Iranian Remote Sensing and GIS Society / Shahid Beheshti University Iranian Journal of Remote Sensing and GIS 2008-5966 14 4 2022 12 22 Sensitivity of Vegetation Dryness Index (VDI) to Reflectance of Different Shortwave Infrared Bands in Arid and Semi-Arid Regions (Case Study: Sistan & Baluchestan Province) Sensitivity of Vegetation Dryness Index (VDI) to Reflectance of Different Shortwave Infrared Bands in Arid and Semi-Arid Regions (Case Study: Sistan & Baluchestan Province) 103 118 101884 10.52547/gisj.14.4.103 FA Kamal Omidvar Prof. of Geography, Campus of Humanities and Social Sciences, Yazd University Massumeh Nabavi Zadeh Ph.D. Students, Dep. of Geography, Campus of Humanities and Social Sciences, Yazd University Ahmad Mazidi Associate Prof., Dep. of Geography, Campus of Humanities and Social Sciences, Yazd University HamidReza Ghaffarian Malmiri Assistant Prof., Dep. of Geography, Campus of Humanities and Social Sciences, Yazd University Peyman Mahmoudi Assistant Prof., Dep. of Natural Geography, Faculty of Geography and Environmental Planning, Sistan Journal Article 2020 12 01 Drought monitoring is critical for early warning of drought hazard. This study  is  attempted to develop remote sensing drought monitoring index (VDI), based on Accuracy of different bands of Moderate Resolution Imaging Spectroradiometer data MODIS, VDI focuses about the vegetation water stress.<br /> Spectral studies have demonstrated that due to the large absorption by leaf water, shortwave infrared reflectance (SWIR) is negatively related to leaf water content. Being sensitive to leaf water content, SWIR is widly utilized to construct various remote-sensing indices for example VDI for reflecting vegetation water content, . In this study, Vegetation Drought Index (VDI) was evaluated Based on the sensitivity rate to moisture by shortwave infrared reflectance bands SWIR 5 and 6 (VDI5 and VDI6). The data included the MODIS sensor images from Terra satellite in a period of nineteen years from 2000 to 2018 and Precipitation data are obtained from the Global Land Data Assimilation System (GLDAS), in Sistan & Balouchestan Province, Pearson correlation coefficient was used to evaluate the accuracy of the Drought spatial distribution maps calculated based on the two bands.<br />Results indicate high significant correlation rate between VDI6 and Precipitation data . Study also showed that shortwave infrared band 6 (SWIR) is more sensitive to agricultural drought than band 5,in Sistan and Baluchestan province . The study recommends  to use VDI index with and 6 for better early detection and monitoring of agricultural drought in operational drought management programmes. Drought monitoring is critical for early warning of drought hazard. This study  is  attempted to develop remote sensing drought monitoring index (VDI), based on Accuracy of different bands of Moderate Resolution Imaging Spectroradiometer data MODIS, VDI focuses about the vegetation water stress.<br /> Spectral studies have demonstrated that due to the large absorption by leaf water, shortwave infrared reflectance (SWIR) is negatively related to leaf water content. Being sensitive to leaf water content, SWIR is widly utilized to construct various remote-sensing indices for example VDI for reflecting vegetation water content, . In this study, Vegetation Drought Index (VDI) was evaluated Based on the sensitivity rate to moisture by shortwave infrared reflectance bands SWIR 5 and 6 (VDI5 and VDI6). The data included the MODIS sensor images from Terra satellite in a period of nineteen years from 2000 to 2018 and Precipitation data are obtained from the Global Land Data Assimilation System (GLDAS), in Sistan & Balouchestan Province, Pearson correlation coefficient was used to evaluate the accuracy of the Drought spatial distribution maps calculated based on the two bands.<br />Results indicate high significant correlation rate between VDI6 and Precipitation data . Study also showed that shortwave infrared band 6 (SWIR) is more sensitive to agricultural drought than band 5,in Sistan and Baluchestan province . The study recommends  to use VDI index with and 6 for better early detection and monitoring of agricultural drought in operational drought management programmes. https://gisj.sbu.ac.ir/article_101884_541de13b0c46fc3d1b8e45c22356e73c.pdf