NDVI-LST feature space based drought monitoring using MERSI data in Hunan Province of China

Abstract

MERSI (MEdium Resolution Spectral Imager) on board FY3A polar-orbiting meteorological satellite has five channels (four VIS and one thermal IR) with a spatial resolution of 250 m. This paper explores the utility of MERSI in drought monitoring through a case study in Hunan Province of China in May, 2011. Feature space of LST and NDVI are established and three indices including TVDI (Temperature Vegetation Dryness Index), VTCI (Vegetation Temperature Condition Index) and VSWI (Vegetation Supply Water Index) are extracted to provide spatial information on drought. Correlation analysis is carried out between the three indices and soil moisture data collected from meteorological stations. MODIS data are processed in the same way to provide a benchmark for MERSI performance evaluation. Results indicate that TVDI and VTCI are more correlated with top soil moisture. VSWI is inferior to TVDI and VTCI probably due to its sensitivity to topography and land cover type. Although correlation coefficients between MODIS-derived indices and soil moisture are a little higher than MERSI-derived indices, MERSI is able to show more rich spatial details due to its high spatial resolution. The case study demonstrates that MERSI data quality is adequate for drought monitoring and it is worthwhile to apply MERSI data to more wide applications.