A New Index for Sandy Land Detection Based On Thermal Infrared Emissivity Data

Spatial distribution and disappearance of sandy land is important for ecosystem management of desert regions and provides highly valuable information on desertification and climate change studies in arid environments. Based on the field measurement in the Gurbantonggut Desert, Xinjiang, China and the analysis of the spectral features of sandy land, a new sand differential emissivity index (SDEI) was proposed first for sandy land detection. Compared with the previous vegetation index, which can only distinguish green plants from bare land, SDEI can make a distinction well between sandy land and dry vegetation. For large regional mapping of sandy land, SDEI was applied on the ASTER Global Emissivity Dataset based on the Google Earth Engine platform. And then, four emissivity simulation schemes of different mixed pixels were conducted to determine the best threshold of sandy land mapping. The results show that when the threshold value is larger than 0.041, the sand distribution can be well extracted. Finally, the sandy land area of China extracted by SDEI is 160.67×104 km2 for year 2008, which is close to the data released by the China’s State Forestry Administration. These experimental results indicated that SDEI is applicable to identification of sandy land, and therefore satellite remotely-sensed thermal infrared observations have good potential in sandy land detection.