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Urban impervious surface area (UISA) and urban green space (UGS) are two core components of cities for characterizing urban environments. Although several global or national urban land use/cover products such as Globeland30 and FROM-GLC are available, they cannot effectively delineate the complex intra-urban land cover components. Here we proposed a new approach to map fractional UISA and UGS in China using Google Earth Engine (GEE) based on multiple data sources. The first step is to extract the vector boundaries of urban areas from China's Land Use/cover Dataset (CLUD). The UISA was retrieved using the logistic regression from the Landsat-derived annual maximum Normalized Difference Vegetation Index (NDVI). The UGS was developed through linear calibration between reference UGS from high spatial resolution image and the normalized NDVI. Thus, the China's UISA and UGS fraction datasets (CLUD-Urban) at 30-meter resolution are generated from 2000 to 2018. The overall accuracy of national urban areas is over 92 %. The root mean square errors of UISA and UGS fractions are 0.10 and 0.14, respectively. The datasets indicate that total urban area of China was 7.10 x 104 km² in 2018, with average fractions of 70.70 % for UISA and 26.54 % for UGS. The UISA and UGS increased with unprecedented annual rates of 1,492.63 km²/yr and 400.43 km²/yr during 2000-2018. CLUD-Urban can enhance our understanding of urbanization impacts on ecological and urban dwellers' environments, and can be used in such applications as urban planning, urban environmental studies and practices. The datasets can be downloaded from https://doi.org/10.5281/zenodo.3778424 (Kuang et al., 2020). [ABSTRACT FROM AUTHOR]

Accurate urban land-cover datasets are essential for mapping urban environments. However, a series of national urban land-cover data covering more than 15 years that characterizes urban environments is relatively rare. Here we propose a hierarchical principle on remotely sensed urban land-use/cover classification for mapping intra-urban structure/component dynamics. China's Land Use/cover Dataset (CLUD) is updated, delineating the imperviousness, green surface, waterbody and bare land conditions in cities. A new data subset called CLUD-Urban is created from 2000 to 2015 at five-year intervals with a medium spatial resolution (30 m). The first step is a prerequisite to extract the vector boundaries covered with urban areas from CLUD. A new method is then proposed using logistic regression between urban impervious surface area (ISA) and the annual maximum Normalized Difference Vegetation Index (NDVI) value retrieved from Landsat images based on a big-data platform with Google Earth Engine. National ISA and urban green space (UGS) fraction datasets for China are generated at 30-meter resolution with five-year intervals from 2000 to 2015. The overall classification accuracy of national urban areas is 92 %. The root mean square error values of ISA and UGS fractions are 0.10 and 0.14, respectively. The datasets indicate that the total urban area of China was 6.28 × 104 km² in 2015, with average fractions of 70.70 % and 26.54 % for ISA and UGS, respectively. The ISA and UGS increased between 2000 and 2015 with unprecedented annual rates of 1,311.13 km²/yr and 405.30 km²/yr, respectively. CLUD-Urban can be used to enhance our understanding of urbanization impacts on ecological and regional climatic conditions and urban dwellers' environments. CLUD-Urban can be applied in future researches on urban environmental research and practices in the future. The datasets can be downloaded from https://doi.org/10.5281/zenodo.2644932. [ABSTRACT FROM AUTHOR]

Impervious surface area (ISA) is an important parameter for many studies such as urban climate, urban environmental change, and air pollution; however, mapping ISA at the regional or global scale is still challenging due to the complexity of impervious surface features. The Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) data have been used for ISA mapping, but high uncertainty existed due to mixed-pixel and data-saturation problems. This paper presents a new index called normalized impervious surface index (NISI), which is an integration of DMSP-OLS and Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data, in order to reduce these problems. Meanwhile, this newly developed index is compared with previously used indices--Human Settlement Index (HSI) and Vegetation Adjusted Nighttime light Urban Index (VANUI)--in ISA mapping performance. We selected China as an example to map fractional ISA distribution through a support vector regression approach based on the relationship between the index and Landsat-derived ISA data. The results indicate that the proposed NISI provided better ISA estimation accuracy than HSI and VANUI, especially when the fractional ISA in a pixel is relatively large (i.e., >0.6) or very small (i.e., <0.2). This approach can be used to rapidly update ISA datasets at regional and global scales. [ABSTRACT FROM AUTHOR]

Analysis of urban distribution and its expansion using remote sensing data has received increasing attention in the past three decades, but little research has examined spatial patterns of urban distribution and expansion with buffer zones in different directions. This research selected Hangzhou metropolis as a case study to analyze spatial patterns and dynamic changes based on time-series urban impervious surface area (ISA) datasets. ISA was developed from Landsat imagery between 1991 and 2014 using a hybrid approach consisting of linear spectral mixture analysis, decision tree classifiers, and post-processing. The spatial patterns of ISA distribution and its dynamic changes in eight directions--east, southeast, south, southwest, west, northwest, north, and northeast--at the temporal scale were analyzed with a buffer zone-based approach. This research indicated that ISA can be extracted from Landsat imagery with both producer and user accuracies of over 90%. ISA in Hangzhou metropolis increased from 146 km² in 1991 to 868 km² in 2014. Annual ISA growth rates were between 15.6 km² and 48.8 km² with the lowest growth rate in 1994-2000 and the highest growth rate in 2005-2010. Urban ISA increase before 2000 was mainly due to infilling within the urban landscape, and, after 2005, due to urban expansion in the urban-rural interfaces. Urban expansion in this study area has different characteristics in various directions that are influenced by topographic factors and urban development policies. [ABSTRACT FROM AUTHOR]

Rapid urbanization has occurred in northwestern China, threatening the sustainability of its fragile dryland ecosystems. A lack of precise urban land-cover information has limited our understanding on the urbanization in the dryland. Here, we examined urban land-cover changes from 2000 to 2014 in 21 major cities that comprise over 50% of the developed land in arid China, using Landsat Enhanced Thematic Mapper Plus and Operational Land Imager data, and a hybrid classification method. The 15-m resolution urban land-cover products (including impervious surfaces, vegetation, bare soil, and water bodies) had an overall accuracy of 90.37%. Based on these new land use products, we found the urbanization in arid China was characterized by the dramatic expansion of impervious surface (+13.23%) and reduction of bare soil (-13.41%), while the proportions of vegetation (+0.27%) and water (-0.10%) remained stable. The observed dynamic equilibrium of vegetated ratio implies an increasing harmonization of urbanization and greening, which was particularly important for the sustainability of fragile urban ecosystems in arid regions. From an economic perspective, gross domestic product and population were significantly correlated with impervious surfaces, and oasis cities displayed a stronger ability to attract new residents than desert cities. [ABSTRACT FROM AUTHOR]

Forests play an important role in maintaining ecosystem services, especially in ecologically fragile areas such as the Loess Plateau (LP) in China. However, there is still great uncertainty in the spatial extent and distribution of forests in such a fragmented region. In order to examine the advantages and disadvantages of existing forest mapping products, we conducted a thorough accuracy assessment on the eight recent, medium resolution (30-50 m) products by using the LP in 2010 as the region of interest. These mapping products include Landsat and/or PALSAR images, including the forest products from GlobeLand30, FROM-GLC, Hansen, ChinaCover, NLCD-China, GLCF VCF, OU-FDL, and JAXA. The same validation data were used to assess and rank the accuracy of each product. Additionally the spatial consistency of the different forest products and their dependence on the terrain were analyzed. The results showed that the overall accuracies of the eight forest products on the LP in 2010 were between 0.93 u 0.003 and 0.97 ± 0.002 with a 95% confidence interval and GlobeLand30 presented the highest overall accuracy (0.97 ± 0.002). Among them, the PALSAR-based products (OU-FDL and JAXA) indicated relatively high accuracies, while the six Landsat-based products showed a large diversity in the accuracy. According to the eight products the total estimated forest area of the LP varied from 7.627 ± 0.077 to 10.196 ± 0.1 million ha with a 95% confidence interval. We also found that the consistency in the spatial distribution of forests between these maps: (1) increased substantially with increasing elevation until 2000m, but then decreased at higher elevations and (2) showed mild variation along increasing slope, but had a slight rate of increase. Our findings implied that future forest mapping studies should consider topographical attributes such as elevation and slope in their final products. Our results are fundamental in guiding future applications of these existing forest maps. [ABSTRACT FROM AUTHOR]

Lack of research into the complexity in urban land conversion, and paucity of observational data of soil organic carbon (SOC) beneath impervious surface area (ISA) limit our understanding of the urbanization effects on carbon (C) pools in dryland cities. Employing Landsat TM images acquired in 1990 and 2010, a hybrid classification method consisting of Linear Spectral Mixture Analysis and decision tree classification was applied to retrieve the land cover (water, ISA, greenspace, cropland, and remnant desert) of the largest dryland city in China--Urumqi. Based on vegetation carbon (VEGC) and SOC density data determined through field observations and literature reviews, we developed Urumqi's C pool maps in 1990 and 2010, and assessed the urbanization impacts on ecosystem C. Our results showed that ISA tripled from 1990 to 2010 displacing remnant desert and cropland. The urban landscape, especially the greenspaces, became obviously fragmented. In 2010, more than 95% of the urban ecosystem C was SOC, 48% of which under the ISA. The city lost 19% of C stock from 1990 to 2010. About 82% of the ecosystem C loss was caused by the conversion of remnant desert and cropland into ISA, mainly in the northern city. [ABSTRACT FROM AUTHOR]