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dc:title "HTML Summary of #11542 \n\nAssessment of spatio-temporal vegetation dynamics in tropical arid ecosystem of India using MODIS time-series vegetation indices\n\n";
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bibo:abstract "In the present study, we analyzed spatio-temporal vegetation dynamics to identify and delineate the vegetation stress zones in\r\ntropical arid ecosystem of Anantapuramu district, Andhra Pradesh, India, using Normalized Difference Vegetation Index\r\n(NDVI), Vegetation Condition Index (VCI), and Vegetation Anomaly Index (VAI) derived from time-series Moderate\r\nResolution Imaging Spectroradiometer (MODIS) 16-day products (MOD13Q1) at 250 m spatial resolution for the growing\r\nseason (June to September) of 19 years during 2000 to 2018. The 1-month Standardized Precipitation Index (SPI) was computed\r\nfor 30 years (1989 to 2018) to quantify the precipitation deficit/surplus regions and assess its influence on vegetation dynamics.\r\nThe growing season mean NDVI and VCI were correlated with growing season mean 1-month SPI of dry (2003) and wet (2007)\r\nyears to analyze the spatio-temporal vegetation dynamics. The correlation analysis between SPI and NDVI for dry year (2003)\r\nshowed strong positive correlation (r = 0.89). Analysis of VAI for dry year (2003) indicates that the central, western, and southwestern\r\nparts of the district reported high vegetation stress with VAI of less than − 2.0. This might be due to the fact that central\r\nand south-western parts of the district are more prone to droughts than the other parts of the district. The correlation analysis of\r\nSPI, NDVI, and VCI distinctly shows the impact of rainfall on vegetation dynamics. The study clearly demonstrates the\r\nrobustness of NDVI, VCI, and VAI derived from time-series MODIS data in monitoring the spatio-temporal vegetation dynamics\r\nand delineate vegetation stress zones in tropical arid ecosystem of India."^^xsd:string;
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bibo:issue "15";
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bibo:volume "13";
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dct:date "2020-06";
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skos:prefLabel "Semi-Arid Tropics"@en .
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skos:prefLabel "GIS Techniques/Remote Sensing"@en .
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bibo:issn "18667511";
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