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Uncertainties in classification system conversion and an analysis of inconsistencies in global land cover products

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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.
Keywords
multi-resource land cover products, inconsistency, classification system conversion uncertainties, arid region, remote sensing, HEIHE RIVER-BASIN, 1 KM RESOLUTION, SURFACE PARAMETERS, IGBP DISCOVER, CENTRAL-ASIA, DATA SETS, CHINA, DATABASE, CLIMATE, ECOSYSTEMS

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MLA
Zhang, Miao et al. “Uncertainties in Classification System Conversion and an Analysis of Inconsistencies in Global Land Cover Products.” ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 6 (2017): n. pag. Print.
APA
Zhang, M., Ma, M., De Maeyer, P., & Kurban, A. (2017). Uncertainties in classification system conversion and an analysis of inconsistencies in global land cover products. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 6.
Chicago author-date
Zhang, Miao, Mingguo Ma, Philippe De Maeyer, and Alishir Kurban. 2017. “Uncertainties in Classification System Conversion and an Analysis of Inconsistencies in Global Land Cover Products.” Isprs International Journal of Geo-information 6.
Chicago author-date (all authors)
Zhang, Miao, Mingguo Ma, Philippe De Maeyer, and Alishir Kurban. 2017. “Uncertainties in Classification System Conversion and an Analysis of Inconsistencies in Global Land Cover Products.” Isprs International Journal of Geo-information 6.
Vancouver
1.
Zhang M, Ma M, De Maeyer P, Kurban A. Uncertainties in classification system conversion and an analysis of inconsistencies in global land cover products. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION. 2017;6.
IEEE
[1]
M. Zhang, M. Ma, P. De Maeyer, and A. Kurban, “Uncertainties in classification system conversion and an analysis of inconsistencies in global land cover products,” ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, vol. 6, 2017.
@article{8517337,
  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.},
  articleno    = {112},
  author       = {Zhang, Miao and Ma, Mingguo and De Maeyer, Philippe and Kurban, Alishir},
  issn         = {2220-9964},
  journal      = {ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION},
  keywords     = {multi-resource land cover products,inconsistency,classification system conversion uncertainties,arid region,remote sensing,HEIHE RIVER-BASIN,1 KM RESOLUTION,SURFACE PARAMETERS,IGBP DISCOVER,CENTRAL-ASIA,DATA SETS,CHINA,DATABASE,CLIMATE,ECOSYSTEMS},
  language     = {eng},
  pages        = {17},
  title        = {Uncertainties in classification system conversion and an analysis of inconsistencies in global land cover products},
  url          = {http://dx.doi.org/10.3390/ijgi6040112},
  volume       = {6},
  year         = {2017},
}

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