250 Hamilton et al.: Volunteer-Derived Data for a Tree Mapping Application held at the University of South Florida campus in Tampa, Florida, U.S. (28.0587°N, 82.4139°W). Be- fore the event, organizers divided the campus into 20 measurement areas to prevent data collection overlap. Within these measurement areas, groups of Arbor Day volunteers (total n = 60, volunteers) were instructed to conduct an inventory of trees for two hours. Participants were undergraduate college students. They did not receive academic credit or any similar compensation for their time. The groups used an iOS data collection and tree mapping application (OpenTreeMap, Aza- vea, Philadelphia, Pennsylvania, U.S.) and a diameter tape to collect data. Prior to being sent to their respective measurement areas, participants watched a brief PowerPoint® train- ing session (i.e., 23 slides, or approximately 30 minutes) that provided instructions on how to measure and plot trees using the inventorying application and tape provided. The presenta- tion also showed eight of the most common tree species on campus and their defining charac- teristics. Later, in small groups, the Arbor Day inventory event organizers verified each stu- dent volunteer’s individual ability to identify species and measure trees (e.g., dbh). During this session, the organizers showed partici- pants how to locate and record a tree’s geo- graphic location using an integrated aerial map function, enter measurement data, and include a photograph of the sample specimen. After the training, the groups were given a campus map showing their assigned measure- ment area zones. Participants utilizing the diameter tape were instructed to measure the diameter of mature trees at 1.37 m from the tree base. After two hours of participation, the student volunteers returned to a nearby lec- ture hall to complete a survey of their experi- ence. These evaluations used a standardized, 19-question questionnaire developed by the university to assess student programs. Ques- tions were a 5-point rating or yes/no depend- ing on the question asked. The evaluations were assessed using descriptive statistics in Excel™. During the summer, a more rigorously-trained quality control team with three advanced (senior bachelor’s degree) environmental science stu- dents accessed the records online and revisited ©2018 International Society of Arboriculture the inventoried trees to recheck the locations, species identification, measured trunk diam- eters, and estimated heights. In addition to the tools and resources provided to volunteers, the quality control team was equipped with a range finding hypsometer (Forestry Pro Laser Rangefinder model 8381, Nikon Corporation, Tokyo, Japan; height data not reported) and a regional field guide not available at the time of the original inventorying event (Koeser et al. 2015). In reassessing the inventoried data, the quality control team noted any trees they could not find given the coordinates logged, trees with incorrectly identified species, and trees with trunk diameters above or below a 2.54 cm error threshold. When significant differences were noted, the records were updated to reflect correct identifications and measurements made by the quality control team. Pictures were taken of any trees requiring additional aid for iden- tification (provided by faculty supervisors). All data used in this study were down- loaded directly from TampaTreeMap.org. Pro- gram evaluations were provided to the authors by the event planners. As such, the research team received an existing data exemption through the supervising author’s internal review board. RESULTS AND DISCUSSION Of the 339 trees logged at the Arbor Day inven- torying event, only 196 were found by the qual- ity control team, resulting in a re-location suc- cess rate of 57.8%. In looking at the response data from the post-event survey, many participants expressed that they had difficulties attempting to map trees using the aerial image function. At the time, some respondents attributed this to a potential but unconfirmed glitch with the appli- cation used (a locally modified version of Open- TreeMap), in which multiple users appeared to be blocked from making simultaneous data sub- missions. Even when working seamlessly, the mapping function requires some correction from the user (GPS is used to provide a rough location, but the user drops a “pin” on the tree being in- ventoried, given their interpretation of aerial im- ages). Aerial interpretation can take some skill, depending on the site and tree coverages. This knowledge requirement may have served as an-
November 2018
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