Remote sensing-based mapping for the new generation of Vegetation Map of China (1:500,000)
Qinghua Guo, Hongcan Guan, Tianyu Hu, Shichao Jin, Yanjun Su, Xuejing Wang, Dengjie Wei, Qin Ma, Qianhui Sun
Abstract
<p indent="0mm">Vegetation maps serve as the key source information for ecological studies, biodiversity conservation, and vegetation management and restoration. The latest version of the Vegetation Map of China (1:1,000,000) was generated in the 1980s. Since then, the vegetation distribution pattern of China has changed dramatically during these <sc>40 years.</sc> Classification errors and time lag have limited the applications of Vegetation Map of China (1:1,000,000), and it is in great demand to make the new generation of national vegetation map to fulfill the needs of ecological studies and government policy making. The development of satellite remote sensing technology provides a practical and economical approach to achieve vegetation mapping in large scale. In this article, we reviewed methods of vegetation mapping at national scale and the progress of satellite remote sensing technology on vegetation classification and mapping, and summarized the current bottleneck in vegetation mapping from satellite images. Further, we introduced a vegetation mapping strategy through the combination of crowdsource sample collection, object-based segmentation, and deep learning techinique from multi-source data. Over 50 taxonomists across China participated in the validation and calibration process through a self-developed online mapping system.