|Holifield Collins, Chandra|
Submitted to: Canadian Journal of Remote Sensing
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/23/2002
Publication Date: 1/1/2003
Citation: Holifield Collins, C.D., Mcelroy, S., Moran, M.S., Bryant, R., Miura, T., Emmerich, W.E. 2003. Temporal and spatial changes in grassland transpiration detected using landsat and etm+ imagery. Can. J. Rem. Sens. 29(2):259-270.
Interpretive Summary: Grasslands compose a substantial portion of the world¿s rangeland ecosystem 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, the 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, as well as differences in transpiration caused by topography, 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, which estimates relative evapotranspiration rates based on meteorological data and the relation between surface reflectance and temperature, has been successfully applied over heterogeneous terrain with little apriori information. In this study, WDI was derived from a ten-year, Landsat-4 Thematic Mapper (TM), Landsat-5 TM and Landsat-7 Enhanced TM Plus (ETM+) data series of the Walnut Gulch Experimental Watershed in Arizona during the summer monsoon period. Our study showed that measurements of surface reflectance and temperature from the three sensors could be combined without sacrificing product accuracy. Results also showed that the WDI was sensitive to both temporal and spatial changes in plant transpiration, as well as differences in transpiration caused by topography. WDI was compared with a measure of plant available soil moisture (the Antecedent Retention Index, ARI), which was derived from an hourly record of precipitation and runoff, obtained from rain gauges and flumes located in the watershed. Results showed that a non-linear relation between WDI and ARI was significant but weak (R2=0.45), and implied that WDI was the more sensitive indicator of vegetation health. Ultimately, the WDI approach may be used as a viable tool to monitor grassland health over heterogeneous regions.