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The Annual International Conference on Geographic Information Science

GIScience 2016: Geographic Information Science pp 130–144Cite as

Representing the Spatial Extent of Places Based on Flickr Photos with a Representativeness-Weighted Kernel Density Estimation

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9927))

Abstract

Geotagged photos have been applied by many researchers to explore the spatial extent of places. This paper addresses an important challenge of using geotagged Flickr photos to delineate the spatial extent of a vague place, which is defined as a place without a clearly defined boundary. We argue that the variation of location popularity has a great impact on the estimation of such vague spatial extent of a place. We propose an approach to model the representativeness of each geotagged photo point based on its location popularity. A modified kernel density estimation method incorporating the photo representativeness is developed and tested with eight places, which cover urban vs. non-urban areas, with vs. without an official boundary cases, and at various spatial scales of state, city and district levels. Our results indicate major improvements of the proposed representativeness-weighted kernel density estimation method over the traditional kernel density estimation method in estimating the spatial extent of vague places.

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Notes

  1. 1.

    Data source: https://www.flickr.com/services/api/, also the data source of this paper.

  2. 2.

    https://www.census.gov/cgi-bin/geo/shapefiles/index.php.

  3. 3.

    https://www.nps.gov/.

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Authors and Affiliations

  1. Department of Geography, University of Tennessee, Knoxville, TN, 37996, USA

    Jiaoli Chen & Shih-Lung Shaw

Authors
  1. Jiaoli Chen
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  2. Shih-Lung Shaw
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Correspondence to Shih-Lung Shaw .

Editor information

Editors and Affiliations

  1. University of Texas at Austin , Austin, Texas, USA

    Jennifer A. Miller

  2. University of California at Berkeley , Berkeley, California, USA

    David O'Sullivan

  3. University of Wisconsin-Madison , Madison, Wisconsin, USA

    Nancy Wiegand

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Chen, J., Shaw, SL. (2016). Representing the Spatial Extent of Places Based on Flickr Photos with a Representativeness-Weighted Kernel Density Estimation. In: Miller, J., O'Sullivan, D., Wiegand, N. (eds) Geographic Information Science. GIScience 2016. Lecture Notes in Computer Science(), vol 9927. Springer, Cham. https://doi.org/10.1007/978-3-319-45738-3_9

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  • DOI: https://doi.org/10.1007/978-3-319-45738-3_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-45737-6

  • Online ISBN: 978-3-319-45738-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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