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Spatial and Temporal Patterns in Volunteer Data Contribution Activities: A Case Study of eBird

Department of Geography and the Environment, College of Natural Sciences and Mathematics, University of Denver, CO 80208, USA
ISPRS Int. J. Geo-Inf. 2020, 9(10), 597; https://doi.org/10.3390/ijgi9100597
Received: 2 September 2020 / Revised: 6 October 2020 / Accepted: 9 October 2020 / Published: 11 October 2020
(This article belongs to the Special Issue Citizen Science and Geospatial Capacity Building)
Volunteered geographic information (VGI) has great potential to reveal spatial and temporal dynamics of geographic phenomena. However, a variety of potential biases in VGI are recognized, many of which root from volunteer data contribution activities. Examining patterns in volunteer data contribution activities helps understand the biases. Using eBird as a case study, this study investigates spatial and temporal patterns in data contribution activities of eBird contributors. eBird sampling efforts are biased in space and time. Most sampling efforts are concentrated in areas of denser populations and/or better accessibility, with the most intensively sampled areas being in proximity to big cities in developed regions of the world. Reported bird species are also spatially biased towards areas where more sampling efforts occur. Temporally, eBird sampling efforts and reported bird species are increasing over the years, with significant monthly fluctuations and notably more data reported on weekends. Such trends are driven by the expansion of eBird and characteristics of bird species and observers. The fitness of use of VGI should be assessed in the context of applications by examining spatial, temporal and other biases. Action may need to be taken to account for the biases so that robust inferences can be made from VGI observations. View Full-Text
Keywords: volunteered geographic information (VGI); data contribution activities; spatial and temporal patterns; biases; eBird volunteered geographic information (VGI); data contribution activities; spatial and temporal patterns; biases; eBird
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Zhang, G. Spatial and Temporal Patterns in Volunteer Data Contribution Activities: A Case Study of eBird. ISPRS Int. J. Geo-Inf. 2020, 9, 597.

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