4.5 Article

Volunteered Geographic Videos in Physical Geography: Data Mining from YouTube

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ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
DOI: 10.1080/24694452.2017.1343658

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image processing; structure from motion (SfM); volunteered geographic information (VGI); YouTube

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Volunteered geographic information and citizen science have advanced academic and public understanding of geographical and ecological processes. Videos hosted online represent-a large data source that could potentially provide meaningful results for studies in physical geographya concept we term volunteered geographic videos (VGV). Technological advances in image-capturing devices, computing, and image processing have resulted in increasingly sophisticated methods that treat imagery as raw data, such as resolving high-resolution topography with structure from motion or the calculation of surface flow velocity in rivers with particle image velocimetry. The ubiquitous nature of recording devices and citizens who share imagery online have resulted in a vast archive of potentially useful online videos. This article analyzes the potential for using YouTube videos for research in physical geography. We discuss the combination of suitability and availability that has made this possible and emphasize the distinction between moderately suitable imagery that can directly answer research questions and lower suitability imagery that can indirectly support a study. We present example case studies that address (1) initial considerations of using VGV, (2) topographic data extraction from a video taken after a landslide, and (3) data extraction from a video of a flash flood that could support a study of extreme floods and wood transport. Finally, we discuss both the benefits and complicating factors associated with VGV. The results indicate that VGV could be used to support certain studies in physical geography and that this large repository of raw data has been underutilized.

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