Vegetation Indices to Aid Areal Evapotranspiration Estimations

Abstract

Multiyear ͑1982-1990͒ monthly areal evapotranspiration ͑AET͒ was modeled with the Morton approach at the Solar and Meteorological Surface Observation Network stations within the conterminous United States. The AET values were correlated with satellite-derived, monthly maximum-value-composited Normalized Difference Vegetation Indices ͑NDVI͒ at half-degree resolution over the growing season ͑April-October͒. Generally, the strongest monthly correlation was obtained when the NDVI values were related to the AET estimates of the previous month. Geographically, both the monthly and growing-season averaged NDVI-AET relationships were best over the prairie ͑with an rϭ0.66Ϯ0.21 and 0.55Ϯ0.22, and a RMSEϭ26.75Ϯ12.62 and 6.24Ϯ1.67 mm month Ϫ1 , respectively͒ and worst along the coastline and in the most humid, southeast region of the conterminous United States, where the Morton approach may function improperly.

Relationship between evapotranspiration and precipitation pulses in a semiarid rangeland estimated by moisture flux towers and MODIS vegetation indices

“…Similar results were reported for wheat (Hunsaker et al, 2005). In a natural setting, Szilagyi (2000Szilagyi ( , 2002 regressed annual rates of ET, measured over different forested catchments areas in Georgia over multiple years by water balance methods, against time-averaged NDVI values from AVHRR satellite sensors. He obtained an r 2 of 0.88 between ET and NDVI over catchments and years, sufficient to scale ET over larger landscape units within the error term of the ground ET estimates.…”

Annual groundwater evapotranspiration mapped from single satellite scenes

“…Photosynthesis requires leaf conductance for the uptake of carbon dioxide, and during this process water is evaporated to the atmosphere. Because of this chain of related properties, NDVI can be used as a competent surrogate for estimation of both photosynthetic activity (Sellers et al, 1992;Chong et al, 1993); and ET (Kerr et al, 1989;Chong et al, 1993;Kustas et al, 1994;Seevers and Ottmann, 1994;Szilagyi et al, 1998;Szilagyi, 2000Szilagyi, , 2002. As shown by Baugh and Groeneveld (2006) and Groeneveld and Baugh (2007), NDVI provides greatly improved prediction after conversion to NDVI * , a process that removes non-systematic variation.…”

Correcting satellite data to detect vegetation signal for eco-hydrologic analyses

“…1016/j.jhydrol.2007.07.001 large-scale study of hydrology. Calculated from satellite data, normalized difference vegetation index (NDVI) is an indicator of vegetation vigor often used for measurement of environmental response to landscape-scale hydrology, including global climate change (Justice et al, 1998;Running and Nemani, 1991;Stow, 1995), rainfall (Wang et al, 2003;Ji and Peters, 2003) and evapotranspiration (ET) (Kerr et al, 1989;Chong et al, 1993;Kustas et al, 1994;Seevers and Ottmann, 1994;Szilagyi et al, 1998;Szilagyi, 2000Szilagyi, , 2002. Because of the relationship of vegetation vigor to hydrology, ET disposition and water supply, NDVI serves as a surrogate measure of these factors and has direct economic and hydrologic interest at the watershed scale, especially in arid and semi-arid environments.…”