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An approach for establishing correspondence between OpenStreetMap and reference datasets for land use and land cover mapping
Author(s) -
Zhou Qi,
Jia Xuecan,
Lin Hao
Publication year - 2019
Publication title -
transactions in gis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.721
H-Index - 63
eISSN - 1467-9671
pISSN - 1361-1682
DOI - 10.1111/tgis.12581
Subject(s) - polygon (computer graphics) , merge (version control) , land cover , computer science , feature (linguistics) , cohen's kappa , cartography , data mining , cover (algebra) , pattern recognition (psychology) , artificial intelligence , geography , land use , information retrieval , machine learning , engineering , mechanical engineering , telecommunications , linguistics , philosophy , civil engineering , frame (networking)
OpenStreetMap (OSM) provides free source data for land use and land cover (LULC) mapping of many regions globally. Earlier work has used just manual and subjective approaches to establish correspondence between paired OSM and reference datasets, an essential step for LULC mapping. This study proposes an approach to establish correspondence via three steps: (1) convert line feature(s) into polygon feature(s); (2) merge multiple polygon feature(s) into a single layer; and (3) establish correspondence and reclassify OSM and/or reference datasets. Study areas in Sheffield, London, Rome, and Paris were used for testing, and two measures (overall accuracy, OA and kappa index) were used for evaluation. Experiments were designed to verify this approach, with each pair of OSM and reference datasets initially compared after reclassification. Correspondence from one study area was then applied to another for further validation. Results show that OA was between 70 and 90% and the kappa index varied between 0.6 and 0.8. Evaluation also indicates that the correspondence obtained from one study area is applicable to another, and we illustrate the effectiveness of this approach.