Spanning High and Low Resolution Remote Sensing Products in Precision Agriculture

Document Type


Journal/Book Title/Conference

2016 World Environmental & Water Resources Congress


Environmental & Water Resources Institute


West Palm Beach, FL

Publication Date



"Satellite and airborne technologies for remote sensing show significant promise for monitoring agricultural field conditions. While agricultural parameters can be estimated using data mining techniques and radiometric information from aircraft or satellites, comparison of results from two different aerial platforms can be difficult because of the differences in spatial and temporal scales. Because of this, downscaling of remotely sensed imagery and corresponding agricultural products/information have been a subject of interest in agricultural science. Downscaling involves enhancement of image resolution by appropriately adding details or high frequency features onto a low resolution observation. Of particular significance to precision agriculture is surface soil moisture (SSM), a key component of the soil water balance. This study presents the geospatial properties of raw remote sensing imagery of an agricultural field and the corresponding surface soil moisture products, and downscales the low resolution information to higher resolutions. This is done by ground truthing the data using available high resolution imagery and a modern statistical model based on sparse representation. Data from Landsat 7 ETM+ (Resolution of 30×30m), Landsat 8 OLI (Resolution of 30×30m), and AggieAirTM (an airborne, unmanned remote sensing platform developed by Utah State University) aerial imagery are utilized as low and high resolution imagery sources.

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