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Open AccessArticle

Exploring the Distribution Patterns of Flickr Photos

by Xuan Ding 1 and Hongchao Fan 2,*
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
Department of Civil and Environmental Engineering, Norwegian University of Science and Technology, 7491 Trondheim, Norway
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2019, 8(9), 418;
Received: 14 August 2019 / Revised: 13 September 2019 / Accepted: 15 September 2019 / Published: 17 September 2019
In recent years, volunteered-geographic-information (VGI) image data have served as a data source for various geographic applications, attracting researchers to assess the quality of these images. However, these applications and quality assessments are generally focused on images associated with geolocation through textual annotations, which is only part of valid images to them. In this paper, we explore the distribution pattern for most relevant VGI images of specific landmarks to extend the current quality analysis, and to provide guidance for improving the data-retrieval process of geographic applications. Distribution is explored in terms of two aspects, namely, semantic distribution and spatial distribution. In this paper, the term semantic distribution is used to describe the matching of building-image tags and content with each other. There are three kinds of images (semantic-relevant and content-relevant, semantic-relevant but content-irrelevant, and semantic-irrelevant but content-relevant). Spatial distribution shows how relevant images are distributed around a landmark. The process of this work can be divided into three parts: data filtering, retrieval of relevant landmark images, and distribution analysis. For semantic distribution, statistical results show that an average of 60% of images tagged with the building’s name actually represents the building, while 69% of images depicting the building are not annotated with the building’s name. There was also an observation that for most landmarks, 97% of relevant building images were located within 300 m around the building in terms of spatial distribution. View Full-Text
Keywords: VGI; Flickr; GIS; data mining; data distribution VGI; Flickr; GIS; data mining; data distribution
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Ding, X.; Fan, H. Exploring the Distribution Patterns of Flickr Photos. ISPRS Int. J. Geo-Inf. 2019, 8, 418.

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