Analysis of agricultural drought using vegetation temperature condition index (VTCI) from Terra/MODIS satellite data
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The most commonly used normalized difference vegetation index (NDVI) from remote sensing often fall short in real-time drought monitoring due to a lagged vegetation response to drought. Therefore, research recently emphasized on the use of combination of surface temperature and NDVI which provides vegetation and moisture conditions simultaneously. Since drought stress effects on agriculture are closely linked to actual evapotranspiration, we used a vegetation temperature condition index (VTCI) which is more closely related to crop water status and holds a key place in real-time drought monitoring and assessment. In this study, NDVI and land surface temperature (T s) from MODIS 8-day composite data during cloud-free period (September–October) were adopted to construct an NDVI–T s space, from which the VTCI was computed. The crop moisture index (based on estimates of potential evapotranspiration and soil moisture depletion) was calculated to represent soil moisture stress on weekly basis for 20 weather monitoring stations. Correlation and regression analysis were attempted to relate VTCI with crop moisture status and crop performance. VTCI was found to accurately access the degree and spatial extent of drought stress in all years (2000, 2002, and 2004). The temporal variation of VTCI also provides drought pattern changes over space and time. Results showed significant and positive relations between CMI (crop moisture index) and VTCI observed particularly during prominent drought periods which proved VTCI as an ideal index to monitor terminal drought at regional scale. VTCI had significant positive relationship with yield but weakly related to crop anomalies. Duration of terminal drought stress derived from VTCI has a significant negative relationship with yields of major grain and oilseeds crops, particularly, groundnut.
KeywordsRemote sensing MODIS Ts-NDVI space VTCI Drought Crop yields
Authors would like to thank the MODIS Land Discipline Group for creating and sharing the MODIS LAND data. We also express our sincere thanks to Department of Agrometeorology, AAU, Anand (India) and Department of Agriculture, Gandhinagar for sharing meteorological and crop yield statistics.
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