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Uncertainties in Classification System Conversion and an Analysis of Inconsistencies in Global Land Cover Products


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State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Science, No. 818 South Beijing Road, Urumqi 830011, China

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Department of Geography, Gent University, Krijgslaan 281, Ghent B-9000, Belgium

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University of the Chinese Academy of Sciences, Beijing 100049, China

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Sino-Belgian Joint Laboratory for Geo-information, Xinjiang Institute of Ecology and Geography and Gent University, Urumqi 830011, China

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Sino-Belgian Joint Laboratory for Geo-information, Ghent University, Gent B-9000, Belgium

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Chongqing Key Laboratory of Karst Environment, School of Geographical Sciences, Southwest University, Beibei, Chongqing 400715, China





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Author to whom correspondence should be addressed.



Academic Editor: Wolfgang Kainz

Abstract In this study, using the common classification systems of IGBP-17, IGBP-9, IPCC-5 and TC vegetation, wetlands and others only, we studied spatial and areal inconsistencies in the three most recent multi-resource land cover products in a complex mountain-oasis-desert system and quantitatively discussed the uncertainties in classification system conversion. This is the first study to compare these products based on terrain and to quantitatively study the uncertainties in classification system conversion. The inconsistencies and uncertainties decreased from high to low levels of aggregation IGBP-17 to TC and from mountain to desert areas, indicating that the inconsistencies are not only influenced by the level of thematic detail and landscape complexity but also related to the conversion uncertainties. The overall areal inconsistency in the comparison of the FROM-GLC and GlobCover 2009 datasets is the smallest among the three pairs, but the smallest overall spatial inconsistency was observed between the FROM-GLC and MODISLC. The GlobCover 2009 had the largest conversion uncertainties due to mosaic land cover definition, with values up to 23.9%, 9.68% and 0.11% in mountainous, oasis and desert areas, respectively. The FROM-GLC had the smallest inconsistency, with values less than 4.58%, 1.89% and 1.2% in corresponding areas. Because the FROM-GLC dataset uses a hierarchical classification scheme with explicit attribution from the second level to the first, this system is suggested for producers of map land cover products in the future. View Full-Text

Keywords: multi-resource land cover products; inconsistency; classification system conversion uncertainties; arid region; remote sensing multi-resource land cover products; inconsistency; classification system conversion uncertainties; arid region; remote sensing





Autor: Miao Zhang 1,2,3,4,5, Mingguo Ma 1,6,* , Philippe De Maeyer 2,4,5 and Alishir Kurban 1,4,5

Fuente: http://mdpi.com/



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