Abstract
Monitoring Land Surface Temperature (LST) from satellite remote sensing requires an accurate correction of the atmospheric effects. Although thermal remote sensing techniques have advanced significantly over the past few decades, to date, single-band pixel-by-pixel atmospheric correction of full thermal images is unsolved. In this work, we introduce a new Single-Band Atmospheric Correction (SBAC) tool that provides pixel-by-pixel atmospheric correction parameters regardless of the pixel size. The SBAC tool uses National Centers of Environmental Prediction (NCEP) profiles as inputs and, as a novelty, it also accounts for pixel elevation through a Digital Elevation Model (DEM). Application of SBAC to 19 Landsat 7-ETM+ scenes shows the potential of the proposed pixel-by-pixel atmospheric correction to capture terrain orography or atmospheric variability within the scene. LST estimation yields negligible bias and an RMSE of ±1.6 K for the full dataset. The Landsat Atmospheric Correction Tool (ACT) is also considered for comparison. SBAC-ACT LST deviations are analyzed in terms of distance to the image center, surface elevation, and spatial distribution of the atmospheric water content. Differences within 3 K are observed. These results give us the first insight of the potential of SBAC for the operational pixel-by-pixel atmospheric correction of full thermal images. The SBAC tool is expected to help users of satellite single-channel thermal sensors to improve their LST estimates due to its simplicity and robustness.
Highlights
Land Surface Temperature (LST) is a key magnitude in the characterization of the surface-atmosphere energy exchanges, evapotranspiration, meteorology, climatology and hydrology [1,2,3,4,5,6]
We introduce a new Single-Band Atmospheric Correction (SBAC) tool that provides pixel-by-pixel atmospheric correction parameters regardless of the pixel size
We focus on the application of SBAC to L7-ETM+ sensor, extension to other single channel sensors is automatic and will be explored in further works
Summary
Land Surface Temperature (LST) is a key magnitude in the characterization of the surface-atmosphere energy exchanges, evapotranspiration, meteorology, climatology and hydrology [1,2,3,4,5,6]. Split-window methods apply to those sensors provided by at least two spectral channels, usually at 11 and 12 × μm. This has been the correction method traditionally applied to NOAA/Advanced Very High Resolution Radiometer (NOAA/AVHRR, [11,12,13,14]), EOS Terra-Aqua/Moderate Resolution Image Spectroradiometer (EOS/MODIS, [15,16,17]), Envisat/Advanced Along Track Scanning Radiometer (Envisat/AATSR, [17,18]) or the Meteosat Second Generation/Spinning Enhanced Visible and Infrared Imager (MSG/SEVIRI, [19,20,21]) or Suomi National Polar-Orbiting Partnership/Visible Infrared Imaging Radiometer Suite (s-NPP/VIIRS, [22,23]). LST products of MODIS (MOD21) and s-NPP/VIIRS are based on TES technique [26,27]
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