Drought indices based on MODIS data compared over a maize-growing season in Songliao Plain, China

Yang Song; Shibo Fang; Zaiqiang Yang; Shuanghe Shen

doi:10.1117/1.JRS.12.046003

5 October 2018 Drought indices based on MODIS data compared over a maize-growing season in Songliao Plain, China

Yang Song, Shibo Fang, Zaiqiang Yang, Shuanghe Shen

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 12, Issue 4, 046003 (October 2018). https://doi.org/10.1117/1.JRS.12.046003

Abstract

Many indices based on MODIS data are used to monitor the process of agricultural drought, such as apparent thermal inertia (ATI) and temperature vegetation dryness index (TVDI). Notable differences in performance and geographic predictions exist among these indices. We statistically evaluated the performance of different drought indices for a known drought process in 2014 in the typical rainfed maize region of Songliao Plain, China, using a linear regression model based on the relationships between indices and soil moisture data. Our results show that during the growth season of May to September, the indices performed independently with changing curves, particularly in different phenological periods. By contrast, correlations tended to be higher for ATI than for other indices in the early vegetative growth stage, whereas small differences were detected among the other indices in the late vegetative to late reproductive growth stages. Our results confirm that the TVDI can be the best choice to detect agricultural drought in the study area.

Citation Download Citation

Yang Song, Shibo Fang, Zaiqiang Yang, and Shuanghe Shen "Drought indices based on MODIS data compared over a maize-growing season in Songliao Plain, China," Journal of Applied Remote Sensing 12(4), 046003 (5 October 2018). https://doi.org/10.1117/1.JRS.12.046003

Received: 1 February 2018; Accepted: 18 September 2018; Published: 5 October 2018

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