Globally, land degradation becomes a serious environmental issue in the context of anthropogenic pressure and climate change in the twenty-first century. Modeling and assessment of land degradation vulnerability assume a greater importance especially in the semi-arid ecosystems for sustainable land resource management. Consistent and reliable earth observation satellite datasets, Analytic Hierarchy Process (AHP), and Geographic Information System (GIS) are the powerful tools to model and assess the land degradation vulnerability. The present study was aimed to model and assess the land degradation vulnerability through analysis of Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), rainfall, terrain characteristics, and pedological parameters by using AHP and GIS in the semi-arid ecosystem of Rayalaseema region of southern India. The NDVI and LST products derived from time-series Moderate Resolution Imaging Spectroradiometer (MODIS) datasets, rainfall products from Tropical Precipitation Measuring Mission (TRMM), terrain characteristics from Shuttle Radar Topography Mission (SRTM) (30 m), and pedological parameters derived from legacy soil datasets were used in the study. The AHP- and GIS-based modeling shows that about 25.3 and 9.9% of the study area were under high and very high vulnerability to land degradation, respectively. Inadequate rainfall and vegetative cover, high temperature, problematic soils, and lack of adequate conservation measures were found to be the main causative environmental factors for land degradation in the study area. The study clearly demonstrates the potential of AHP- and GIS-based modeling in the assessment of land degradation vulnerability by using the time-series MODIS NDVI- and TRMM-based rainfall products, terrain characteristics, and pedological parameters.

在全球范围内，在二十一世纪的人为压力和气候变化的背景下，土地退化成为一个严重的环境问题。土地退化脆弱性的建模和评估具有更大的重要性，尤其是在半干旱生态系统中，对可持续土地资源的管理。一致且可靠的地球观测卫星数据集，层次分析法（AHP）和地理信息系统（GIS）是用于建模和评估土地退化脆弱性的强大工具。本研究旨在通过分析归一化植被指数（NDVI），地表温度（LST），降雨，地形特征，AHP和GIS在印度南部Rayalaseema地区的半干旱生态系统中确定和参数。NDVI和LST产品源自时间序列中等分辨率成像光谱仪（MODIS）数据集，热带降水测量任务（TRMM）的降雨产品，航天飞机雷达地形任务（SRTM）（30 m）的地形特征以及源自以下参数的土壤学参数研究中使用了传统土壤数据集。基于AHP和GIS的模型显示，分别有25.3％和9.9％的研究区域处于土地退化的高度脆弱性之中。降雨和植物覆盖不足，高温，土壤问题以及缺乏适当的保护措施被认为是造成该地区土地退化的主要环境因素。