Evaluating thermal image sharpening over irrigated crops in a desert environment

Handle URI:
http://hdl.handle.net/10754/620995
Title:
Evaluating thermal image sharpening over irrigated crops in a desert environment
Authors:
Rosas, Jorge; McCabe, M. F. ( 0000-0002-1279-5272 ) ; Houborg, Rasmus; Gao, Feng
Abstract:
Satellite remote sensing provides spatially and temporally distributed data on land surface characteristics, useful for mapping land surface energy fluxes and evapotranspiration (ET). Multi-spectral platforms, including Landsat and the Moderate Resolution Imaging Spectroradiometer (MODIS), acquire imagery in the visible to shortwave infrared and thermal infrared (TIR) domain at resolutions ranging from 30 to 1000 m. Land-surface temperature (LST) derived from TIR satellite data has been reliably used as a remote indicator of ET and surface moisture status. However, TIR imagery usually operates at a coarser resolution than that of shortwave sensors on the same satellite platform, making it sometimes unsuitable for monitoring of field-scale crop conditions. As a result, several techniques for thermal sharpening have been developed. In this study, the data mining sharpener (DMS; Gao et al., 2012) technique is applied over irrigated farming areas located in harsh desert environments in Saudi Arabia. The DMS approach sharpens TIR imagery using finer resolution shortwave spectral reflectances and functional LST and reflectance relationships established using a flexible regression tree approach. In this study, the DMS is applied to Landsat 8 data (100m TIR resolution), which is scaled up to 240m, 480m, and 960m in order to assess the accuracy of the DMS technique in arid irrigated farming environments for different sharpening ratios. Furthermore, the scaling done on Landsat 8 data is consistent with the resolution of MODIS products. Potential enhancements to DMS are investigated including the use of ancillary terrain data. Finally, the impact of using sharpened LST, as input to a two-source energy balance model, on simulated ET will be evaluated. The ability to accurately monitor field-scale changes in vegetation cover, crop conditions and surface fluxes, are of main importance towards an efficient water use in areas where fresh water resources are scarce and poorly monitored.
KAUST Department:
Water Desalination & Reuse Research Cntr
Conference/Event name:
The 4th International Symposium on Recent Advances in Quantitative Remote Sensing: RAQRS'IV
Issue Date:
Sep-2014
Type:
Poster
Additional Links:
http://ipl.uv.es/raqrs/RAQRS_2014_Programme_and_Abstract_book.pdf
Appears in Collections:
Posters

Full metadata record

DC FieldValue Language
dc.contributor.authorRosas, Jorgeen
dc.contributor.authorMcCabe, M. F.en
dc.contributor.authorHouborg, Rasmusen
dc.contributor.authorGao, Fengen
dc.date.accessioned2016-10-13T12:05:33Z-
dc.date.available2016-10-13T12:05:33Z-
dc.date.issued2014-09-
dc.identifier.urihttp://hdl.handle.net/10754/620995-
dc.description.abstractSatellite remote sensing provides spatially and temporally distributed data on land surface characteristics, useful for mapping land surface energy fluxes and evapotranspiration (ET). Multi-spectral platforms, including Landsat and the Moderate Resolution Imaging Spectroradiometer (MODIS), acquire imagery in the visible to shortwave infrared and thermal infrared (TIR) domain at resolutions ranging from 30 to 1000 m. Land-surface temperature (LST) derived from TIR satellite data has been reliably used as a remote indicator of ET and surface moisture status. However, TIR imagery usually operates at a coarser resolution than that of shortwave sensors on the same satellite platform, making it sometimes unsuitable for monitoring of field-scale crop conditions. As a result, several techniques for thermal sharpening have been developed. In this study, the data mining sharpener (DMS; Gao et al., 2012) technique is applied over irrigated farming areas located in harsh desert environments in Saudi Arabia. The DMS approach sharpens TIR imagery using finer resolution shortwave spectral reflectances and functional LST and reflectance relationships established using a flexible regression tree approach. In this study, the DMS is applied to Landsat 8 data (100m TIR resolution), which is scaled up to 240m, 480m, and 960m in order to assess the accuracy of the DMS technique in arid irrigated farming environments for different sharpening ratios. Furthermore, the scaling done on Landsat 8 data is consistent with the resolution of MODIS products. Potential enhancements to DMS are investigated including the use of ancillary terrain data. Finally, the impact of using sharpened LST, as input to a two-source energy balance model, on simulated ET will be evaluated. The ability to accurately monitor field-scale changes in vegetation cover, crop conditions and surface fluxes, are of main importance towards an efficient water use in areas where fresh water resources are scarce and poorly monitored.en
dc.relation.urlhttp://ipl.uv.es/raqrs/RAQRS_2014_Programme_and_Abstract_book.pdfen
dc.titleEvaluating thermal image sharpening over irrigated crops in a desert environmenten
dc.typePosteren
dc.contributor.departmentWater Desalination & Reuse Research Cntren
dc.conference.date22-26th September 2014en
dc.conference.nameThe 4th International Symposium on Recent Advances in Quantitative Remote Sensing: RAQRS'IVen
dc.conference.locationTorrent (Valencia), Spainen
dc.contributor.institutionUSDA-ARS, Hydrology and Remote Sensing Laboratoryen
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