Journal
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
Volume 44, Issue 7, Pages 1740-1746Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TGRS.2006.874750
Keywords
fuzzy logic; image classification; remote sensing; uncertainty; vegetation mapping
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This paper presents a methodology for the comparison of different land cover datasets and illustrates how this can be extended to create a hybrid land cover product. The datasets used in this paper are the GLC-2000 and MODIS land cover products. The methodology addresses: 1) the harmonization of legend classes from different global land cover datasets and 2) the uncertainty associated with the classification of the images. The first part of the methodology involves mapping the spatial disagreement between the two land cover products using a combination of fuzzy logic and expert knowledge. Hotspots of disagreement between the land cover datasets are then identified to determine areas where other sources of data such as TM/ETM images or detailed regional and national maps can be used in the creation of a hybrid land cover dataset.
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