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ARS Home » Pacific West Area » Tucson, Arizona » SWRC » Research » Publications at this Location » Publication #134860


item Holifield Collins, Chandra
item MCELROY, S.
item Moran, Mary
item BRYANT, R.
item MIURA, T.
item GAO, X.
item HUETE, A.

Submitted to: International Society Remote Sensing of Environment
Publication Type: Proceedings
Publication Acceptance Date: 7/13/2002
Publication Date: 10/11/2002
Citation: Holifield, C.D., Mcelroy, S., Moran, M.S., Bryant, R., Miura, T., Gao, X., Huete, A. 2002. Temporal and spatial changes in grassland transpiration detected using landsat imagery. International Society Remote Sensing of Environment. p. 495-497.

Interpretive Summary: A substantial portion of the world¿s rangeland ecosystm is comoposed of grasslands and are a significant food source for wild and domestic animals. If land managers are going to make effective management plans toward attaining sustainable rangelands, it is necessary to have a means of monitoring plant health. Photosynthesis is an indicator of plant health, but is very difficult to measure on a large scale. However, transpiration, loss of water by plant leaves, can be used as an indicator of plant health due to its link with photosynthesis. The Water Deficit Index (WDI), derived from Landsat satellite imagery, can provide an estimate of transpiration over an area spanning thousands of acres. In this study, the WDI derived from continuous Landsat-4, -5, and ¿7 imagery over an 11-year period was used to detect changes in space and time in grassland transpiration. The study showed that the WDI was sensitive to both temporal and spatial changes in plant transpiration, over an area of 2,224 acres in southeastern Arizona. The WDI was shown to have great promise as a viable tool for monitoring relative plant health on grasslands/rangelands.

Technical Abstract: The Water Deficit Index (WDI) derived from Landsat imagery was used to detect temporal and spatial changes in grassland transpiration. The WDI approach to estimating evapotranspiration is based on the relation between surface reflectance and temperature and driven by meteorological data, and has been successfully applied over heterogeneous terrain with little apriori information. The WDI information was derived from a 10-year, Landsat-4, -5, -7 data series taken of the Walnut Gulch Experimental Watershed in Arizona during the summer monsoon period. Transpiration estimated by the WDI was compared with precipitation data obtained from rain gauge instrumentation located in the watershed. Results from this study showed that the WDI was able to detect temporal and spatial changes in transpiration, as well as differences in transpiration caused by topography. Ultimately, the WDI approach may be used as a viable tool to measure plant health over heterogeneous regions