Abstract
Monitoring rock desert formation caused by two different origins (ice-snow melting and drying) through remote sensing is crucial to our understanding of the interaction between the underlying surface of different rock desert and land-atmosphere types, as well as the relationship between bare land and soil erosion. A number of achievements have been made in remote sensing monitoring of desert areas, but there is a lack of accurate classification and remote sensing identification of rock desert types based on formation mechanism. In this study, the north and south sides of the eastern Kunlun Mountains in the northern part of the Qinghai-Tibet Plateau of China were taken as the study areas. Landsat operational landscape imager, digital elevation model, and precipitation and temperature grid data were used as data sources. By identifying the bare areas based on the normalized difference vegetation index (NDVI), we used the multi-element fusion method of contours, isotherms, and isohyets to identify the rock desert types in the ice-snow melting and dry areas. The results showed that: (1) the rock desert areas identified by remote sensing based on topographic and meteorological elements were highly accurate, with an overall accuracy of 88.45％ and kappa coefficient of 0.77. The multi-element fusion method of contours, isotherms, and isohyets could effectively identify the rock desert types in the ice-snow melting and dry areas; (2) the optimal segmentation range of the ice-snow melting and dry areas was 3600 m contour, –2℃–2℃ isotherms, and 100–130 mm isohyets. The areas with elevation less than 3600 m, annual average temperature higher than 2℃, and average annual precipitation less than 100 mm were rock desert in the dry areas. The range of –2℃–2℃ isotherms and 100–130 mm isohyets was the transition area between the ice-snow melting and dry areas. The areas with elevation higher than 3600 m, annual average temperature less than –2℃, and average annual precipitation higher than 130 mm were rock desert in the ice-snow melting areas; and (3) the identification accuracy of the bare areas based on the NDVI method was better, specifically, the identification accuracy of plain bare areas was generally better than that of mountain bare areas. The remote sensing identification method considers not only the topographic factors that have great influence on the spatial distribution of the two types of rock desert areas, but also the meteorological factors, which can provide a scientific reference for the effective identification of the two types of rock desert areas.
基金项目
Natural Science Foundation of Qinghai Province of China(2021-ZJ-905)
Second Qinghai-Tibet Plateau Scientific Expedition and Research Program of China(2019QZKK0606)
国家科技期刊平台
NSTL
万方数据