Accuracy of Volunteer-Derived Data from a Single-Day Inventory Event Built Around a Crowd-Sourcing Tree Mapping Application
Document Type
Article
Publication Date
2018
Keywords
citizen science, crowdsourced data, data accuracy, data quality, tree inventory, urban forestry
Abstract
Freely-available ecosystem service models like those incorporated in the i-Tree suite of tools have helped scientists and practitioners estimate the environmental functions and economic benefits associated with their urban forest. While professional inventory crews have traditionally been used to collect the inventory data needed for these models, several cities have established crowd-sourcing platforms to allow volunteers to map and inventory trees. Students in this study hosted and participated in an Arbor Day inventory collection event using a newly released crowd-sourcing application for mapping trees and estimating ecosystem services. The students located, identified, and measured trees on the University of South Florida campus (Tampa, Florida, United States) after a brief training session. After the one-day event, a more rigorously-trained field crew attempted to relocate the inventoried trees to assess the accuracy and variability of the data collected. Of the 339 trees inventoried at the original event, only 57.8% (n=196) had coordinates that were accurate enough to re-measure. Of the 196 re-measured trees, 91.3% (n=179) were correctly identified. However, only 47.9% (n=91) of trees had dbh measurements within a one inch (2.5 cm) threshold for accuracy. Results of this experiment offer insights for communities looking to host special inventorying events to increase participation in crowd-sourcing tree inventory initiatives.
Was this content written or created while at USF?
Yes
Citation / Publisher Attribution
Arboriculture & Urban Forestry, v. 44, issue 6, p. 248-254
Scholar Commons Citation
Hamilton, Keir; Koeser, Andrew K.; and Landry, Shawn M., "Accuracy of Volunteer-Derived Data from a Single-Day Inventory Event Built Around a Crowd-Sourcing Tree Mapping Application" (2018). School of Geosciences Faculty and Staff Publications. 1265.
https://digitalcommons.usf.edu/geo_facpub/1265
