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.
Highlights
Street trees are trees growing in the public right-of-way along streets in cities, towns, and suburbs.Though street trees are a relatively small proportion of the overall urban forest in many cities [1], they are a highly visible component that constitute a major focus of public engagement by municipalities and nonprofit organizations [2,3,4]
This work advances our understanding of data quality associated with two approaches to data collection – citizen science projects and virtual surveys using street-level panoramas – that have potential to become increasingly prominent for street tree inventories
We present the following recommendations for those who may be interested in combining citizen science and virtual surveys to generate street tree inventory data
Summary
Though street trees are a relatively small proportion of the overall urban forest in many cities [1], they are a highly visible component that constitute a major focus of public engagement by municipalities and nonprofit organizations [2,3,4]. Street trees generate a range of benefits such as increased property values, shade, stormwater capture, and aesthetics [5,6,7]. Street trees can be conceived of as common pool resources, in that they provide benefits to the general public, but it is often unclear who is responsible. The public right-of-way in which street trees are located is directly adjacent to both private and public properties, and may include a sidewalk. Many municipalities have long directly managed street trees through municipal laws, policies, and personnel [2,9], these trees exist under a multi-stakeholder governance regime [10], with residents, municipal agencies, nonprofit organizations, and developers impacting decision-making
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