VSDI: a visible and shortwave infrared drought index for monitoring soil and vegetation moisture based on optical remote sensing

Abstract

In this article, a new index, the visible and shortwave infrared drought index (VSDI), is proposed for monitoring both soil and vegetation moisture using optical spectral bands. VSDI is defined as , where ρ represents the reflectance of shortwave infrared (SWIR) red and blue channels, respectively. VSDI is theoretically based on the difference between moisture-sensitive bands (SWIR and red) and moisture reference band (blue), and is expected to be efficient for agricultural drought monitoring over different land-cover types during the plant-growing season. The fractional water index (FWI) derived from 49 Mesonet stations over nine climate divisions (CDs) across Oklahoma are used as ground truth data and VSDI is compared with three other drought indices. The results show that VSDI generally presents the highest correlation with FWI among the four indices, either for whole sites or for individual CDs. The NDVI threshold method is applied to demonstrate the satisfactory performance of VSDI over different land-cover types. A time-lag analysis is also conducted and suggests that VSDI can be used as a real-time drought indicator with a time lag of less than 8 days. The VSDI drought maps are produced and compared with the US Drought Monitor (USDM) maps. A good agreement has been observed between the two products, and finer spatial information is also found in VSDI. In conclusion, VSDI appears to be a real-time drought indicator that is applicable over different land-cover types and is suitable for drought monitoring through the plant-growing season.

Acknowledgements

The authors would like to thank the Mesonet network (http://www.mesonet.org) for providing the ground measurement data. The MODIS reflectance products (MOD09A1) used in this study were collected from http://ladsweb.nascom.nasa.gov/data The CDL used in this study was downloaded from the Geospatial Data Gateway at http://datagateway.nrcs.usda.gov/. The archive maps of the USDM were obtained from http://droughtmonitor.unl.edu/archive.html The authors also thank anonymous reviewers for their critical and helpful comments and suggestions. The authors appreciate the generous financial support of the National Natural Science Foundation of China (No. 41071221, No. 41201331) and the R&D Special Fund for Public Welfare Industry of China (Meteorology) (No. GYHY 200806022). The lead author would also like to thank the HyDROS Lab (http://hydro.ou.edu) at the National Weather Center, Norman, Oklahoma.