Characterizing Off-Highway Road Use with Remote-Sensing, Social Media and Crowd-Sourced Data: An Application to Grizzly Bear (<i>Ursus Arctos</i>) Habitat
Characterizing roads is important for conservation since the relationship between road use and ecological impact can vary across species. However, road use is challenging to monitor due to limited data and high spatial-temporal variability, especially for unpaved roads, which often coincide with cri...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-06-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/13/13/2547 |
| _version_ | 1797528317632446464 |
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| author | Sean P. Kearney Terrence A. Larsen Tristan R. H. Goodbody Nicholas C. Coops Gordon B. Stenhouse |
| author_facet | Sean P. Kearney Terrence A. Larsen Tristan R. H. Goodbody Nicholas C. Coops Gordon B. Stenhouse |
| author_sort | Sean P. Kearney |
| collection | DOAJ |
| description | Characterizing roads is important for conservation since the relationship between road use and ecological impact can vary across species. However, road use is challenging to monitor due to limited data and high spatial-temporal variability, especially for unpaved roads, which often coincide with critical habitats. In this study, we developed and evaluated two methods to characterize off-highway road use across a large management area of grizzly bear (<i>Ursus arctos</i>) habitat using: (1) a ‘network-based’ approach to connect human activity hotspots identified from social media posts and remotely detected disturbances and (2) an ‘image-based’ approach, in which we modeled road surface conditions and travel speed from high spatial resolution satellite imagery trained with crowd-sourced smartphone data. To assess the differences between these approaches and their utility for characterizing roads in the context of habitat integrity, we evaluated how behavioural patterns of global positioning system (GPS)-collared grizzly bears were related to road use characterized by these methods compared to (a) assuming all roads have equal human activity and (b) using a ‘reference’ road classification from a government database. The network- and image-based methods showed similar patterns of road use and grizzly bear response compared to the reference, and all three revealed nocturnal behaviour near high-use roads and better predicted grizzly bear habitat selection compared to assuming all roads had equal human activity. The network- and image-based methods show promise as cost-effective approaches to characterize road use for conservation applications where data is not available. |
| first_indexed | 2024-03-10T09:57:30Z |
| format | Article |
| id | doaj.art-314096ef331a460f9c81efb36feb7d41 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T09:57:30Z |
| publishDate | 2021-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-314096ef331a460f9c81efb36feb7d412023-11-22T02:13:37ZengMDPI AGRemote Sensing2072-42922021-06-011313254710.3390/rs13132547Characterizing Off-Highway Road Use with Remote-Sensing, Social Media and Crowd-Sourced Data: An Application to Grizzly Bear (<i>Ursus Arctos</i>) HabitatSean P. Kearney0Terrence A. Larsen1Tristan R. H. Goodbody2Nicholas C. Coops3Gordon B. Stenhouse4Faculty of Forestry, 2424 Main Mall, University of British Columbia, Vancouver, BC V6T 1Z4, CanadafRI Research, Hinton, AB T7V 1V3, CanadaFaculty of Forestry, 2424 Main Mall, University of British Columbia, Vancouver, BC V6T 1Z4, CanadaFaculty of Forestry, 2424 Main Mall, University of British Columbia, Vancouver, BC V6T 1Z4, CanadafRI Research, Hinton, AB T7V 1V3, CanadaCharacterizing roads is important for conservation since the relationship between road use and ecological impact can vary across species. However, road use is challenging to monitor due to limited data and high spatial-temporal variability, especially for unpaved roads, which often coincide with critical habitats. In this study, we developed and evaluated two methods to characterize off-highway road use across a large management area of grizzly bear (<i>Ursus arctos</i>) habitat using: (1) a ‘network-based’ approach to connect human activity hotspots identified from social media posts and remotely detected disturbances and (2) an ‘image-based’ approach, in which we modeled road surface conditions and travel speed from high spatial resolution satellite imagery trained with crowd-sourced smartphone data. To assess the differences between these approaches and their utility for characterizing roads in the context of habitat integrity, we evaluated how behavioural patterns of global positioning system (GPS)-collared grizzly bears were related to road use characterized by these methods compared to (a) assuming all roads have equal human activity and (b) using a ‘reference’ road classification from a government database. The network- and image-based methods showed similar patterns of road use and grizzly bear response compared to the reference, and all three revealed nocturnal behaviour near high-use roads and better predicted grizzly bear habitat selection compared to assuming all roads had equal human activity. The network- and image-based methods show promise as cost-effective approaches to characterize road use for conservation applications where data is not available.https://www.mdpi.com/2072-4292/13/13/2547spatial ecologygeotagged social media datacircuit theoryroad ecologyroad usetelemetry |
| spellingShingle | Sean P. Kearney Terrence A. Larsen Tristan R. H. Goodbody Nicholas C. Coops Gordon B. Stenhouse Characterizing Off-Highway Road Use with Remote-Sensing, Social Media and Crowd-Sourced Data: An Application to Grizzly Bear (<i>Ursus Arctos</i>) Habitat Remote Sensing spatial ecology geotagged social media data circuit theory road ecology road use telemetry |
| title | Characterizing Off-Highway Road Use with Remote-Sensing, Social Media and Crowd-Sourced Data: An Application to Grizzly Bear (<i>Ursus Arctos</i>) Habitat |
| title_full | Characterizing Off-Highway Road Use with Remote-Sensing, Social Media and Crowd-Sourced Data: An Application to Grizzly Bear (<i>Ursus Arctos</i>) Habitat |
| title_fullStr | Characterizing Off-Highway Road Use with Remote-Sensing, Social Media and Crowd-Sourced Data: An Application to Grizzly Bear (<i>Ursus Arctos</i>) Habitat |
| title_full_unstemmed | Characterizing Off-Highway Road Use with Remote-Sensing, Social Media and Crowd-Sourced Data: An Application to Grizzly Bear (<i>Ursus Arctos</i>) Habitat |
| title_short | Characterizing Off-Highway Road Use with Remote-Sensing, Social Media and Crowd-Sourced Data: An Application to Grizzly Bear (<i>Ursus Arctos</i>) Habitat |
| title_sort | characterizing off highway road use with remote sensing social media and crowd sourced data an application to grizzly bear i ursus arctos i habitat |
| topic | spatial ecology geotagged social media data circuit theory road ecology road use telemetry |
| url | https://www.mdpi.com/2072-4292/13/13/2547 |
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