Abstract
In South Asia, annual land cover and land use (LCLU) is a severe issue in the field of earth science because it affects regional climate, global warming, and human activities. Therefore, it is vital essential to obtain correct information on the LCLU in the South Asia regions. LULC annual map covering the entire period is the primary dataset for climatological research. Although the LULC annual global map was produced from the MODIS dataset in 2001, this limited the perspective of the climatological analysis. This study used AVHRR GIMMS NDVI3g data from 2001 to 2015 to randomly forests classify and produced a time series of the annual LCLU map of the South Asia. The MODIS land cover products (MCD12Q1) are used as data from reference for trained classifiers. The results were verified using of the annual map of LCLU time series, and the space-time dynamics of the LCLU map were shown in the last 15 years, from 2001 to 2015. The overall precision of our 15-year land cover map simplifies 16 classes, which is 1.23% and 86.70% significantly maximum as compared to the precision of the MODIS data map. Findings of the past 15 years shows the changing detection that forest land, savanna, farmland, urban and established land, arid land, and cultivated land have increased; by contrast, woody prairie, open shrub-lands, permanent ice and snow, mixed forests, grasslands, evergreen broadleaf forests, permanent wetlands, and water bodies have been significantly reduced over South Asia regions.
Factors Influencing Activity of Xiwang Road Ground Fissure Based on Time-series Interferometric Synthetic Aperture Radar and Detection of Land Cover Changes Using Optical Imaging
