully to manage these impacts. Our findings contribute to a better understanding of the potential conflict between human settlements and nature reserves.

Optimising land use allocation to balance ecosystem services and economic benefits - A case study in Wuhan, China

The optimisation of land use allocation plays an important role in sustainable land use planning. It is crucial to realise the synergy between economic development and ecosystem conservation by optimising land use allocation. In this study, we developed a method to optimise land use allocation to balance ecosystem services and economic benefits based on the spatial difference of both ecosystem services value (ESV) and land use efficiency, based on the LAND System Cellular Automata model for Potential Effect (LANDSCAPE). In the optimisation model, spatial difference of ESV was represented by the parameter of resistance, while spatial difference of land use efficiency was expressed as the parameter of asynchronous rate of transition. Subsequently, land use allocation was optimised based on spatial difference of resistances and asynchronous rates. Taking Wuhan as the study area, the proposed optimisation model was used to conduct the optimisation of land use allocation during 2010-2020. Results showed that: economic benefits would increase by 444.77 million US$, while losses of ESV would decrease by 142.55 million US$ by optimisation of land use allocation. This indicated that the optimal allocation of land use based on spatial difference of ESV and land use efficiency can increase economic benefits at lower cost of ESV. In conclusion, it is feasible to allocate land resources to balance ecosystem services and economic benefits based on the differences of ESV and land use efficiency. This study highlights that taking the spatial difference of both ESV and land use efficiency into consideration is helpful for a sustainable land use planning.

Economic losses due to ozone impacts on human health, forest productivity and crop yield across China

China's economic growth has significantly increased emissions of tropospheric ozone (O₃) precursors, resulting in increased regional O₃ pollution. We analyzed data from >1400 monitoring stations and estimated the exposure of population and vegetation (crops and forests) to O₃ pollution across China in 2015. Based on WHO metrics for human health protection, the current O₃ level leads to +0.9% premature mortality (59,844 additional cases a year) with 96% of populated areas showing O₃-induced premature death. For vegetation, O₃ reduces annual forest tree biomass growth by 11-13% and yield of rice and wheat by 8% and 6%, respectively, relative to conditions below the respective AOT40 critical levels (CL). These CLs are exceeded over 98%, 75% and 83% of the areas of forests, rice and wheat, respectively. Using O₃ exposure-response functions, we evaluated the costs of O₃-induced losses in rice (7.5 billion US$), wheat (11.1 billion US$) and forest production (52.2 billion US$) and SOMO35-based morbidity for respiratory diseases (690.9 billion US$) and non-accidental mortality (7.5 billion US$), i.e. a total O₃-related cost representing 7% of the China Gross Domestic Product in 2015.

What Are the Driving Forces of Urban CO2 Emissions in China? A Refined Scale Analysis between National and Urban Agglomeration Levels

With the advancement of society and the economy, environmental problems have increasingly emerged, in particular, problems with urban CO2 emissions. Exploring the driving forces of urban CO2 emissions is necessary to gain a better understanding of the spatial patterns, processes, and mechanisms of environmental problems. Thus, the purpose of this study was to quantify the driving forces of urban CO2 emissions from 2000 to 2015 in China, including explicit consideration of a comparative analysis between national and urban agglomeration levels. Urban CO2 emissions with a 1-km spatial resolution were extracted for built-up areas based on the anthropogenic carbon dioxide (ODIAC) fossil fuel emission dataset. Six factors, namely precipitation, slope, temperature, population density, normalized difference vegetation index (NDVI), and gross domestic product (GDP), were selected to investigate the driving forces of urban CO2 emissions in China. Then, a probit model was applied to examine the effects of potential factors on urban CO2 emissions. The results revealed that the population, GDP, and NDVI were all positive driving forces, but that temperature and precipitation had negative effects on urban CO2 emissions at the national level. In the middle and south Liaoning urban agglomeration (MSL), the slope, population density, NDVI, and GDP were significant influencing factors. In the Pearl River Delta urban agglomeration (PRD), six factors had significant impacts on urban CO2 emissions, all of which were positive except for slope, which was a negative factor. Due to China's hierarchical administrative levels, the model results suggest that regardless of which level is adopted, the impacts of the driving factors on urban CO2 emissions are quite different at the national compared to the urban agglomeration level. The degrees of influence of most factors at the national level were lower than those of factors at the urban agglomeration level. Based on an analysis of the forces driving urban CO2 emissions, we propose that it is necessary that the environment play a guiding role while regions formulate policies which are suitable for emission reductions according to their distinct characteristics.

Detecting Spatiotemporal Features and Rationalities of Urban Expansions within the Guangdong–Hong Kong–Macau Greater Bay Area of China from 1987 to 2017 Using Time-Series Landsat Images and Socioeconomic Data

The Guangdong–Hong Kong–Macau Greater Bay Area (GBA) of China is one of the major bay areas in the world. However, the spatiotemporal characteristics and rationalities of urban expansions within this region over a relatively long period of time are not well-understood. This study explored the spatiotemporal evolution of 11 cities within the GBA in 1987–2017 by integrating remote sensing, landscape analysis, and geographic information system (GIS) techniques, and further evaluated the rationalities of their expansion using the urban area population elastic coefficient (UPEC) and the urban area gross domestic product (GDP) elastic coefficient (UGEC). The results showed the following: (1) Guangzhou, Shenzhen, Foshan, Dongguan, Zhongshan, and Zhuhai experienced unprecedented urbanization compared with the other cities, and from 1987 to 2017, their urban areas expanded by 10.12, 11.48, 14.21, 24.90, 37.07, and 30.15 times, respectively; (2) several expansion patterns were observed in the 11 cities, including a mononuclear polygon radiation pattern (Guangzhou and Foshan), a double-nucleated polygon pattern (Macau and Zhongshan), and a multi-nuclear urbanization pattern (Shenzhen, Hong Kong, Dongguan, Jiangmen, Huizhou, Zhaoqing, and Zhuhai); (3) with regard to the proportion of area, the edge-expansion and outlying growth types were the predominant types for all 11 cities, and the infilling growth type was the one of the important types during 2007–2017 for Shenzhen, Hong Kong, Dongguan, Zhongshan, and Foshan; (4) the expansion of most cities took on an urban-to-rural landscape gradient, especially for Guangzhou, Shenzhen, Foshan, Zhongshan, Dongguan, and Zhuhai; and (5) the rationalities of expansion in several time periods were rational for Guangzhou (1997–2007), Hong Kong (2007–2017), Foshan (1987–2007), Huizhou (1987–1997), and Dongguan (1997–2007), and the rationalities of expansion in the other cities and time periods were found to be irrational. These findings may help policy- and decision-makers to maintain the sustainable development of the Guangdong–Hong Kong–Macau Greater Bay Area.

Applications of Satellite Remote Sensing of Nighttime Light Observations: Advances, Challenges, and Perspectives

Nighttime light observations from remote sensing provide us with a timely and spatially explicit measure of human activities, and therefore enable a host of applications such as tracking urbanization and socioeconomic dynamics, evaluating armed conflicts and disasters, investigating fisheries, assessing greenhouse gas emissions and energy use, and analyzing light pollution and health effects. The new and improved sensors, algorithms, and products for nighttime lights, in association with other Earth observations and ancillary data (e.g., geo-located big data), together offer great potential for a deep understanding of human activities and related environmental consequences in a changing world. This paper reviews the advances of nighttime light sensors and products and examines the contributions of nighttime light remote sensing to perceiving the changing world from two aspects (i.e., human activities and environmental changes). Based on the historical review of the advances in nighttime light remote sensing, we summarize the challenges in current nighttime light remote sensing research and propose four strategic directions, including: Improving nighttime light data; developing a long time series of consistent nighttime light data; integrating nighttime light observations with other data and knowledge; and promoting multidisciplinary and interdisciplinary analyses of nighttime light observations.

Comparison of Changes in Urban Land Use/Cover and Efficiency of Megaregions in China from 1980 to 2015

Urban land use/cover and efficiency are important indicators of the degree of urbanization. However, research about comparing their changes at the megaregion level is relatively rare. In this study, we depicted the differences and inequalities of urban land and efficiency among megaregions in China using China’s Land Use/cover Dataset (CLUD) and China’s Urban Land Use/cover Dataset (CLUD-Urban). Furthermore, we analyzed regional inequality using the Theil index. The results indicated that the Guangdong-Hong Kong-Macao Great Bay Area had the highest proportion of urban land (8.03%), while the Chengdu-Chongqing Megaregion had the highest proportion of developed land (64.70%). The proportion of urban impervious surface area was highest in the Guangdong-Hong Kong-Macao Great Bay Area (75.16%) and lowest in the Chengdu-Chongqing Megaregion (67.19%). Furthermore, the highest urban expansion occurred in the Yangtze River Delta (260.52 km2/a), and the fastest period was 2000–2010 (298.19 km2/a). The decreasing Theil index values for the urban population and economic density were 0.305 and 1.748, respectively, in 1980–2015. This study depicted the development trajectory of different megaregions, and will expect to provide a valuable insight and new knowledge on reasonable urban growth modes and sustainable goals in urban planning and management.

Does China's Yangtze River Economic Belt policy impact on local ecosystem services?

The ecological protection of the Yangtze River Economic Belt (YREB) is one part of China's national strategy, and to identify the spatiotemporal variation of ecosystem service values (ESV) and examine the YREB policies performances can provide effective knowledge and supports for making ecological protection policies. In this paper, the ESV of YREB's 11 units were measured based on equivalent factor value method. Panal data and regression discontinuity model were used to discuss the impact of the ecological protection policies issued 2012 and 2014 on the ESVs. The results showed that: (1) From 2009 to 2016, the total ESVs of the YREB increased from 617.49 billion USD to 844.84 billion USD, showing a pattern of slow increase (2009-2012), substantial growth (2012-2014) and stability of high level (2014-2016). Forestland and water body were the key types of land to ecological protection. For the average of all measured years, the two lands accounted for 43.24% of total ecological land and provided 82.36% of total ESVs;(2) Generally, all the units were closely related to the ecological protection policy and were positively affected. In the first period (2009-2012), the ESVs of 11 units had three statuses: declined, kept steady and moderately increased. After strong policy implementation, all units rose sharply (2012-2014) and maintained a steady increase at a high level (2014-2016); (3) Ecological protection policies have a significant positive effect on the ESVs. The policy in 2012 suppressed the downward trend of ESVs increase and the policy in 2014 had a positive impact to increase ESVs. This study proved that possible to achieve a win-win situation of urban development and ecological environmental protection by implementing ecological protection policies.

Urban growth simulation guided by ecological constraints in Beijing city: Methods and implications for spatial planning

An ecologically constrained and scenario oriented urban growth simulation provides an effective means to address and mitigate ecological impacts resulting from urban expansion. However, current urban growth simulations usually set ecological indicators as explanatory variables in the model, while ignoring the trade-off relationship between the requirement for additional urban space and the prevention of ecological loss. In this study, ecological loss was set as a constraint parallel to the urban growth simulation indicator system. The Minimum losses of key ecosystem functions were set as constraints in order to realize optimized urban growth pattern. Taking Beijing's urban growth from 2000 to 2010 as a case, we proposed an optimized coupling model with ecological loss as a constraint in urban growth simulation. The results showed a 22.96% reduction in the total amount of ecological loss under the ecological constraint. According to the urban growth simulation, the "constant growth scenario" had the least ecological loss. Moreover, a combination of multiple ecosystem functions is required for describing the ecological constraint. We suggest that ecological constraint in an urban growth simulation model could be an effective policy tool to plan urban expansion and provide more accurate support for the formulation of spatial planning.

Automated Extraction of Built-Up Areas by Fusing VIIRS Nighttime Lights and Landsat-8 Data

As the world urbanizes and builds more infrastructure, the extraction of built-up areas using remote sensing is crucial for monitoring land cover changes and understanding urban environments. Previous studies have proposed a variety of methods for mapping regional and global built-up areas. However, most of these methods rely on manual selection of training samples and classification thresholds, leading to low extraction efficiency. Furthermore, thematic accuracy is limited by interference from other land cover types like bare land, which hinder accurate and timely extraction and monitoring of dynamic changes in built-up areas. This study proposes a new method to map built-up areas by combining VIIRS (Visible Infrared Imaging Radiometer Suite) nighttime lights (NTL) data and Landsat-8 multispectral imagery. First, an adaptive NTL threshold was established, vegetation and water masks were superimposed, and built-up training samples were automatically acquired. Second, the training samples were employed to perform supervised classification of Landsat-8 data before deriving the preliminary built-up areas. Third, VIIRS NTL data were used to obtain the built-up target areas, which were superimposed onto the built-up preliminary classification results to obtain the built-up area fine classification results. Four major metropolitan areas in Eurasia formed the study areas, and the high spatial resolution (20 m) built-up area product High Resolution Layer Imperviousness Degree (HRL IMD) 2015 served as the reference data. The results indicate that our method can accurately and automatically acquire built-up training samples and adaptive thresholds, allowing for accurate estimates of the spatial distribution of built-up areas. With an overall accuracy exceeding 94.7%, our method exceeded accuracy levels of the FROM-GLC and GUL built-up area products and the PII built-up index. The accuracy and efficiency of our proposed method have significant potential for global built-up area mapping and dynamic change monitoring.

Spatiotemporal evolution of urban agglomerations in four major bay areas of US, China and Japan from 1987 to 2017: Evidence from remote sensing images

As major urban agglomerations with strong urbanization, global bay areas are seldom detected and compared in detail regarding the spatiotemporal evolution of their urban expansion. In this work, a framework was applied for detecting and comparing the spatiotemporal evolution of urban agglomerations in four major bay areas: the San Francisco Bay Area and the New York Bay Area in the US, the Tokyo Bay Area in Japan, and the Guangdong-Hong Kong-Macau (GHM) Bay Area in China. Landsat images from 1987, 1997, 2007 and 2017 were employed to derive the four urban bay areas using the object-oriented support vector machine (O-SVM) classification method, and a multi-scale spatial analysis method was applied to detect the landscape characteristics and types of growth in the urban expansions. The results showed that: (1) the O-SVM classification method exhibited a high accuracy in urban area extraction, especially for classifying large-scale images; (2) the urban areas of the San Francisco Bay Area, the New York Bay Area, the Tokyo Bay Area and the GHM Bay Area from 1987 to 2017 expanded from 1686.82, 5315.93, 3765.09 and 605.71 km² to 2714.7, 8359.18, 5351.06 and 7568.19 km², respectively, with a corresponding annual average increase of 1.60%, 1.52%, 1.18% and 8.82%; (3) the GHM Bay Area had the largest expansion area and rate among the four bay areas; (4) both the San Francisco Bay Area and the New York Bay Area successively formed a multi-nuclei ribbon model, and the Tokyo Bay Area and the GHM Bay Area formed a multinuclear fan-shaped model and a triangle zonal expansion pattern, respectively; and (5) the spatial patterns of urban expansions in these bay areas shifted from outlying to edge-expansion and infilling, in which the Tokyo Bay Area and the New York Bay Area experienced the largest infilling growth, and the San Francisco Bay Area followed closely thereafter; all were ahead of the GHM Bay Area. These results will be helpful for the understanding and sustainable development of these bay areas.

Aligning Pixel Values of DMSP and VIIRS Nighttime Light Images to Evaluate Urban Dynamics

The brightness of pixels in nighttime light images (NTL) has been regarded as the proxy of the urban dynamics. However, the great difference between the pixel values of NTL from the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) and the Suomi National Polar-orbiting Partnership satellite’s Visible Infrared Imaging Radiometer Suite (Suomi NPP/VIIRS) poses obstacles to analyze economic and social development with NTL in a continuous temporal sequence. This research proposes a methodology to align the pixel values of both NTL by calibrating annual DMSP images between the years 1992–2013 with a robust regression algorithm with a quadratic polynomial regression model and simulating annual DMSP images with VIIRS images between years 2012 and 2018 with a model consisting of a power function and a Gaussian low pass filter. As a result, DMSP annual images between years 1992–2018 can be produced. Case study of Beijing and Yiwu are conducted and evaluated with local gross domestic product (GDP). Compared with the values of DMSP and VIIRS annual composites, the Pearson correlation coefficients of DMSP and simulated DMSP annual composites in 2012 and in 2013 increase significantly, while the root mean square error (RMSE) decrease evidently. In addition, the correlation of the sum of light of NTL and local GDP is enhanced with a simulation process. These results demonstrate the feasibility of the proposed method in narrowing the gap between DMSP and VIIRS NTL in pixel values.

Valuing urban green spaces in mitigating climate change: A city-wide estimate of aboveground carbon stored in urban green spaces of China's Capital

Urban green spaces provide manifold environmental benefits and promote human well-being. Unfortunately, these services are largely undervalued, and the potential of urban areas themselves to mitigate future climate change has received little attention. In this study, we quantified and mapped city-wide aboveground carbon storage of urban green spaces in China's capital, Beijing, using field survey data of diameter at breast height (DBH) and tree height from 326 field survey plots, combined with satellite-derived vegetation index at a fine resolution of 6 m. We estimated the total amount of carbon stored in the urban green spaces to be 956.3 Gg (1 Gg = 10⁹ g) in 2014. There existed great spatial heterogeneity in vegetation carbon density varying from 0 to 68.1 Mg C ha^-1 , with an average density of 7.8 Mg C ha^-1 . As expected, carbon density tended to decrease with urban development intensity (UDI). Likely being affected by vegetation cover proportion and configuration of green space patches, large differences were presented between the 95th and 5th quantile carbon density for each UDI bin, showing great potential for carbon sequestration. However, the interquartile range of carbon density narrowed drastically when UDI reached 60%, signifying a threshold for greatly reduced carbon sequestration potentials for higher UDI. These findings suggested that urban green spaces have great potential to make contribution to mitigating against future climate change if we plan and design urban green spaces following the trajectory of high carbon density, but we should be aware that such potential will be very limited when the urban development reaches certain intensity threshold.

Spatial Patterns and Driving Forces of Conflicts among the Three Land Management Red Lines in China: A Case Study of the Wuhan Urban Development Area

The delimitation of three land management red lines (LMRLs), which refers to urban growth boundaries (UGBs), ecological protection redlines (EPRs), and basic farmland protection zones (BFPZs), has been regarded as a control method for promoting sustainable urban development in China. However, in many Chinese cities, conflicts extensively exist among the three LMRLs in terms of spatial partitioning. This study clarifies the connotation of conflicts among the three LMRLs. Moreover, a red line conflict index (RLCI) is established to characterize the intensity of conflicts among the three LMRLs. The Wuhan Urban Development Area (WUDA) is used for a case study, in which the spatial patterns of the three types of conflicts among the three LMRLs (i.e., conflicts between EPRs and BFPZs, EPRs and UGBs, and UGBs and BFPZs) are analyzed through numerous spatial statistical analysis methods (including spatial autocorrelation, urban-rural gradient, and landscape pattern analyses). In addition, the driving forces of these conflicts are identified from the perspectives of natural physics, socioeconomic development, neighborhood, policy and planning using three binary logistic regression models. Results show that the conflicts between EPRs and BFPZs, EPRs and UGBs, and UGBs and BFPZs are mainly distributed on the edge of the WUDA, inside Wuhan’s third circulation line, and at the urban–rural transition zone, respectively. The patch of conflict between BFPZs and UGBs has the lowest aggregation degree, the highest fragmentation degree, and the most complex shape. Logistic regression results show that the combination and relative importance of driving factors vary in the three types of conflicts among the three LMRLs. In the conflict between EPRs and BFPZs, the distance to city centers is the most important influencing factor, followed by the proportion of ecological land and elevation. In the conflict between UGBs and EPRs, the proportion of construction land, the distance to city centers, and whether the land unit is within the scope of a restricted development zone are the three most important factors. The proportion of construction land, the distances to the Yangtze and Han Rivers, and the proportion of cultivated land significantly influence the conflict between UGBs and BFPZs. This study aids in our understanding of the causes and mechanisms of conflicts among the three LMRLs, and provides important information for the “integration of multi-planning” and land management in Wuhan and similar cities.

Exploring Urban Expansion and Socioeconomic Vitality Using NPP-VIIRS Data in Xia-Zhang-Quan, China

Studying the spatiotemporal evolution of urban expansion in the Xia-Zhang-Quan metropolitan area (XZQ) is of crucial importance, to effectively guide coordinated development and industrial adjustment during urbanization. Based on National Polar Partnership-Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) data this study used an analytical method of irregular spatial grids to explore and evaluate the dynamics of urban spatial expansion and urban socioeconomic vitality in XZQ between 2013 and 2017. The results show that the gulf-type urban development strategy of Xiamen has played a key role in the integration and development of XZQ. The urban area increased by 20–30% and increased intensity of socioeconomic activities was demonstrated by observed increases in the total brightness of urban nighttime light. Due to its unique advantages in the agricultural industries, Zhangzhou made significant economic progress during 2013–2017. At the same time, driven by spatial processes in Xiamen, areas such as the Zhangzhou Port Area and Longhai also achieved significant progress. This is also the case in Quanzhou and thus, collectively there is evidence of multi-polar growth. Jinjiang and Shishi effectively utilized coastal port economy development advantages to play a key role in the integration and development of XZQ. There were both commonalities and differences in terms of the characteristics of spatial expansion in different cities of XZQ. In summary, this study provides evidence to support further promotion of coordinated development in XZQ, and with appropriate caveats these findings could also be transferred to other urban agglomerations.

Mapping and evaluating cultivated land fallow in Southwest China using multisource data

Accurately and effectively mapping and evaluating cultivated land fallow has already become an important issue that has received much attention in China. However, systematically analysing regional cultivated land fallow remains inadequate because current studies have mainly focused on quantifying cultivated land fallow using statistical data based on administrative units or a single aspect of cultivated land fallow using high or medium spatial resolution images at the local or regional scales. Against the existing shortcomings, this study first developed an integrated index of cultivated land fallow (ILF) for mapping and evaluating cultivated land fallow in Southwest China using multisource spatial data. The performance of the ILF was validated by comparing its results with Google Earth images and ecological carrying capacity of cultivated land (TEC). And the spatial distribution of cultivated land fallow in Southwest China was evaluated at the regional, provincial and metropolitan scales. The results revealed that the ILF provided a reliable evaluation of cultivated land fallow in Southwest China. Compared to the Google earth images, the pixel with the high ILF value was the cultivated land that was found to prioritize fallow. There was also a significant correlation between ILF and TEC at the prefectural level in Sichuan, with an R² value >0.65. In Southwest China, the cultivated land related to highly appropriate fallow (HAF) accounted for 5.73% of the total cultivated land in 2010. The cultivated land related to inappropriate fallow (IF) accounted for 53.26% and 37.36% in Sichuan and Chongqing but only comprised 22.90% and 19.72% in Yunnan and Guizhou, respectively. Special attention needs to be paid to Guiyang and Kunming, where the HAF made up 25.38% and 17.48% of their total cultivated land, respectively. Human activities have been found to already become the most important impact factors for cultivated land fallow in Southwest China. This study is especially valuable for providing a scientific basis for policy-making on viable cultivated land fallow policy in Southwest China.

Tele-connecting China's future urban growth to impacts on ecosystem services under the shared socioeconomic pathways

Land change, especially urban land expansion, is increasingly triggered by remote demands for goods and services rather than by purely local drivers, exerting pressure on ecosystem services beyond local boundaries. This effect has been termed as 'tele-connections'. China has become the world's second largest economy. Understanding the tele-connections between China's future urban growth and its impacts on ecosystem services is essential to reconcile the conflict between socioeconomic developments and ecological protection. To this end, we propose to integrate an urban growth simulation model with the multi-region input-output (MRIO) model, thereby illustrating how urban land consumption in one region can cause ecosystem services' degradation in another. We explore the decline in ecosystem services due to urban land tele-connections under five shared socioeconomic pathway (SSP) scenarios. The results yield the direct loss of ecosystem services by 1.14-5.42% in food production, 0.06-0.44% in carbon sequestration, 0.09-0.59% in soil retention, 0.05-0.29% in sandstorm prevention, 0.12-0.80% in water retention and 0.19-1.04% in habitat provision. Uneven ecological consequences caused by domestic urban land displacement are witnessed not only in China's peripheral regions but also in developed regions. Shanghai, as the largest city in China, is expected to exert great impacts in terms of the quantity of ecosystem services decline and its spatial extent as well. Overall, the presented scenario simulations can support the establishment of effective compensation strategies toward balancing the responsibility and rights of stakeholders associated with ecological services protection.

Climate change will constrain the rapid urban expansion in drylands: A scenario analysis with the zoned Land Use Scenario Dynamics-urban model

Evaluation of climate change impacts (CCIs) on urban expansion is important to improving the urban sustainability in drylands. Taking the agro-pastoral transitional zone of northern China (APTZNC) as an example, this study evaluates potential CCIs on urban expansion in 2015-2050. First, we set up six climate change scenarios (CCSs) based on the simulated results of global climate model and regional climate model under different representative concentration pathways. Then, we simulate regional urban expansion under the different CCSs using the zoned Land Use Scenario Dynamics-urban (LUSD-urban) model. We find that climate change will be a key factor that affects urban expansion in this region. The urban land affected by climate change in the entire region will increase from 20.24-26.48 km² (2020) to 119.71-339.26 km² (2050), an increase of 4.91-11.81 times. The CCIs on urban expansion will be the most significant in the mid-western region. In 2050, the urban land potentially affected by climate change will be 98.70-213.88 km², which is 42.26%-134.12% of the urban land in the entire region. To improve urban sustainability in the APTZNC, effective measures must be adopted to mitigate and adapt to CCIs on urban expansion.

A Framework for Evaluating Land Use and Land Cover Classification Using Convolutional Neural Networks

Analyzing land use and land cover (LULC) using remote sensing (RS) imagery is essential for many environmental and social applications. The increase in availability of RS data has led to the development of new techniques for digital pattern classification. Very recently, deep learning (DL) models have emerged as a powerful solution to approach many machine learning (ML) problems. In particular, convolutional neural networks (CNNs) are currently the state of the art for many image classification tasks. While there exist several promising proposals on the application of CNNs to LULC classification, the validation framework proposed for the comparison of different methods could be improved with the use of a standard validation procedure for ML based on cross-validation and its subsequent statistical analysis. In this paper, we propose a general CNN, with a fixed architecture and parametrization, to achieve high accuracy on LULC classification over RS data from different sources such as radar and hyperspectral. We also present a methodology to perform a rigorous experimental comparison between our proposed DL method and other ML algorithms such as support vector machines, random forests, and k-nearest-neighbors. The analysis carried out demonstrates that the CNN outperforms the rest of techniques, achieving a high level of performance for all the datasets studied, regardless of their different characteristics.

Urban Land Intensive Use Evaluation Study Based on Nighttime Light—A Case Study of the Yangtze River Economic Belt

Urban land intensive use meets the requirements for the sustainable development of urban land and is an important part of urban sustainable development. The Yangtze River Economic Belt (YREB) spans the three major regions of China, which are the most active areas of China’s economy. The contradiction between humans and land is becoming more acute. There are also regional differences in land use patterns affecting the coordinated development of the YREB and the construction of an ecological civilization. Therefore, the scientific evaluation of urban land intensive use is a key area in the current research field of urban sustainable development. In this study, the YREB is chosen as the research object, and urban land intensive use is studied using nighttime light data and statistical data on the urban built-up area. An evaluation model based on urban nighttime light intensity and land urbanization is constructed with an allometric growth model. Considering that the impact of land urbanization on urban nighttime light has a possible lag effect, an evaluation model of land intensive use that considers the lag effect between urban nighttime light and the land urbanization level is proposed. Using urban agglomerations and some typical cities in the study area as research samples, the characteristics of urban nighttime light and land urbanization are analyzed to reveal the spatial and temporal characteristics of land development in the YREB. The results show that nighttime light remote-sensing data can better reflect the level of urban land use, the allometric growth model can better fit the intensity of urban light and the land urbanization level, and the allometric growth characteristics can reflect the land use characteristics of different cities and urban agglomerations. In regional experiments with typical cities and with urban agglomerations, compared to the original allometric growth model, the goodness of fit of the allometric growth model with the lag effect improves, on average, by 3.2% and 2%, respectively, with the highest increases being by 9.9% and 4.9%, respectively. The level of intensive land use in the YREB gradually decreases from east to west, and there are great differences among different cities in the provinces and urban agglomerations. The lower reaches of the Yangtze River have high land intensive use on the whole. In the middle reaches, multicenter cities have a greater efficiency of land use than the surrounding cities. In the upper reaches, only Chengdu and Chongqing have clear advantages in urban land intensive use. The results of this study can be helpful in providing an important reference for the sustainable development of land in the YREB and can provide a basis for future urban land optimization and sustainable development. Realizing the coordination and linkage between key cities and major cities is the key to enhancing the overall sustainable development ability of the core cities in the YREB.

Impacts of Strict Cropland Protection on Water Yield: A Case Study of Wuhan, China

Land use and land cover change is a critical factor of ecosystem services, while water yield plays a vital role in sustainable development. The impact of urban expansion on water yield has long been discussed, but water yield change resulting from cropland protection is seldom concerned. Therefore, this paper aims to investigate the impacts of cropland protection on water yield by comparing the water yield in two cropland protection scenarios (i.e., Strict Cropland Protection scenario and No Cropland Protection scenario). Specifically, the LAND System Cellular Automata for Potential Effects (LANDSCAPE) model was employed to simulate land use maps in the two scenarios, while Water Yield module in the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model was used to calculate water yield. The results show water yield would increase by 8.7 × 107 m3 in the No Cropland Protection scenario and 9.4 × 107 m3 in the Strict Cropland Protection scenario. We conclude that implementation of strict cropland protection in rapid urbanizing areas may cause more water yield, which is also a prerequisite of potential urban flooding risk. This study throws that it is not wise to implement strict cropland protection policy in an area of rapid urbanization.

Linking ecosystem services and circuit theory to identify ecological security patterns

The rapid process of urbanization, accompanied by the sharp increase of urban population and expansion of artificial surface, has resulted in the loss of natural ecosystems and the degradation of ecosystem services. Identifying and protecting key places that have high importance for ecological sustainability are great challenges. Ecological security patterns are such an integrated approach to protecting regional ecological sustainability. In this study, taking Yunnan Province, China as a case study area, ecological sources were identified through ecosystem services, and circuit theory was used to model ecosystem processes in heterogeneous landscapes via calculating the 'resistance' or 'current', and thus to identify ecological corridors and key ecological nodes. The results showed that, ecological security patterns included 66 ecological sources, 186 ecological corridors, 24 pinch-points and 10 barriers. In details, the ecological sources were mainly distributed in the southwest and northwest of Yunnan Province, with the ecological corridors locating along the high mountains, and both ecological sources and corridors were mostly covered with forest land. Pinch-points covered by forest land and cultivated land, were distributed in the middle of Yunnan Province along the rivers. Approximately 75.9% nature reserves were located in the identified ecological sources, and the remainings were mainly distributed in eastern Yunnan Province with small area, showing the effectiveness in identifying ecological security patterns. Among 81 projects of low-slope hill development carried out in Yunnan Province, 46.9% showed potential human stress on regional ecological security. Based on ecosystem services and circuit theory, this study provides a new approach to identifying the spatial range of ecological corridors and the specific location of key nodes for effective ecological conservation and restoration.

Asymmetric response of different functional insect groups to low-grazing pressure in Eurasian steppe in Ningxia

In recent years, the continued loss and fragmentation of steppe has caused decreased ecosystem functions and species losses in insect diversity. In the 2000s, the Chinese government developed a series of national projects, such as the construction of enclosures, to conserve natural ecosystems, including steppe. However, the effects of these enclosures on steppe arthropod community are largely unknown. In the present study, we selected enclosed and low-grazing regions at eight National Grassland Fixed Monitoring Stations to examine the compositional differences in four insect functional groups and their associated ecological functions. The results showed that diversity significantly differed between the enclosed and low-grazing regions, with the number of insect families being significantly higher in enclosed regions than in regions with low-grazing pressure. The responses of the insect community to steppe management also varied among the four groups (herbivores, predators, parasitoids, and pollinators). The abundances of herbivores, predators, and parasitoids were higher in enclosed regions than in low-grazing regions, while there was no significant difference in pollinators. Additionally, there were no significant differences in the predator/prey ratio between enclosed regions and low-grazing regions in any of the steppe types. The parasitic wasp/prey ratio was higher in enclosed regions than in low-grazing regions in meadow steppe and typical steppe, while there were no significant differences between the enclosed and low-grazing regions in desert steppe and steppe desert. Herbivores were observed to benefit much more from enclosures than predators, parasitoids, and pollinators. Therefore, we recommend low-grazing should be considered in steppe conservation, which could conserve biodiversity and achieve biocontrol functions of arthropod community.

Modeling the Census Tract Level Housing Vacancy Rate with the Jilin1-03 Satellite and Other Geospatial Data

The vacant house is an essential phenomenon of urban decay and population loss. Exploration of the correlations between housing vacancy and some socio-environmental factors is conducive to understanding the mechanism of urban shrinking and revitalization. In recent years, rapidly developing night-time remote sensing, which has the ability to detect artificial lights, has been widely applied in applications associated with human activities. Current night-time remote sensing studies on housing vacancy rates are limited by the coarse spatial resolution of data. The launch of the Jilin1-03 satellite, which carried a high spatial resolution (HSR) night-time imaging camera, provides a new supportive data source. In this paper, we examined this new high spatial resolution night-time light dataset in housing vacancy rate estimation. Specifically, a stepwise multivariable linear regression model was engaged to estimate the housing vacancy rate at a very fine scale, the census tract level. Three types of variables derived from geospatial data and night-time image represent the physical environment, landuse (LU) structure, and human activities, respectively. The linear regression models were constructed and analyzed. The analysis results show that (1) the HVRs estimating model using the Jilin1-03 satellite and other ancillary geospatial data fits well with the Census statistical data (adjusted R2 = 0.656, predicted R2 = 0.603, RMSE = 0.046) and thus is a valid estimation model; (2) the Jilin1-03 satellite night-time data contributed a 28% (from 0.510 to 0.656) fitting accuracy increase and a 68% (from 0.359 to 0.603) predicting accuracy increase in the estimate model of the housing vacancy rate. Reflecting socio-economic conditions, the luminous intensity of commercial areas derived from the Jilin1-03 satellite is the most influential variable to housing vacancy. Land use structure indirectly and partially demonstrated that the social environment factors in the community have strong correlations with residential vacancy. Moreover, the physical environment factor, which depicts vegetation conditions in the residential areas, is also a significant indicator of housing vacancy. In conclusion, the emergence of HSR night light data opens a new door to future microscopic scale study within cities.

Urbanization Impacts on Vegetation Phenology in China

Urbanization can affect the ecological processes, local climate and human health in urban areas by changing the vegetation phenology. In the past 20 years, China has experienced rapid urbanization. Thus, it is imperative to understand the impact of urbanization on vegetation phenology in China. In this study, we quantitatively analyzed the impact of urbanization on vegetation phenology at the national and climate zone scales using remotely sensed data. We found that the start of the growing season (SOS) was advanced by approximately 2.4 days (P < 0.01), and the end of the growing season (EOS) was delayed by approximately 0.7 days (P < 0.01) in the urban areas compared to the rural areas. As a result, the growing season length (GSL) was extended by approximately 3.1 days (P < 0.01). The difference in the SOS and GSL between the urban and rural areas increased from 2001 to 2014, with an annual rate of 0.2 days (R2 = 0.39, P < 0.05) and 0.2 days (R2 = 0.31, P < 0.05), respectively. We also found that the impact of urbanization on vegetation phenology varied among different vegetation types at the national and climate zone levels (P < 0.05). The SOS was negatively correlated with land surface temperature (LST), with a correlation coefficient of −0.24 (P < 0.01), and EOS and GSL were positively correlated with LST, with correlation coefficients of 0.56 and 0.44 (P < 0.01), respectively. The improved understanding of the impact of urbanization on vegetation phenology from this study will be of great help for policy-makers in terms of developing relevant strategies to mitigate the negative environmental effects of urbanization in China.

Urbanization and Spillover Effect for Three Megaregions in China: Evidence from DMSP/OLS Nighttime Lights

Urbanization drives human social development and natural environmental changes and shows complex implications for sustainability and challenges of future development, particularly in emerging countries. While extensive studies focus on extracting urban areas more precisely, less attention has been devoted to understand megaregion evolution and its related socioeconomic processes, not by socioeconomic statistics, but by comparing remote sensing based spatiotemporal evolution and the related spillover effect. Three main megaregions (with large area, high population and total gross domestic product) in China are selected for the analysis of development changes in an urbanization (magnitude, development)-diagram, of growth pattern changes based on Gravity Center and weighted Standard Deviation Ellipses and of the megaregions’ spillover effect. Employing the spatiotemporally continuous lighted areas (DN ≥ 12) from the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) nighttime signal (1992–2013) to the Beijing-Tianjin-Hebei (BTH), the Yangtze River Delta (YRD), and the Pearl River Delta (PRD) leads to the following results: (i) Developments in the (magnitude, development)-diagram indicate 25.97%, 45.95%, and 39.10% of the first (high urbanization, fast development) class of the BTH, YRD, and PRD megaregions are rapidly developing into highly urbanized regions. The first class may slow down in the future like the second (high urbanization, slow development) class acting from 1992 to 2013, and the third (moderate urbanization, fast development) class shows potential to become the first class in the future. (ii) The original core function zones of YRD and PRD have highly developed till 1992 and expanding out with fast development from 1992 to 2013. Contrarily, BTH indicates more fast development toward the original core function zones while spatial expansion. (iii) The gravity distance evolution of the three megaregions shows a tendency towards the geometric distance 2013. However, YRD and PRD (BTH) indicate a light intensity expansion (concentration). This may relate to a positive spillover effect of YRD and PRD upon their neighbor cities, with the strongest signal in the early 21st Century and thereafter adjusting and followed by another positive spillover.

Differences in Urban Built-Up Land Expansion in Zhengzhou and Changsha, China: An Approach Based on Different Geographical Features

The disorderly expansion of urban built-up land is a global issue. It is of great significance to guide urban land use scientifically through the analysis of geographical features to identify the mechanisms that underlie differences in urban built-up land expansion. We selected Changsha and Zhengzhou in China, whose built-up areas during the initial period of study had different natural geographical features, but similar human geographical features, and systematically explored the development and evolution characteristics of the natural and human geographical features from 1990 to 2010 using a landscape metrics analysis and an urban built-up land intensive use analysis. We found that (1) although human beings have a strong ability to transform nature, they have to rely on the natural endowment of the land to develop the cities and, thus, have formed different landscape patterns and levels of urban built-up land intensive use; (2) in places where the natural geographical features are more restrictive, land-use policy-makers are more cautious in their decision-making, which more closely links the land-use policies and human geographical features, thereby simultaneously increasing the degree of intensive built-up land use and reducing the number of problems that arise from urban built-up land expansion. This research can provide a reference for the development of policies for urban built-up land use in Changsha and Zhengzhou. It also can provide ideas for how to implement different built-up land management policies for other cities with different natural and human geographical features.

Urban Expansion and Farmland Loss in Beijing during 1980–2015

The analysis of urban land expansion and farmland loss is essential to adequately understand the land use change in a rapidly urbanizing China. We found that both urban expansion and farmland loss in Beijing experienced high- and low-speed stages and their spatial patterns were consistent during the past 35 years as most of the newly expanded urban land was converted from farmland. The area of farmland loss by urban expansion in Beijing is 12.6 km2/year, 39.86 km2/year, 23.38 km2/year, and 41.11 km2/year during the period of 1980–1990, 1990–2000, 2000–2010, and 2010–2015, respectively. The urban expansion in Beijing continuously preferred to consume “above average” quality farmland during 1980–2015. Meanwhile, although the urban expansion in Beijing was highly dependent on occupying farmland, the dependence of urban expansion on farmland consumption has declined over time. However, the contribution of urban expansion on farmland loss increased during 1980–2010 and decreased afterward. In order to protect the farmland from urban expansion, we call for more effort to improve the urban land use efficiency with rigid controls over areas of urban expansion.

Mapping Urban Extent Using Luojia 1-01 Nighttime Light Imagery

Luojia 1-01 satellite, launched on 2 June 2018, provides a new data source of nighttime light at 130 m resolution and shows potential for mapping urban extent. In this paper, using Luojia 1-01 and VIIRS nighttime light imagery, we compared several methods for extracting urban areas, including Human Settlement Index (HSI), Simple Thresholding Segmentation (STS) and SVM supervised classification. According to the accuracy assessment, the HSI method using LJ1-01 data had the best performance in urban extent extraction, which presented the largest Kappa Coefficient value, 0.834, among all the results. For the urban areas extracted by VIIRS based HSI method, the largest Kappa Coefficient value was 0.772. In contrast, the largest Kappa Coefficient values obtained by STS method were 0.79 and 0.7512 respectively when using LJ1-01 and VIIRS data, while for SVM method the values were 0.7829 and 0.7486 when using Landsat-LJ and Landsat-VIIRS composite data respectively. The experimented results demonstrated that the utilization of nighttime light imagery can largely improve the accuracy of urban extent extraction and LJ1-01 data, with a higher resolution and more abundant spatial information, can lead to better identification results than its predecessors.

Spatial Pattern Evolution and Optimization of Urban System in the Yangtze River Economic Belt, China, Based on DMSP-OLS Night Light Data

It is of great significance to research the spatial pattern of the urban system of the Yangtze River economic belt to analyze the characteristics and laws of the spatial structure of the Yangtze River economic belt and to promote the optimal development of the urban system of the Yangtze River economic zone. In this paper, the time data of the Yangtze River economic zone are corrected using Landsat satellite data and the clustering analysis method. The threshold of the urban built area is obtained by comparing the auxiliary data with other auxiliary data. Based on this threshold, a total of eight typical landscape pattern indicators—including the total area of the landscape, the total patch number, and the aggregation index—are used, and then FRAG-STATS 4.2 software is used to analyze the spatial pattern of urban development in the Yangtze River economic zone from 1992 to 2013. The results show the following: (1) During the period from 1992 to 2013, the urbanization of the Yangtze River economic zone expanded rapidly; the area of urban built-up area increased by a factor of 9.68, the number of patches increased by a factor of 2.39, and the patch density increased greatly, indicating that the Yangtze River economic zone, with an increasing number of towns and urban areas, continues to expand. (2) The complexity of the landscape patch shape gradually increased, the small and medium-sized cities continued to grow, more small towns emerged, and the total length of the border and the average density had average annual growth rates of 21.56% and 21.58%; the degree of aggregation and the mutual influence are increasing. (3) The maximum plaque index and the aggregation index show an overall declining trend. However, there are some fluctuations and disorder in the process of evolution, such as the total area of the landscape, the total patch number and the total patch density, which reflects that the Yangtze River economic zone is in the process of urbanization and has irregular and disordered characteristics.