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Verfasst von:Kuo, Chiao-Ling [VerfasserIn]   i
 Zipf, Alexander [VerfasserIn]   i
Titel:Efficient method for POI/ROI discovery using flickr geotagged photos
Verf.angabe:by Chiao-Ling Kuo, Ta-Chien Chan, I.-Chun Fan, and Alexander Zipf
E-Jahr:2018
Jahr:16 March 2018
Umfang:19 S.
Fussnoten:Gesehen am 13.11.2019
Titel Quelle:Enthalten in: International Society for Photogrammetry and Remote SensingISPRS International Journal of Geo-Information
Ort Quelle:Basel : MDPI, 2012
Jahr Quelle:2018
Band/Heft Quelle:7(2018,3) Artikel-Nummer 121, 19 Seiten
ISSN Quelle:2220-9964
Abstract:In the era of big data, ubiquitous Flickr geotagged photos have opened a considerable opportunity for discovering valuable geographic information. Point of interest (POI) and region of interest (ROI) are significant reference data that are widely used in geospatial applications. This study aims to develop an efficient method for POI/ROI discovery from Flickr. Attractive footprints in photos with a local maximum that is beneficial for distinguishing clusters are first exploited. Pattern discovery is combined with a novel algorithm, the spatial overlap (SO) algorithm, and the naming and merging method is conducted for attractive footprint clustering. POI and ROI, which are derived from the peak value and range of clusters, indicate the most popular location and range for appreciating attractions. The discovered ROIs have a particular spatial overlap available which means the satisfied region of ROIs can be shared for appreciating attractions. The developed method is demonstrated in two study areas in Taiwan: Tainan and Taipei, which are the oldest and densest cities, respectively. Results show that the discovered POI/ROIs nearly match the official data in Tainan, whereas more commercial POI/ROIs are discovered in Taipei by the algorithm than official data. Meanwhile, our method can address the clustering issue in a dense area.
DOI:doi:10.3390/ijgi7030121
URL:Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.

Volltext: https://doi.org/10.3390/ijgi7030121
 Verlag: https://www.mdpi.com/2220-9964/7/3/121
 DOI: https://doi.org/10.3390/ijgi7030121
Datenträger:Online-Ressource
Sprache:eng
Sach-SW:Flickr geotagged photo
 pattern discovery
 point of interest (POI)
 region of interest (ROI)
 spatial overlap algorithm
K10plus-PPN:1681764970
Verknüpfungen:→ Zeitschrift

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