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Citizen Science for Urban Forest Management? Predicting the Data Density and Richness of Urban Forest Volunteered Geographic Information

1
School for Environment and Sustainability, University of Michigan, 500 S State St, Ann Arbor, MI 48109, USA
2
Management Department, College of Business, San Francisco State University, 1600 Holloway Ave, San Francisco, CA 94132, USA
3
Department of Geography and Urban Studies, Temple University, 1801 N Broad St, Philadelphia, PA 19122, USA
*
Author to whom correspondence should be addressed.
Urban Sci. 2017, 1(3), 30; https://doi.org/10.3390/urbansci1030030
Received: 22 July 2017 / Revised: 13 September 2017 / Accepted: 15 September 2017 / Published: 19 September 2017
(This article belongs to the Special Issue Crowdsourcing Urban Data)
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PDF [4043 KB, uploaded 19 September 2017]
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Abstract

Volunteered geographic information (VGI) has been heralded as a promising new data source for urban planning and policymaking. However, there are also concerns surrounding uneven levels of participation and spatial coverage, despite the promotion of VGI as a means to increase access to geographic knowledge production. To begin addressing these concerns, this research examines the spatial distribution and data richness of urban forest VGI in Philadelphia, Pennsylvania and San Francisco, California. Using ordinary least squares (OLS), general linear models (GLM), and spatial autoregressive models, our findings reveal that sociodemographic and environmental indicators are strong predictors of both densities of attributed trees and data richness. Although recent digital urban tree inventory applications present significant opportunities for collaborative data gathering, innovative research, and improved policymaking, asymmetries in the quantity and quality of the data may undermine their effectiveness. If these incomplete and uneven datasets are used in policymaking, environmental justice issues may arise. View Full-Text
Keywords: data richness; digital divide; urban forests; urban public policy; volunteered geographic information (VGI) data richness; digital divide; urban forests; urban public policy; volunteered geographic information (VGI)
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Foster, A.; Dunham, I.M.; Kaylor, C. Citizen Science for Urban Forest Management? Predicting the Data Density and Richness of Urban Forest Volunteered Geographic Information. Urban Sci. 2017, 1, 30.

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