Calculating regional drought indices using evapotranspiration (ET) distribution derived from Landsat7 ETM+ data

Hongjun Li; Yuping Lei; Li Zheng; Renzhao Mao

doi:10.1117/12.615880

1 September 2005 Calculating regional drought indices using evapotranspiration (ET) distribution derived from Landsat7 ETM⁺ data

Hongjun Li, Yuping Lei, Li Zheng, Renzhao Mao

Author Affiliations +

Proceedings Volume 5884, Remote Sensing and Modeling of Ecosystems for Sustainability II; 58841E (2005) https://doi.org/10.1117/12.615880
Event: Optics and Photonics 2005, 2005, San Diego, California, United States

Abstract

In this study, we demonstrate that the conventional temperature/vegetation drought index (TVDI) approach tends to overstate the degree of drought condition in areas with dense vegetation. This is because the TVDI approach may specify points with significant evapotranspiration (ET) activities (i.e. points with soil water content significantly above the wilting point) as the drought points in these areas. To overcome this shortcoming, we construct a new drought index, termed evapotranspiration/vegetation drought index (EVDI), using evapotranspiration distribution derived from the remote sensing data. We apply both TVDI and EVDI approaches to calculate drought indices for a dominantly crop farming region, Luancheng County, in Hebei Province of China at the season of high fractional vegetation cover. We use Landsat7 ETM⁺ data to derive the surface temperature, the fractional vegetation cover and evapotranspiration distribution, and compute both TVDI and EVDI maps for this region. Result comparison and analyses show that the TVDI map overstates the drought condition. The EVDI map is a more accurate representation of the real condition.

Citation Download Citation

Hongjun Li, Yuping Lei, Li Zheng, and Renzhao Mao "Calculating regional drought indices using evapotranspiration (ET) distribution derived from Landsat7 ETM⁺ data", Proc. SPIE 5884, Remote Sensing and Modeling of Ecosystems for Sustainability II, 58841E (1 September 2005); https://doi.org/10.1117/12.615880

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KEYWORDS

Vegetation

Remote sensing

Earth observing sensors

Landsat

Heat flux

Soil science

Lithium

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