Next Article in Journal
Understory Vegetation Responses to 15 Years of Repeated Fuel Reduction Treatments in the Southern Appalachian Mountains, USA
Next Article in Special Issue
Mapping Maximum Tree Height of the Great Khingan Mountain, Inner Mongolia Using the Allometric Scaling and Resource Limitations Model
Previous Article in Journal
Effects of Phosphate Solubilizing Bacteria on the Growth, Photosynthesis, and Nutrient Uptake of Camellia oleifera Abel.
Previous Article in Special Issue
Do High-Voltage Power Transmission Lines Affect Forest Landscape and Vegetation Growth: Evidence from a Case for Southeastern of China
Article Menu
Issue 4 (April) cover image

Export Article

Open AccessArticle

Can Field Crews Telecommute? Varied Data Quality from Citizen Science Tree Inventories Conducted Using Street-Level Imagery

1
Department of Geography, Ball State University, 2000 W University Ave, Muncie, IN 47306, USA
2
US Forest Service, Northern Research Station, Philadelphia Field Station, 100 N. 20th St. Suite 205, Philadelphia, PA 19103, USA
3
Environmental Science and Studies Department, DePaul University, 1 E. Jackson Blvd., Chicago, IL 60601, USA
*
Author to whom correspondence should be addressed.
Forests 2019, 10(4), 349; https://doi.org/10.3390/f10040349
Received: 18 March 2019 / Revised: 12 April 2019 / Accepted: 18 April 2019 / Published: 20 April 2019
  |  
PDF [1273 KB, uploaded 26 April 2019]
  |  

Abstract

Street tree inventories are a critical component of urban forest management. However, inventories conducted in the field by trained professionals are expensive and time-consuming. Inventories relying on citizen scientists or virtual surveys conducted remotely using street-level photographs may greatly reduce the costs of street tree inventories, but there are fundamental uncertainties regarding the level of data quality that can be expected from these emerging approaches to data collection. We asked 16 volunteers to inventory street trees in suburban Chicago using Google Street ViewTM imagery, and we assessed data quality by comparing their virtual survey data to field data from the same locations. We also compared virtual survey data quality according to self-rated expertise by measuring agreement within expert, intermediate, and novice analyst groups. Analyst agreement was very good for the number of trees on each street segment, and agreement was markedly lower for tree diameter class and tree identification at the genus and species levels, respectively. Interrater agreement varied by expertise, such that experts agreed with one another more often than novices for all four variables assessed. Compared to the field data, we observed substantial variability in analyst performance for diameter class estimation and tree identification, and some intermediate analysts performed as well as experts. Our findings suggest that virtual surveys may be useful for documenting the locations of street trees within a city more efficiently than field crews and with a high level of accuracy. However, tree diameter and species identification data were less reliable across all expertise groups, and especially novice analysts. Based on this analysis, virtual street tree inventories are best suited to collecting very basic information such as tree locations, or updating existing inventories to determine where trees have been planted or removed. We conclude with evidence-based recommendations for effective implementation of this type of approach. View Full-Text
Keywords: crowdsourced data; Google Street View; interrater agreement; municipal forestry; species identification; street trees; tree measurement; urban ecology; urban forestry crowdsourced data; Google Street View; interrater agreement; municipal forestry; species identification; street trees; tree measurement; urban ecology; urban forestry
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Supplementary material

SciFeed

Share & Cite This Article

MDPI and ACS Style

Berland, A.; Roman, L.A.; Vogt, J. Can Field Crews Telecommute? Varied Data Quality from Citizen Science Tree Inventories Conducted Using Street-Level Imagery. Forests 2019, 10, 349.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Forests EISSN 1999-4907 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top