Interactive comment on “A 30-meter resolution dataset of China’s urban impervious surface area and green space fractions, 2000–2018” by Wenhui Kuang et al.

2020 ◽  
Author(s):  
Wenhui Kuang
Keyword(s):  
Surface Area ◽  
Green Space ◽  
Impervious Surface ◽  
Impervious Surface Area ◽  
Urban Impervious Surface ◽  
Resolution Dataset

scholarly journals A 30-meter resolution dataset of China's urban impervious surface area and green space fractions, 2000–2018

2020 ◽  
Author(s):  
Wenhui Kuang ◽  
Shu Zhang ◽  
Xiaoyong Li ◽  
Dengsheng Lu
Keyword(s):  
Land Use ◽  
Surface Area ◽  
Urban Areas ◽  
Green Space ◽  
Impervious Surface ◽  
Urban Land ◽  
Google Earth ◽  
Urban Land Use ◽  
Impervious Surface Area ◽  
Urban Impervious Surface

Abstract. 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 ×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).

scholarly journals DMBLC: An Indirect Urban Impervious Surface Area Extraction Approach by Detecting and Masking Background Land Cover on Google Earth Image

2018 ◽  
Vol 10 (5) ◽  
pp. 766 ◽  
Author(s):  
Min Huang ◽  
Nengcheng Chen ◽  
Wenying Du ◽  
Zeqiang Chen ◽  
Jianya Gong
Keyword(s):  
Land Cover ◽  
Surface Area ◽  
Impervious Surface ◽  
Google Earth ◽  
Impervious Surface Area ◽  
Urban Impervious Surface
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