Date of Award




Document Type

Master's Thesis

Degree Name

Master of Science (MS)


Department of Atmospheric and Environmental Sciences

Content Description

1 online resource (iii, 54 pages) : illustrations (some color), color map.

Dissertation/Thesis Chair

Qilong Min

Committee Members

Lee Harrison


edvi, land skin temperature, microwave emissivity, microwave remote sensing, vegetation, Droughts, Plants, Vegetation and climate, Vegetation monitoring

Subject Categories

Atmospheric Sciences | Meteorology | Remote Sensing


As monitoring vegetation and crops becomes increasingly important due to climate change, there arises the need for a monitoring scheme that places more weight on water availability as an indication of vegetation health and vitality. The Emissivity Difference Vegetation Index (EDVI) is the first step towards that type of monitoring scheme. With the potential for diurnal studies, there are applications towards agriculture monitoring, wildfire monitoring, and much more. EDVI is a synergetic product retrieved from microwave, visible, and infrared satellite measurements, as well as reanalysis. Since microwave measurements are more sensitive to vegetation water content, EDVI has the potential to capture intrinsic changes in vegetation. A new drought index is developed from EDVI, the Emissivity Vegetation Condition Index (EVCI). The high temporal sampling of EVCI will make it one of the more dynamic attempts to measure and investigate drought impacts on vegetation and crops on short-term scales. This new drought index will be compared to presently operational drought indices including the Palmer drought indices, the Vegetation Condition Index (VCI), and the Vegetation Health Index (VHI) for the period between 2009-2011 in the United States. The focus will be on improving the methodology of the EDVI retrieval and then examining two periods of identified drought, one in the Southern Great Plains in 2011, and one short-term drought in the Great Lakes region in 2010. The results indicate an agreement between ECVI and precipitation, and the drought episodes in 2010 and 2011 are resolved by EVCI. With a dataset beyond the three years used for this study it would be possible to correct more accurately for climatology.