A time series of land cover maps of South Asia from 2001 to 2015 generated using AVHRR GIMMS NDVI3g data

In South Asia, key differences in annual land use and land cover (LULC) take place due to climate change, global warming, human activity, biodiversity, and hydrology. So, it is very important to get accurate land cover information for this region. An annual LULC map that covers a comprehensive period is a major dataset for climatologically study. While yearly worldwide maps of LULC are produced from Moderate Resolution Imaging Spectroradiometer (MODIS) dataset, in 2001, the first LULC map of MODIS is generated which restrictions the perspective climatologically analysis. This research work generated a time series of yearly LULC maps of South Asia from 2001 to 2015 by using random forest classification from AVHRR GIMMS NDVI3g data. The MODIS land cover product such as (MCD12Q1) was used as a reference data for the trained classifier. The result was validated by using time series of annual LULC maps, and the spatiotemporal dynamic of LULC maps was illustrated in the last 15 years from 2001 to 2015. The simplified sixteen class versions of our 15-year overall accuracy of a land cover map are 86.70%, and 1.23% higher than that of MODIS maps. The change detection indicated that, for the last 15 years, the class of closed shrublands, savannas, croplands, urban and built-up land, barren, and cropland per natural vegetation mosaics increase notably during the 2001 to 2015, and in contrast, the class of woody savannas, evergreen needleleaf forests, open shrublands, grasslands, mixed forests, permanent wetlands, permanent snow and ice, evergreen broadleaf forests, and water bodies decrease notably during 2001 to 2015. These yearly land cover maps will be an essential dataset for the upcoming climate study, where time series of LULC maps accessibility is restricted.