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item Li, Fuqin
item Jackson, Thomas
item Kustas, William - Bill
item Schmugge, Thomas
item FRENCH, A
item Cosh, Michael

Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/18/2004
Publication Date: 9/30/2004
Citation: Li, F., Jackson, T.J., Kustas, W.P., Schmugge, T.J., French, A., Cosh, M.H., Bindlish, R. 2004. Deriving land surface temperature from Landsat 5 and 7 during SMEX02/SMACEX. Remote Sensing of Environment. 92(2):521-534.

Interpretive Summary: Landsat satellite thermal infrared images collected during the Soil Moisture Experiments in 2002 over central Iowa croplands were used in conjunction with ground based and other satellite observations to understand the scaling of derived land surface temperatures. Land surface temperature Ts, is a key boundary condition in many remote sensing-based land surface modeling schemes. The thermal infrared sensors from various satellites platforms provide different spatial resolution data to estimate land surface temperature. The findings from this investigation show that it is possible to extract accurate land surface temperature of about 1o K from Landsat Thematic Mapper data with a radiative transfer model, on site radiosonde data, and an emissivity algorithm. From these results we conclude that with adequate ancillary information and atmospheric correction, the high resolution satellite data can be used to extract detailed information about vegetation cover and surface temperature. These are both important surface boundary conditions for modeling surface fluxes. It is possible that different types of satellite data can be used synergistically. Higher resolution and less frequent thermal infrared observations from Landsat can be used to understand the spatial variation within coarser resolution observations made by other satellites, which provide more frequent measurements. This spatial information is important in estimating energy balance components, which utilizes temperature measurements; because it is known that (unlike the measured radiance) the fluxes do not exhibit linear scaling. This information can be used to assess crop conditions within fields and the impacts of land cover and land use changes on surface energy balance.

Technical Abstract: A sequence of five high resolution satellite based land surface temperature images over a watershed area in Iowa were analyzed. As a part of the SMEX02 field experiment, these land surface temperature images were extracted from Landsat 5 TM and Landsat 7 ETM thermal bands. The radiative transfer model MODTRAN 4.1 was used with atmospheric profile data to atmospherically correct the Landsat data. NDVI derived from Landsat visible and near-infrared bands was used to estimate fractional vegetation cover, which in turn was used to estimate emissivity for Landsat thermal bands. The estimated brightness temperature was compared with concurrent tower based measurements. The difference between the satellite based brightness temperature estimates and the tower based brightness temperature was 0.98o C for Landsat 7 and 1.47ºC for Landsat 5 respectively. Based on these images, the land surface temperature spatial variation and its change with scale are addressed. The scaling properties of the surface temperature is important as it has significant implications for changes in land surface fluxes estimation between higher resolution Landsat and regional to global sensors such as MODIS.