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Assessment of spatio-temporal vegetation dynamics in tropical arid ecosystem of India using MODIS time-series vegetation indices

机译:使用MODIS时间级植被指数评估印度热带干旱生态系统中的时空植被动态

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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.
机译:在本研究中,我们分析了时空植被动力学,以识别和描绘印度Anantapuramu区的热带干旱生态系统中的植被应力区,采用归一化差异植被指数(NDVI),植被条件指数(VCI),以及植被异常指数(vai)来自时间系列中度分辨率成像分光镜(MODIS)16日产品(Mod13Q1),在2000年至2018年期间的19年的生长季节(6月至9月)以250米的空间分辨率为250米。1-月份标准化降水指数(SPI)已计算30年(1989年至2018),以量化降水赤字/剩余地区,并评估其对植被动态的影响。不断增长的季节意味着NDVI和VCI与生长季节意味着1个月的干燥(2003)和潮湿(2007)年来分析时空植被动态。干燥年份(2003)SPI和NDVI之间的相关分析显示出强烈的正相关(R = 0.89)。沃伊对干燥年(2003年)的分析表明,该区中央,西部和西南部地区的畜牧患者高于-2.0的vai植被胁迫。这可能是由于该地区的中南部部位更容易出现比区的其他地区更容易出现干旱。 SPI,NDVI和VCI的相关分析明显显示降雨对植被动态的影响。该研究清楚地展示了NDVI,VCI和Vai的鲁棒性来自时序序列MODIS数据,在监测印度热带干旱生态系统中的时期植被动态和描绘植被应力区域。

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