Time-series normalized difference vegetation index (NDVI) is commonly used to conduct vegetation dynamics, which is an important research topic. However, few studies have focused on the relationship between vegetation type and NDVI changes. We investigated changes in vegetation in Xinjiang using linear regression of time-series MOD13Q1 NDVI data from 2001 to 2020. MCD12Q1 vegetation type data from 2001 to 2019 were used to analyze transformations among different vegetation types, and the relationship between the transformation of vegetation type and NDVI was analyzed. Approximately 63.29% of the vegetation showed no significant changes. In the vegetation-changed area, approximately 93.88% and 6.12% of the vegetation showed a significant increase and decrease in NDVI, respectively. Approximately 43,382.82 km2 of sparse vegetation and 25,915.44 km2 of grassland were transformed into grassland and cropland, respectively. Moreover, 17.4% of the area with transformed vegetation showed a significant increase in NDVI, whereas 14.61% showed a decrease in NDVI. Furthermore, in areas with NDVI increased, the mean NDVI slopes of pixels in which sparse vegetation transferred to cropland, sparse vegetation transferred to grassland, and grassland transferred to cropland were 9.8 and 3.2 times that of sparse vegetation, and 1.97 times that of grassland, respectively. In areas with decreased NDVI, the mean NDVI slopes of pixels in which cropland transferred to sparse vegetation, grassland transferred to sparse vegetation were 1.75 and 1.36 times that of sparse vegetation, respectively. The combination of vegetation type transformation NDVI time-series can assist in comprehensively understanding the vegetation change characteristics.
IDENTIFICATION OF AFFECTED HIGH-ALTITUDE WETLANDS IN THE NORTH CHILE USING LARGE LANDSAT TIME SERIES
