Arboriculture & Urban Forestry 44(6): November 2018 ENHANCING TREE CHECKERS Mobile and Online Data Collection Prior to 2016, PHS records for tree planting and monitoring were managed through a complex se- ries of steps involving manually entered paper records and emailed spreadsheets (Boyer et al. 2016). With the decentralized structure of the Tree Tenders program, this data management system required PHS staff to clean and compile dozens of spreadsheets from the group leaders for both planting requests and monitoring data. PHS staff were concerned that this process was too time- consuming and prone to error. When PHS staff be- gan their search for a soſtware solution to their data management challenges, there was no off-the-shelf option, as proprietary soſtware for urban forestry did not include monitoring features (Boyer et al. 2016). To address data management concerns, PHS switched to a new data management and collec- tion system in 2015, called the PHS Urban Forest Cloud, a customization of the Tree Plotter soſtware from the firm Plan-It Geo (Hanou 2016). The Ur- ban Forest Cloud system “features a collection of all data gathered for individual trees and projects and enables multiple user groups to update and manage tree information that is stored in a central database and map” (Hanou 2016). Within the Ur- ban Forest Cloud, the Tree Checkers component is a web-based data collection system that enables volunteers to enter data via mobile devices, such as smartphones or tablets. During the summer of 2017, half of the tree data came through mobile data collection, while data from Tree Checkers who preferred paper was entered later via computer. With two summers of Tree Checkers data collec- tion using the Urban Forest Cloud (2016–2017), PHS staff have identified several benefits of the system. First, although there was an initial financial and staff time investment in the soſtware and re-training of volunteers, the data entry burden for PHS staff and Tree Tenders has declined. Second, by eliminating the data entry and spreadsheet compilation steps, PHS staff can more quickly produce summary sta- tistics about tree-planting performance. Third, based on informal conversations between PHS staff and volunteers, Tree Tenders have appreciated using the online map for routing data collection and visual- izing data. Fourth, using mobile data collection has 259 enabled groups to seamlessly integrate tree photos, which should help with reliable re-location of trees in the future (Roman et al. 2017). A key remaining challenge is that a subset of the monitoring data is still submitted via manually transcribed spreadsheets. PHS staff would prefer to have all data submitted via the Urban Forest Cloud, to eliminate the staff time needed to incorporate those spreadsheets back into the cloud. However, PHS staff continue allowing paper data entry, so as not to discourage volunteers who are not comfortable with or do not own mobile devices. Indeed, while citizen science programs more broadly have embraced mobile data collection (Gra- ham et al. 2011; Newman et al. 2012), such technolo- gies can risk excluding certain populations, such as retirees and low-income individuals lacking smart- phones (Roman et al. 2013; Klimova et al. 2018). Data Quality Evaluation Following in the semi-autonomous nature of Tree Tenders, PHS strongly encourages but does not strictly require (or enforce) participation in Tree Checkers. Therefore, Tree Checkers data is essen- tially a convenience sample, which may yield biased results due to patterns in non-participation. In some earlier years, only half of the trees planted in the prior two seasons were monitored. In addition to potential sampling bias, volunteers may also have observation errors (Roman et al. 2017). To investigate these data quality issues, PHS and Forest Service scientists de- signed a supplementary sample for summer 2017. In addition to the volunteer-generated convenience sample, paid interns monitored a random sample. The volunteer sample and the intern sample were col- lected independently. These interns had additional supervision and training. The primary objective of comparing the volunteers and intern samples was to determine whether overall findings as well as tree-by-tree observations—especially survival— were comparable between the two samples. Out of the 797 trees planted in autumn 2016 and spring 2017, interns recorded data for 198 (25%) trees and volunteers recorded data for 707 (89%) trees, with 178 recorded by both crews. Volunteers collected data June–August 2017, and interns August 2017. The proportion of trees recorded by volunteers was considerably higher than in prior years (66% in 2015, 71% in 2016). More people may be partici- pating as they learn to use the Urban Forest Cloud, ©2018 International Society of Arboriculture
November 2018
| Title Name |
Pages |
Delete |
Url |
| Empty |
Ai generated response may be inaccurate.
Search Text Block
Page #page_num
#doc_title
Hi $receivername|$receiveremail,
$sendername|$senderemail wrote these comments for you:
$message
$sendername|$senderemail would like for you to view the following digital edition.
Please click on the page below to be directed to the digital edition:
$thumbnail$pagenum
$link$pagenum
Your form submission was a success.
Downloading PDF
Generating your PDF, please wait...
This process might take longer please wait
