Skip to Main Content
Data quality in citizen science urban tree inventoriesAuthor(s): Lara A. Roman; Bryant C. Scharenbroch; Johan P.A. Ostberg; Lee S. Mueller; Jason G. Henning; Andrew K. Koeser; Jessica R. Sanders; Daniel R. Betz; Rebecca C. Jordan
Source: Urban Forestry & Urban Greening
Publication Series: Scientific Journal (JRNL)
Station: Northern Research Station
View PDF (1.0 MB)
DescriptionCitizen science has been gaining popularity in ecological research and resource management in general and in urban forestry specifically. As municipalities and nonprofits engage volunteers in tree data collection, it is critical to understand data quality. We investigated observation error by comparing street tree data collected by experts to data collected by less experienced field crews in Lombard, IL; Grand Rapids, MI; Philadelphia, PA; and Malmö, Sweden. Participants occasionally missed trees (1.2%) or counted extra trees (1.0%). Participants were approximately 90% consistent with experts for site type, land use, dieback, and genus identification. Within correct genera, participants recorded species consistent with experts for 84.8% of trees. Mortality status was highly consistent (99.8% of live trees correctly reported as such), however, there were few standing dead trees overall to evaluate this issue. Crown transparency and wood condition had the poorest performance and participants expressed concerns with these variables; we conclude that these variables should be dropped from future citizen science projects. In measuring diameter at breast height (DBH), participants had challenges with multi-stemmed trees. For single-stem trees, DBH measured by participants matched expert values exactly for 20.2% of trees, within 0.254 cm for 54.4%, and within 2.54 cm for 93.3%. Participants' DBH values were slightly larger than expert DBH on average (+0.33 cm), indicating systematic bias. Volunteer data collection may be a viable option for some urban forest management and research needs, particularly if genus-level identification and DBH at coarse precision are acceptable. To promote greater consistency among field crews, we suggest techniques to encourage consistent population counts, using simpler methods for multi-stemmed trees, providing more resources for species identification, and more photo examples for other variables. Citizen science urban forest inventory and monitoring projects should use data validation and quality assurance procedures to enhance and document data quality.
- Check the Northern Research Station web site to request a printed copy of this publication.
- Our on-line publications are scanned and captured using Adobe Acrobat.
- During the capture process some typographical errors may occur.
- Please contact Sharon Hobrla, email@example.com if you notice any errors which make this publication unusable.
- We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
- This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
CitationRoman, Lara A.; Scharenbroch, Bryant C.; Ostberg, Johan P.A.; Mueller, Lee S.; Henning, Jason G.; Koeser, Andrew K.; Sanders, Jessica R.; Betz, Daniel R.; Jordan, Rebecca C. 2017. Data quality in citizen science urban tree inventories. Urban Forestry & Urban Greening. 22: 124-135.
Keywordsdiameter at breast height, observation error, species misidentification, tree monitoring, urban forest, volunteer monitoring
- Why count trees? Volunteer motivations and experiences with tree monitoring in New York City
- Civic science in urban forestry: Engaging the public in data collection, knowledge production, and stewardship
- FIA national assessment of data quality for forest health indicators
XML: View XML