A text-messaging chatbot to support outdoor recreation monitoring through community science
Public land managers depend on reliable and readily available data about outdoor recreation in parks and greenspaces. However, traditional recreation monitoring techniques including visitor surveying and counting cannot be implemented over large spatial and temporal scales, especially in remote and...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-12-01
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| Series: | Digital Geography and Society |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666378323000119 |
| _version_ | 1827577252688166912 |
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| author | Emilia H. Lia Monika M. Derrien Samantha G. Winder Eric M. White Spencer A. Wood |
| author_facet | Emilia H. Lia Monika M. Derrien Samantha G. Winder Eric M. White Spencer A. Wood |
| author_sort | Emilia H. Lia |
| collection | DOAJ |
| description | Public land managers depend on reliable and readily available data about outdoor recreation in parks and greenspaces. However, traditional recreation monitoring techniques including visitor surveying and counting cannot be implemented over large spatial and temporal scales, especially in remote and undeveloped settings where monitoring is costly. To fill these data gaps, and thereby inform decision-making, this study develops and tests the efficacy of a novel recreation monitoring technique that engages visitors in data collection using a chatbot and text-messages. Drawing on knowledge and methods from community science and crowdsourcing, we present a relatively low-cost and low-barrier approach to counting and characterizing recreational visits on public lands. In an 18-month pilot implementation on a national forest in Washington, USA, we found that crowdsourced data collected using the chatbot were consistent with results of controlled counts and in-person surveys. Furthermore, some sites received relatively high participation rates, up to 12% of recreating parties, regardless of cellular connectivity at the site. This study, which is the first to engage public land usersin community science using a text-messaging chatbot for the purposes of studying outdoor recreation, demonstrates the potential for technology to support new community science approaches that involve visitors in land stewardship and the development of recreation monitoring systems. |
| first_indexed | 2024-03-08T21:24:15Z |
| format | Article |
| id | doaj.art-6c3b952cbcd14fadb61002d8b082f152 |
| institution | Directory Open Access Journal |
| issn | 2666-3783 |
| language | English |
| last_indexed | 2024-03-08T21:24:15Z |
| publishDate | 2023-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Digital Geography and Society |
| spelling | doaj.art-6c3b952cbcd14fadb61002d8b082f1522023-12-21T07:37:27ZengElsevierDigital Geography and Society2666-37832023-12-015100059A text-messaging chatbot to support outdoor recreation monitoring through community scienceEmilia H. Lia0Monika M. Derrien1Samantha G. Winder2Eric M. White3Spencer A. Wood4Outdoor Recreation & Data Lab, University of Washington, Seattle, WA, USA; Corresponding author.USDA Forest Service, Pacific Northwest Research Station, Seattle, WA, USAOutdoor Recreation & Data Lab, University of Washington, Seattle, WA, USAOutdoor Recreation & Data Lab, University of Washington, Seattle, WA, USA; USDA Forest Service, Pacific Northwest Research Station, Seattle, WA, USA; eScience Institute, University of Washington, Seattle, WA, USA.; USDA Forest Service, Pacific Northwest Research Station, Portland, OR, USAOutdoor Recreation & Data Lab, University of Washington, Seattle, WA, USA; eScience Institute, University of Washington, Seattle, WA, USA.Public land managers depend on reliable and readily available data about outdoor recreation in parks and greenspaces. However, traditional recreation monitoring techniques including visitor surveying and counting cannot be implemented over large spatial and temporal scales, especially in remote and undeveloped settings where monitoring is costly. To fill these data gaps, and thereby inform decision-making, this study develops and tests the efficacy of a novel recreation monitoring technique that engages visitors in data collection using a chatbot and text-messages. Drawing on knowledge and methods from community science and crowdsourcing, we present a relatively low-cost and low-barrier approach to counting and characterizing recreational visits on public lands. In an 18-month pilot implementation on a national forest in Washington, USA, we found that crowdsourced data collected using the chatbot were consistent with results of controlled counts and in-person surveys. Furthermore, some sites received relatively high participation rates, up to 12% of recreating parties, regardless of cellular connectivity at the site. This study, which is the first to engage public land usersin community science using a text-messaging chatbot for the purposes of studying outdoor recreation, demonstrates the potential for technology to support new community science approaches that involve visitors in land stewardship and the development of recreation monitoring systems.http://www.sciencedirect.com/science/article/pii/S2666378323000119chatbottext-messagingoutdoor recreationvisitor monitoringcommunity sciencecrowdsourcing |
| spellingShingle | Emilia H. Lia Monika M. Derrien Samantha G. Winder Eric M. White Spencer A. Wood A text-messaging chatbot to support outdoor recreation monitoring through community science Digital Geography and Society chatbot text-messaging outdoor recreation visitor monitoring community science crowdsourcing |
| title | A text-messaging chatbot to support outdoor recreation monitoring through community science |
| title_full | A text-messaging chatbot to support outdoor recreation monitoring through community science |
| title_fullStr | A text-messaging chatbot to support outdoor recreation monitoring through community science |
| title_full_unstemmed | A text-messaging chatbot to support outdoor recreation monitoring through community science |
| title_short | A text-messaging chatbot to support outdoor recreation monitoring through community science |
| title_sort | text messaging chatbot to support outdoor recreation monitoring through community science |
| topic | chatbot text-messaging outdoor recreation visitor monitoring community science crowdsourcing |
| url | http://www.sciencedirect.com/science/article/pii/S2666378323000119 |
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