Unmixing-based Landsat TM and MERIS FR data fusion

R. Zurita Milla, J.G.P.W. Clevers, M.E. Schaepman

Research output: Contribution to journalArticleAcademicpeer-review

123 Citations (Scopus)

Abstract

An unmixing-based data fusion technique is used to generate images that have the spatial resolution of Landsat Thematic Mapper (TM) and the spectral resolution provided by the Medium Resolution Imaging Spectrometer (MERIS) sensor. The method requires the optimization of the following two parameters: the number of classes used to classify the TM image and the size of the MERIS ¿window¿ (neighborhood) used to solve the unmixing equations. The ERGAS index is used to assess the quality of the fused images at the TM and MERIS spatial resolutions and to assist with the identification of the best combination of the two parameters that need to be optimized. Results indicate that it is possible to successfully downscale MERIS full resolution data to a Landsat-like spatial resolution while preserving the MERIS spectral resolution.
Original languageEnglish
Pages (from-to)453-457
JournalIEEE Geoscience and Remote Sensing Letters
Volume5
Issue number3
DOIs
Publication statusPublished - 2008

Keywords

  • spatial-resolution improvement
  • multisensor image fusion
  • radiometric calibration
  • quality

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