title: [Evaluating the utility of MODIS vegetation index for monitoring agricultural drought].
abstract: The exclusive shortwave bands provided by MODIS sensors offer new opportunities for agricultural drought monitoring, since they are very sensitive to vegetation moisture. In the present work, we selected Songnen Plain in Northeast China as study area aiming at monitoring agricultural drought of dry farmland here. Four types of vegetation water indices and vegetation greenness indices were calculated from the 8-day composite MODIS product (MODO9A1) in vegetation growing season between 2001 and 2010, respectively. Multi-scale standardized precipitation index (SPI) derived from precipitation data of weather stations was used as reference data to estimate drought sensitivity of various vegetation indices, and a pixel-to-weather station paired correlation approach was used to calculate the Pearson correlation coefficient between vegetation index and SPIs. The result indicated that vegetation water indices established by near infrared and shortwave infrared bands outperformed vegetation greenness indices based on visible and near infrared bands. Of these indices, NDII7 performs the best with highest correlation coefficients across all SPIs. The authors' results demonstrated the potential of MODIS shortwave spectral bands in monitoring agricultural drought, and this provides new insights to future research.
authors.affiliation: Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, China. lhpcas@163.com
authors.forename: Hua-Peng
authors.initials: HP
authors.lastname: Li
authors.forename: Shu-Qing
authors.initials: SQ
authors.lastname: Zhang
authors.forename: Zi-Qiang
authors.initials: ZQ
authors.lastname: Gao
authors.forename: Yan
authors.initials: Y
authors.lastname: Sun
mesh_terms: D018556:Crops, Agricultural / Q000254:growth & development* / Q000378:metabolism; D055864:Droughts; D004784:Environmental Monitoring / Q000295:instrumentation / Q000379:methods*; D010788:Photosynthesis; D018515:Plant Leaves / Q000737:chemistry*; D058998:Remote Sensing Technology / Q000379:methods; D019265:Spectroscopy, Near-Infrared / Q000379:methods*