Tuesday, 19 July 2011: 11:00 AM
Salon C2 (Asheville Renaissance)
Remote sensing driven evapotranspiration (ET) models are a significant technological improvement to the dynamic management of forests, phreatophytes, rangelands, agricultural water and invasive pests. However, most remote sensing ET models are not available in an Internet-based operational mode. Manually downloading satellite and weather data and processing this data is complicated and time-consuming, requiring as much as 26 hrs per satellite scene. If the ET algorithm is to be used by the scientific community or management agencies and farmers, it is imperative that the computer processing be automated and user-friendly. The user should be able to input the dates and locations of interest and have the model output the ET results (map and ACSII data file). The objective of our research was to test the hypothesis that remote sensing algorithms that calculate daily ET based on the energy balance approach could be automated. An Internet-based ET model combining MODIS satellite images, local weather station data, and forecast data was developed. The automated calculated daily ET was compared to on-site ET, measured by eddy-covariance, under both stressed and non-stressed conditions.
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