Abstract
Building a density map over large areas could provide essential information of land development intensity and settlement condition. It is crucial for supporting studies and planning of human settlement environment. The Global Human Settlement Layer (GHSL) is a comprehensive data set of mapping human settlement at a global scale, which was produced by the Joint Research Centre (JRC), European Commission. The built-up density is an important layer of GHSL data set. Currently, the validation of the GHSL built-up area products was preliminarily conducted over the United States and European countries. However, as a typical East Asian region, China is quite different from the United States, Europe, and other regions in terms of building forms and urban layouts. Therefore, it is necessary to perform an accuracy assessment of GHSL data set in Asian countries like China. With individual building footprint data of 20 typical cities in China, this paper presents our effort to validate the GHSL built-up area products. The aggregation mean and neighborhood search based algorithms are adopted for matching building footprint data and the GHSL products, through the regression analysis at per-pixel level, the building density map in raster format are generated as validation data. The accuracy index of GHSL built-up area was calculated for the study areas, and the validation methods were explored for GHSL built-up products at large scale. The results show that the built-up layer aggregated by the building footprint have the highest correlation with the coarse resolution GHSL built-up products, but GHSL tends to underestimate the building density of low-density areas and overestimate the areas with high density. This study suggests that GHSL built-up area products in 20 representative Chinese cities of China could provide quantitative information about built-up areas, but the product accuracy still need to be improved in the regions with heterogeneous formations of human settlements like China. There is a big picture of mapping high accuracy built-up density of China with the training data set acquired by the study.
Highlights
Land cover is an important factor of environmental studies of the earth surfaces [1,2,3], since the land cover/land use change, environmental pollution, land degradation and loss of biodiversity have become increasingly serious
The Global Urban Footprint (GUF) dataset is produced for urban mapping, it is based on the satellite SAR imagery acquired by the German satellites TerraSAR-X and TanDEM-X
The Global Human Built-up And Settlement Extent (HBASE) Dataset is a global scale product derived from the Global Land Survey (GLS) Landsat dataset for the year of 2010 [16], the product is only for the mapping and monitoring of urbanization
Summary
Land cover is an important factor of environmental studies of the earth surfaces [1,2,3], since the land cover/land use change, environmental pollution, land degradation and loss of biodiversity have become increasingly serious. Urbanization is one of the most significant factors that human influence the land cover of earth surfaces. As the high-resolution remote sensing satellite data can provide detailed urban surfaces, Xu investigated the land cover information extraction using IKONOS panchromatic data with 1m resolution [13]. With a fully automated processing system, global coverage of more than 180,000 very high-resolution SAR images with 3m ground resolution, mainly acquired between 2010 and 2013, were processed, the scattering amplitude is combined with the derived texture information to depict the human settlement. The products contain comprehensive data layer for urbanization assessment, land cover change, urban planning and management [6], species changes studies [18], but the accuracy of the product needs further validation. The development of large-scale building density remote sensing products, the formation of large-scale and long time series of remote sensing mapping products has become an urgent need for both research and applications
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