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Relative semantics include spatial and visual semantics. However, most navigation data models are based on an absolute reference frame and do not support the organization of relative semantics. To address this deficiency, we propose a pedestrian navigation data model based on relative semantic images that organizes the relative semantics of landmarks and environments directly in the image channels. Using geographic data for a university campus, we compared the data file size, data access time, and memory usage to confirm that the proposed approach outperforms the geodatabase approach in storing and accessing the relative semantic data. Two examples, self\u2010localization and route guidance, demonstrate the feasibility of the proposed data model. This model can support fast pedestrian navigation on mobile devices in small and medium\u2010sized areas.<\/jats:p>","DOI":"10.1111\/tgis.12669","type":"journal-article","created":{"date-parts":[[2020,8,3]],"date-time":"2020-08-03T13:46:05Z","timestamp":1596462365000},"page":"1655-1680","update-policy":"http:\/\/dx.doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["A data model for organizing relative semantics as images to support pedestrian navigation computations"],"prefix":"10.1111","volume":"24","author":[{"ORCID":"http:\/\/orcid.org\/0000-0003-1651-878X","authenticated-orcid":false,"given":"Zhixiang","family":"Fang","sequence":"first","affiliation":[{"name":"State Key Laboratory for Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan China"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-9591-7748","authenticated-orcid":false,"given":"Fan","family":"Yang","sequence":"additional","affiliation":[{"name":"State 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