Utility of Thermal Sharpening Over Texas High Plains Irrigated Agricultural Fields

Authors: AGAM, NURIT - 1265-06-00; Kustas, William - Bill; Anderson, Martha; Li, Fuqin; COLAIZZI, PAUL - 1265-06-00

Submitted to: Journal of Geophysical Research Atmospheres
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/1/2007
Publication Date: 11/5/2007
Citation: Agam, N., Kustas, W.P., Anderson, M.C., Li, F., Colaizzi, P.D. 2007. Utility of thermal sharpening over Texas high plains irrigated agricultural fields. Journal of Geophysical Research Atmospheres. 112(D19110). http:/dx.doi.org/10.1029/2007JD008407.

Interpretive Summary: Irrigated crop production in the Texas High Plains (THP) is dependent on water extracted from the Ogallala Aquifer, an area suffering from sever water shortage. Water management in this area is therefore highly important. Thermal satellite imagery at high-temporal (~daily) and high-spatial (~100 m) resolutions provide important surface boundary conditions for vegetation stress and water use monitoring, mainly through energy-balance models such as DisALEXI. At present, however, no satellite platform collects such high spatiotemporal resolution data. The objective of this study is to examine the utility of an image sharpening technique (TsHARP) for retrieving land-surface temperature at high spatial resolution from low spatial resolution imagery at this irrigated agricultural area. TsHARP was applied to Landsat 7 imagery collected over the THP to examine its utility over both agricultural and natural vegetation cover. The algorithm did not provide any measurable improvement in estimating high-resolution temperature distributions over natural land-cover. In contrast, TsHARP was shown to retrieve high-resolution temperature information with good accuracy over much of the agricultural area within the scene. However, in recently irrigated fields, TsHARP could not reproduce the temperature patterns. Therefore we conclude that TsHARP is not an adequate substitute for 100-m scale observations afforded by the current Landsat platforms. Should the thermal imager be removed from the LDCM, we will lose valuable capacity to monitor water use at the field-scale, particularly in many agricultural regions where the typical field size is ~100 x 100 m. In this unfortunate scenario, TsHARP could serve as a second-best alternative.

Technical Abstract: Irrigated crop production in the Texas High Plains (THP) is dependent on water extracted from the Ogallala Aquifer, an area suffering from sever water shortage. Water management in this area is therefore highly important. Thermal satellite imagery at high-temporal (~daily) and high-spatial (~100 m) resolutions provide important surface boundary conditions for vegetation stress and water use monitoring, mainly through energy-balance models such as DisALEXI. At present, however, no satellite platform collects such high spatiotemporal resolution data. The objective of this study is to examine the utility of an image sharpening technique (TsHARP) for retrieving land-surface temperature at high spatial resolution from low spatial resolution imagery at this irrigated agricultural area. TsHARP was applied to Landsat 7 imagery collected over the THP to examine its utility over both agricultural and natural vegetation cover. The algorithm did not provide any measurable improvement in estimating high-resolution temperature distributions over natural land-cover. In contrast, TsHARP was shown to retrieve high-resolution temperature information with good accuracy over much of the agricultural area within the scene. However, in recently irrigated fields, TsHARP could not reproduce the temperature patterns. Therefore we conclude that TsHARP is not an adequate substitute for 100-m scale observations afforded by the current Landsat platforms. Should the thermal imager be removed from the LDCM, we will lose valuable capacity to monitor water use at the field-scale, particularly in many agricultural regions where the typical field size is ~100 x 100 m. In this unfortunate scenario, TsHARP could serve as a second-best alternative.