Publications

Khan, J; Wang, PX; Xie, Y; Wang, L; Li, L (2018). Mapping MODIS LST NDVI Imagery for Drought Monitoring in Punjab Pakistan. IEEE ACCESS, 6, 19898-19911.

Abstract
A near-real-time drought monitoring approach termed as vegetation temperature condition index (VTCI) and a geospatial near-real-time coupling (NRTC) approach were applied to investigate drought over the great plain of Punjab, Pakistan. We identified the warm edges (LSTmax) and cold edges (LSTmin) as well as determined and validated the drought on a time series (2003-2008) of satellite EOS's MODIS-Aqua data products. We assessed six years of drought conditions during the winter-wheat-growing seasons and determined the effects of the record-breaking drought during 1998-2002 and its impact on the 2003-2008 periods. The VTCI drought monitoring approach is based on the integration of the normalized difference vegetation index and land surface temperature for comprehensive coverage of current drought and edges determination. The geospatial NRTC approach, which utilizes the VTCI imagery and daily precipitation data, was used for the validation of drought over five weather stations. It was established that the VTCI result has a higher correlation coefficient (r) with cumulative precipitation (r = 0.88) in the winter, during the six-year period of the Julian day of year (D-041), whereas the D-169 correlation was found to be negative in the summer, as the thermal boundaries gradually increases, which indicate the seasons and time of the days. The drift finding indicates that the VTCI not only achieves results that are very close to the recent precipitation anomaly but also correlates on the past precipitation. This analysis shows the good sensitivity of the VTCI to soil moisture and precipitation in agricultural areas. Our results suggest the capability of the VTCI for near-real-time drought monitoring as a better indicator of vegetation and thermal conditions over the regions in both rainfed and irrigated covenant areas.

DOI:
10.1109/ACCESS.2018.2821717

ISSN:
2169-3536