In the present study, we analyzed spatio-temporal vegetation dynamics to identify and delineate the vegetation stress zones in tropical arid ecosystem of Anantapuramu district, Andhra Pradesh, India, using Normalized Difference Vegetation Index (NDVI), Vegetation Condition Index (VCI), and Vegetation Anomaly Index (VAI) derived from time-series Moderate Resolution Imaging Spectroradiometer (MODIS) 16-day products (MOD13Q1) at 250 m spatial resolution for the growing season (June to September) of 19 years during 2000 to 2018. The 1-month Standardized Precipitation Index (SPI) was computed for 30 years (1989 to 2018) to quantify the precipitation deficit/surplus regions and assess its influence on vegetation dynamics. The growing season mean NDVI and VCI were correlated with growing season mean 1-month SPI of dry (2003) and wet (2007) years to analyze the spatio-temporal vegetation dynamics. The correlation analysis between SPI and NDVI for dry year (2003) showed strong positive correlation (r = 0.89). Analysis of VAI for dry year (2003) indicates that the central, western, and south-western parts of the district reported high vegetation stress with VAI of less than − 2.0. This might be due to the fact that central and south-western parts of the district are more prone to droughts than the other parts of the district. The correlation analysis of SPI, NDVI, and VCI distinctly shows the impact of rainfall on vegetation dynamics. The study clearly demonstrates the robustness of NDVI, VCI, and VAI derived from time-series MODIS data in monitoring the spatio-temporal vegetation dynamics and delineate vegetation stress zones in tropical arid ecosystem of India.

生长季节的平均NDVI和VCI与干旱（2003年）和潮湿（2007年）的1个月SPI的生长季节平均相关，以分析时空植被动态。干旱年份（2003年）的SPI与NDVI之间的相关性分析显示强正相关（r = 0.89）。对干旱年份（2003年）进行的VAI分析表明，该地区的中部，西部和西南部报告了较高的植被胁迫，其VAI小于-2.0。这可能是由于该地区的中部和西南部地区比该地区的其他地区更容易发生干旱。SPI，NDVI和VCI的相关分析清楚地显示了降雨对植被动态的影响。这项研究清楚地证明了从时间序列MODIS数据得出的NDVI，VCI和VAI在监测印度热带干旱生态系统的时空植被动态和描绘植被压力带方面的鲁棒性。