Evaluating the use of sharpened land surface temperature for daily evapotranspiration estimation over irrigated crops in arid lands

Handle URI:
http://hdl.handle.net/10754/620996
Title:
Evaluating the use of sharpened land surface temperature for daily evapotranspiration estimation over irrigated crops in arid lands
Authors:
Rosas, Jorge; McCabe, M. F. ( 0000-0002-1279-5272 ) ; Houborg, Rasmus; Gao, Feng
Abstract:
Satellite remote sensing provides data on land surface characteristics, useful for mapping land surface energy fluxes and evapotranspiration (ET). Land-surface temperature (LST) derived from thermal infrared (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. This study applies the data mining sharpener (DMS; Gao et al., 2012) technique to data from the Moderate Resolution Imaging Spectroradiometer (MODIS), which sharpens the 1 km thermal data down to the resolution of the optical data (250-500 m) based on functional LST and reflectance relationships established using a flexible regression tree approach. The DMS approach adopted here has been enhanced/refined for application over irrigated farming areas located in harsh desert environments in Saudi Arabia. The sharpened LST data is input to an integrated modeling system that uses the Atmosphere-Land Exchange Inverse (ALEXI) model and associated flux disaggregation scheme (DisALEXI) in conjunction with model reanalysis data and remotely sensed data from polar orbiting (MODIS) and geostationary (MSG; Meteosat Second Generation) satellite platforms to facilitate daily estimates of evapotranspiration. Results are evaluated against available flux tower observations over irrigated maize near Riyadh in Saudi Arabia. Successful monitoring of field-scale changes in surface fluxes are of importance towards an efficient water use in areas where fresh water resources are scarce and poorly monitored. Gao, F.; Kustas, W.P.; Anderson, M.C. A Data Mining Approach for Sharpening Thermal Satellite Imagery over Land. Remote Sens. 2012, 4, 3287-3319.
KAUST Department:
Water Desalination & Reuse Research Cntr
Conference/Event name:
American Geophysical Union Fall Meeting
Issue Date:
Dec-2014
Type:
Poster
Additional Links:
http://adsabs.harvard.edu/abs/2014AGUFM.H43C0974R
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.accessioned2016-10-13T12:13:04Z-
dc.date.available2016-10-13T12:13:04Z-
dc.date.issued2014-12-
dc.identifier.urihttp://hdl.handle.net/10754/620996-
dc.description.abstractSatellite remote sensing provides data on land surface characteristics, useful for mapping land surface energy fluxes and evapotranspiration (ET). Land-surface temperature (LST) derived from thermal infrared (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. This study applies the data mining sharpener (DMS; Gao et al., 2012) technique to data from the Moderate Resolution Imaging Spectroradiometer (MODIS), which sharpens the 1 km thermal data down to the resolution of the optical data (250-500 m) based on functional LST and reflectance relationships established using a flexible regression tree approach. The DMS approach adopted here has been enhanced/refined for application over irrigated farming areas located in harsh desert environments in Saudi Arabia. The sharpened LST data is input to an integrated modeling system that uses the Atmosphere-Land Exchange Inverse (ALEXI) model and associated flux disaggregation scheme (DisALEXI) in conjunction with model reanalysis data and remotely sensed data from polar orbiting (MODIS) and geostationary (MSG; Meteosat Second Generation) satellite platforms to facilitate daily estimates of evapotranspiration. Results are evaluated against available flux tower observations over irrigated maize near Riyadh in Saudi Arabia. Successful monitoring of field-scale changes in surface fluxes are of importance towards an efficient water use in areas where fresh water resources are scarce and poorly monitored. Gao, F.; Kustas, W.P.; Anderson, M.C. A Data Mining Approach for Sharpening Thermal Satellite Imagery over Land. Remote Sens. 2012, 4, 3287-3319.en
dc.relation.urlhttp://adsabs.harvard.edu/abs/2014AGUFM.H43C0974Ren
dc.titleEvaluating the use of sharpened land surface temperature for daily evapotranspiration estimation over irrigated crops in arid landsen
dc.typePosteren
dc.contributor.departmentWater Desalination & Reuse Research Cntren
dc.conference.dateDecember 15 to December 19, 2014en
dc.conference.nameAmerican Geophysical Union Fall Meetingen
dc.conference.locationSan Francisco, Californiaen
dc.contributor.institutionUSDA-ARS, Hydrology and Remote Sensing Laboratoryen
All Items in KAUST are protected by copyright, with all rights reserved, unless otherwise indicated.