A new regional vegetation mapping method based on terrain-climate-remote sensing and its application on the Qinghai-Xizang Plateau

Understanding the impact of climate change on vegetation and its evolution trend requires long-term accurate data on regional vegetation types and their geographical distribution. Currently, land use and land cover types are mainly obtained based on remote sensing information. Little research has been conducted on remote sensing interpretation of vegetation types and their geographical distributions in terms of the comprehensive utilization of remote sensing, climate, and terrain. A new region vegetation mapping method based on terrain-climate-remote sensing was developed in this study, supported by the Google Earth Engine (GEE) and the random forest algorithm, which is a new generation of earth science data and analysis application platform, together with optimal vegetation mapping features obtained from the average impure reduction method and out-of-bag error value, using different information from remote sensing, climate, and terrain. This vegetation of Qinghai-Xizang Plateau with 10 m spatial resolution in 2020 was mapped, in terms of this new vegetation mapping method, Sentinel-2A/B remotely sensed images, climate, and terrain. The accuracy verification of vegetation mapping on the Qinghai-Xizang Plateau showed an overall accuracy of 89.5% and a Kappa coefficient of 0.87. The results suggest that the regional vegetation mapping method based on terrain-climate-remote sensing proposed in this study can provide technical support for obtaining long-term accurate data on vegetation types and their geographical distributions on the Qinghai-Xizang Plateau and the globe.

Automated summary

Understanding the impact of climate change on vegetation and its evolution trend requires accurate and long-term regional vegetation data. This study developed a new method for mapping regional vegetation using terrain-climate-remote sensing. The method, supported by Google Earth Engine and the random forest algorithm, utilized information from remote sensing, climate, and terrain to achieve a 10-meter spatial resolution vegetation map of the Qinghai-Xizang Plateau in 2020.