Automatic classification-based generation of thermal infrared land surface emissivity maps using AATSR data over Europe

This is the author’s version of a work that was accepted for publication in Remote Sensing of Environment. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Remote Sensing of Environment, 124, 321-333.DOI :10.1016/j.rse.2012.05.024.The remote sensing measurement of land surface temperature from satellites provides a monitoring of this magnitude on a continuous and regular basis, which is a critical factor in many research fields such as weather forecasting, detection of forest fires or climate change studies, for instance. The main problem of measuring temperature from space is the need to correct for the effects of the atmosphere and the surface emissivity. In this work an automatic procedure based on the Vegetation Cover Method, combined with the GLOBCOVER land surface type classification, is proposed. The algorithm combines this land cover classification with remote sensing information on the vegetation cover fraction to obtain land surface emissivity maps for AATSR split-window bands. The emissivity estimates have been compared with ground measurements in two validation cases in the area of rice fields of Valencia, Spain, and they have also been compared to the classification-based emissivity product provided by MODIS (MOD11_L2). The results show that the error in emissivity of the proposed methodology is of the order of ±0.01 for most of the land surface classes considered, which will contribute to improve the operational land surface temperature measurements provided by the AATSR instrument. © 2012 Elsevier Inc. All rights reserved.This work was funded by the Generalitat Valenciana (project PRO-METEO/2009/086, and contract of Eduardo Caselles) and the Spanish Ministerio de Ciencia e Innovacion (projects CGL2007-64666/CLI, CGL2010-17577/CLI and CGL2007-29819-E, co-financed with FEDER funds). AATSR data were provided by European Space Agency (ESA) under Cat-1 project 3466. We also thank ESA and the ESA GLOBCOVER Project, led by MEDIAS-France, for the GLOBCOVER classification data. The comments and suggestions of three anonymous reviewers that improved the paper are also acknowledged.Caselles, E.; Valor, E.; Abad Cerdá, FJ.; Caselles, V. (2012). Automatic classification-based generation of thermal infrared land surface emissivity maps using AATSR data over Europe. Remote Sensing of Environment. 124:321-333. https://doi.org/10.1016/j.rse.2012.05.02432133312