Development of a Drought Detection Indicator using MODIS Thermal Infrared Data

Based on surface energy balance climatology, surface temperatures should respond to drying conditions well before plant response. To test this hypothesis, land surface temperatures (LST) derived from MODIS data were analyzed to determine how the data were correlated with climatic water balance variables and NDVI anomalies during a growing season in Western and Central Kansas. Daily MODIS data were integrated into weekly composites so that each composite data set included the maximum temperature recorded at each pixel during each composite period. Time-integrated, or cumulative values of the LST deviation standardized with mean air temperatures had significantly high correlation coefficients with SM, AE/PE, and MD/PE, ranging from 0.65 to 0.89. The Standardized Thermal Index (STI) is proposed in this study to accomplish the objective. The STI, based on surface temperatures standardized with observed mean air temperatures, had significant temporal relationships with the hydroclimatological factors. STI classes in all the composite periods also had a strong correlation with NDVI declines during a drought episode. Results showed that, based on LST, air temperature observations, and water budget analysis, NDVI declines below normal could be predicted as early as 8 weeks in advance in this study area.