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Mapping Total Vegetation Cover Across Western Rangelands With Moderate-Resolution Imaging Spectroradiometer Data
Authors:Stephen C Hagen  Philip Heilman  Robert Marsett  Nathan Torbick  William Salas  Jenni van Ravensway  Jiaguo Qi
Institution:1. Senior Research Scientist, Applied GeoSolutions, LLC, Durham, NH 03824, USA;4. President and Chief Scientist, Applied GeoSolutions, LLC, Durham, NH 03824, USA;2. Research Leader, USDA-ARS, SWRC, Tucson, AZ, 85719 USA;3. Owner, Ranges, LLC, Tucson, AZ, 85749 USA;5. Research Associate, Michigan State University, East Lansing, MI, 48824 USA;6. Director, Center for Global Change and Earth Observations ,Michigan State University, East Lansing, MI, 48824 USA;7. Professor, Department of Geography, Michigan State University, East Lansing, MI, 48824 USA
Abstract:Remotely sensed observations of rangelands provide a synoptic view of vegetation condition unavailable from other means. Multiple satellite platforms in operation today (e.g. Landsat, moderate-resolution imaging spectroradiometer MODIS]) offer opportunities for regional monitoring of rangelands. However, the spatial and temporal variability of rangelands pose challenges to consistent and accurate mapping of vegetation condition. For instance, soil properties can have a large impact on the reflectance registered at the satellite sensor. Additionally, senescent vegetation, which is often abundant on rangeland, is dynamic and its physical and photochemical properties can change rapidly along with moisture availability. Remote sensing has been successfully used to map local rangeland conditions. However, regional and frequently updated maps of vegetation cover in rangelands are not currently available. In this research, we compare ground measurements of total vegetation cover, including both green and senescent cover, to reflectance observed by the satellite and develop a robust method for estimating total vegetation canopy cover over diverse regions of the western United States. We test the effects of scaling from ground observations up to the Landsat 30-m scale, then to the MODIS 500-m scale, and quantify sources of noise. The soil-adjusted total vegetation index (SATVI) captures 55% of the variability in ground measured total vegetation cover from diverse sites in New Mexico, Arizona, Wyoming, and Nevada. Scaling from the Landsat to MODIS scale introduces noise and loss of spatial detail, but offers inexpensive and frequent observations and the ability to track trends in cover over large regions.
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