An evaluation of crowdsourced information for assessing the visitation and perceived importance of protected areas. (February 2017)

• Record Type: Journal Article
• Authors: Levin, Noam; Lechner, Alex Mark; Brown, Greg
• Is Part Of: Applied geography. Volume 79(2017:May)
• Page Start: 115
• Page End: 126
• Publication Date: 2017-02
• Subjects: Flickr -- OpenStreetMap -- Place values -- Public participation GIS (PPGIS) -- Volunteered geographic information (VGI) -- Wikipedia; Geography -- Periodicals; Human geography -- Periodicals; Human ecology -- Periodicals; 910
• DOI: 10.1016/j.apgeog.2016.12.009
• Languages: English
• ISSNs: 0143-6228

Abstract

Abstract: Parks and protected areas provide a wide range of benefits, but methods to evaluate their importance to society are often ad hoc and limited. In this study, the quality of crowdsourced information from Public Participation GIS (PPGIS) and Volunteered Geographic Information (VGI) sources (Flickr, OpenStreetMap (OSM), and Wikipedia) was compared with visitor counts that are presumed to reflect social importance. Using the state of Victoria, Australia as a case study, secondary crowdsourced VGI data, primary crowdsourced (PPGIS data) and visitor statistics were examined for their correspondence and differences, and to identify spatial patterns in park popularity. Data completeness—the percent of protected areas with data—varied between sources, being highest for OSM (90%), followed by Flickr (41%), PPGIS (24%), visitation counts (5%), and Wikipedia articles (4%). Statistically significant correlations were found between all five measures of popularity for protected areas. Using stepwise multiple linear regression, the explained variability in visitor numbers was greater than 70%, with PPGIS, Flickr and OSM having the largest standardized coefficients. The social importance of protected areas varied as a function of accessibility and the types of values (direct or indirect use) expressed for the areas. Crowdsourced data may provide an alternative to visitor counts for assessing protected area social importance and spatial variability of visitation. However, crowdsourced data appears to be an unreliable proxy for the full range of values and importance of protected areas, especially for non-use values such as biological conservation. Highlights: Examines potential of crowdsourced data for assessing protected area importance. Compares and evaluates multiple crowdsourced data with protected area visitor counts. Found significant correlations between crowdsourced data and protected area visitation. PPGIS methods better suited than VGI to assess full range of protected area values. Data completeness limits crowdsourced applications to more popular protected areas.