The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLVIII-4/W1-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4/W1-2022, 537–544, 2022
https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-537-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4/W1-2022, 537–544, 2022
https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-537-2022
 
06 Aug 2022
06 Aug 2022

CREATING A LAND USE/LAND COVER DICTIONARY BASED ON MULTIPLE PAIRS OF OSM AND REFERENCE DATASETS

S. Wang, Q. Zhou, and Y. Liu S. Wang et al.
  • School of Geography and Information Engineering, China University of Geosciences, Wuhan, P.R. China

Keywords: Land Use/Land cover, Mapping, OpenStreetMap, Dictionary, Reference dataset

Abstract. OpenStreetMap (OSM) can supply useful information to improve land use/land cover (LULC) mapping. A dictionary is needed to convert each OSM tag into a LULC class. However, such a dictionary was mostly created subjectively or with only one pair of OSM and reference datasets. As a result, the existing dictionaries may not be applicable to other study areas. This study designed four measures: sample count, average area percentage, sample ratio and average maximum percentage; and used multiple pair of OSM and reference datasets to create a dictionary. 50 pan-European metropolitans were involved for testing and 1409 different OSM tags were found. We further found that: (1) Only a small proportion of OSM tags play a decisive role for LULC mapping. (2) An OSM tag may correspond to multiple different LULC classes, but the issue that which and how different LULC classes correspond to each OSM tag can be determined. Moreover, not only the proposed dictionary is useful for various applications, e.g., producing LULC maps and assessing the quality of an OSM dataset, but also the approach can be applicable to different study areas and/or LULC datasets.