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ISPRS Int. J. Geo-Inf. 2017, 6(3), 72; doi:10.3390/ijgi6030072

Salience Indicators for Landmark Extraction at Large Spatial Scales Based on Spatial Analysis Methods

School of Recource and Environmental Science, Wuhan University, 120 Luoyu Road, Wuhan 430079, China
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Academic Editors: Georg Gartner, Haosheng Huang and Wolfgang Kainz
Received: 3 January 2017 / Revised: 25 February 2017 / Accepted: 1 March 2017 / Published: 4 March 2017
(This article belongs to the Special Issue Location-Based Services)
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Abstract

Urban landmarks are frequently used in way-finding and representations of spatial knowledge. However, assessing the salience of urban landmarks is difficult. Moreover, no method exists to rapidly extract urban landmarks from basic geographic information databases. The goal of this paper is to solve these problems from the dual aspects of spatial knowledge representation and public spatial cognition rules. A clear and systematic definition for multiple-scale urban landmarks is proposed, together with a category reference for extracting small- and medium-scale urban landmarks and a model for the large-scale automatic extraction of urban landmarks. In this large-scale automatic urban landmark extraction model, the salience is expressed by two weighted parameters: the check-in totals and local accessibility. The extraction threshold is set according to a predefined number of landmarks to be extracted. Experiments show that the extraction results match the reference data well. View Full-Text
Keywords: urban landmark extraction; address description; spatial cognition; spatial context; scale effect of cognition urban landmark extraction; address description; spatial cognition; spatial context; scale effect of cognition
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Weng, M.; Xiong, Q.; Kang, M. Salience Indicators for Landmark Extraction at Large Spatial Scales Based on Spatial Analysis Methods. ISPRS Int. J. Geo-Inf. 2017, 6, 72.

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