Monitoring desertification processes in Mongolian Plateau using MODIS tasseled cap transformation and TGSI time series

Most remote sensing studies assess the desertification using vegetation monitoring method. But it has the insufficient precision of vegetation monitoring for the limited vegetation cover of the desertification region. Therefore, it offers an alternative approach for the desertification research to assess sand dune and sandy land change using remote sensing in the desertification region. In this study, the indices derived from the well-known tasseled cap transformation(TCT), tasseled cap angle(TCA),disturbance index(DI), process indicator(PI), and topsoil grain size index(TGSI) were integrated to monitor and assess the desertification at the thirteen study sites including sand dunes and sandy lands distributed in the Mongolian Plateau(MP) from 2000 to 2015. A decision tree was used to classify the desertification on a regional scale. The average overall accuracy of 2000, 2005, 2010 and 2015 desertification classification was higher than 90%. Results from this study indicated that integration of the advantages of TCA, DI and TGSI could better assess the desertification. During the last 16 years, Badain Jaran Desert, Tengger Desert, and Ulan Buh Desert showed a relative stabilization. Otindag Sandy Land and the deserts of Khar Nuur, Ereen Nuur, Tsagan Nuur, Khongoryn Els, Hobq, and Mu Us showed a slow increasing of desertification, whereas Bayan Gobi, Horqin and Hulun Buir sandy lands showed a slow decreasing of desertification. Compared with the other 11 sites, the fine sand dunes occupied the majority of the Tengger Desert, and the coarse sandy land occupied the majority of the Horqin Sandy Land. Our findings on a three or four years' periodical fluctuated changes in the desertification may possibly reflect changing precipitation and soil moisture in the MP. Further work to link the TCA, DI,TGSI, and PI values with the desertification characteristics is recommended to set the thresholds and improve the assessment accuracy with field investigation.