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        <dc:title>Assessment of spatio-temporal vegetation dynamics in tropical arid ecosystem of India using MODIS time-series vegetation indices</dc:title>
        <dc:creator>Reddy, G P A</dc:creator>
        <dc:creator>Kumar, N</dc:creator>
        <dc:creator>Sahu, N</dc:creator>
        <dc:creator>Srivastava, R</dc:creator>
        <dc:creator>Singh, S K</dc:creator>
        <dc:creator>Naidu, LG K</dc:creator>
        <dc:creator>Chary, G R</dc:creator>
        <dc:creator>Biradar, C M</dc:creator>
        <dc:creator>Gumma, M K</dc:creator>
        <dc:creator>Reddy, B S</dc:creator>
        <dc:creator>Kumar, J N</dc:creator>
        <dc:subject>GIS Techniques/Remote Sensing</dc:subject>
        <dc:subject>Semi-Arid Tropics</dc:subject>
        <dc:description>In the present study, we analyzed spatio-temporal vegetation dynamics to identify and delineate the vegetation stress zones in&#13;
tropical arid ecosystem of Anantapuramu district, Andhra Pradesh, India, using Normalized Difference Vegetation Index&#13;
(NDVI), Vegetation Condition Index (VCI), and Vegetation Anomaly Index (VAI) derived from time-series Moderate&#13;
Resolution Imaging Spectroradiometer (MODIS) 16-day products (MOD13Q1) at 250 m spatial resolution for the growing&#13;
season (June to September) of 19 years during 2000 to 2018. The 1-month Standardized Precipitation Index (SPI) was computed&#13;
for 30 years (1989 to 2018) to quantify the precipitation deficit/surplus regions and assess its influence on vegetation dynamics.&#13;
The growing season mean NDVI and VCI were correlated with growing season mean 1-month SPI of dry (2003) and wet (2007)&#13;
years to analyze the spatio-temporal vegetation dynamics. The correlation analysis between SPI and NDVI for dry year (2003)&#13;
showed strong positive correlation (r = 0.89). Analysis of VAI for dry year (2003) indicates that the central, western, and southwestern&#13;
parts of the district reported high vegetation stress with VAI of less than − 2.0. This might be due to the fact that central&#13;
and south-western parts of the district are more prone to droughts than the other parts of the district. The correlation analysis of&#13;
SPI, NDVI, and VCI distinctly shows the impact of rainfall on vegetation dynamics. The study clearly demonstrates the&#13;
robustness of NDVI, VCI, and VAI derived from time-series MODIS data in monitoring the spatio-temporal vegetation dynamics&#13;
and delineate vegetation stress zones in tropical arid ecosystem of India.</dc:description>
        <dc:publisher>Springer, Saudi Society for Geosciences</dc:publisher>
        <dc:date>2020-06</dc:date>
        <dc:type>Article</dc:type>
        <dc:type>PeerReviewed</dc:type>
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        <dc:language>en</dc:language>
        <dc:identifier>http://oar.icrisat.org/11542/1/06_Spatio-temporal%20dynamics-arid%20ecosystems_AJG.pdf</dc:identifier>
        <dc:identifier>  Reddy, G P A and Kumar, N and Sahu, N and Srivastava, R and Singh, S K and Naidu, LG K and Chary, G R and Biradar, C M and Gumma, M K and Reddy, B S and Kumar, J N  (2020) Assessment of spatio-temporal vegetation dynamics in tropical arid ecosystem of India using MODIS time-series vegetation indices.  Arabian Journal of Geosciences (TSI), 13 (15).  pp. 1-13.  ISSN 1866-7511     </dc:identifier>
        <dc:relation>https://doi.org/10.1007/s12517-020-05611-4</dc:relation>
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