The main objective of this study is to investigate land degradation and environmental change in Mongolia using time series of multi-sources remotely sensed data and advanced approaches. As the data analysis techniques, the Random Forest (RF) classifier, Ordinary Least Square (OLS), and Partial Least Square (PLS) regressions, Break for Additive Season and Trend (BFAST) algorithm, Sen’s slope and Restrend method were applied. For detecting land degradation and environmental change, we have investigated several factor impacts: (1) climate factor impact on land degradation and environmental change, (2) impact of land cover change on land degradation and environmental change, (3) impact of vegetation index on land degradation and environmental change, (4) impact of drought on land degradation and environmental change. The meteorological time series analysis showed that between 1990 and 2019, air temperature over Mongolian has increased by 1.8 °C, while annual total precipitation over Mongolia had decreased from 714 to 640 mm. The land cover analysis indicated that between 1990 and 2019, forest, steppe, dry steppe, and cropland were decreased. In contrast, the meadow steppe, wetland, sand land, broken area, urban land, and water were increased. The trend analysis result indicated that positive trends were observed in Mongolia's central, northern, and northeastern parts. In contrast, the negative trends were detected in all areas of the west, southern region, forested areas in the north and east, around the Ulaanbaatar city, and in the grassland area of eastern Mongolia. The drought detection analysis showed that the years 1993, 1994, 1997, 2000–2002, 2004–2007, 2009, and 2017 could very well detect the droughts during the growing season for the period 1990–2019. The trend analysis result showed that negative and positive trends of time series NDVI were strongly related to land cover change.
