Handheld photogrammetry advances capabilities to systematically characterize broken‐rock habitat
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| Format: | Artículo Open Access |
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Wiley
2025
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| _version_ | 1867009288814198784 |
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| author | Ana T. Ferreira Lisa A. Shipley Amanda T. Stahl Meghan C. Camp Arjan J. H. Meddens |
| author_facet | Ana T. Ferreira Lisa A. Shipley Amanda T. Stahl Meghan C. Camp Arjan J. H. Meddens Ana T. Ferreira Lisa A. Shipley Amanda T. Stahl Meghan C. Camp Arjan J. H. Meddens |
| collection | Wiley Open Access |
| contents | Handheld photogrammetry advances capabilities to systematically characterize broken‐rock habitat Ana T. Ferreira Lisa A. Shipley Amanda T. Stahl Meghan C. Camp Arjan J. H. Meddens Wildlife Society Bulletin Abstract Structurally complex habitats play a critical role in the survival of wildlife species by providing food, thermal refuges, and protection from predation. However, the same complex properties that make these habitats suitable for wildlife also make them challenging to characterize and assess their ecological value. Traditional methods for characterizing complex habitats are labor intensive and lack the fine‐scale resolution needed for accurate habitat assessment. We developed a workflow using handheld photogrammetry to systematically map and measure fine‐scale habitat characteristics in broken‐rock patches, and identify key habitat features relevant to rock‐dwelling wildlife. To test our workflow, we established 10 m × 10 m plots at 15 talus patches within the North Cascades National Park Service Complex in Washington, USA, and used a structured approach to capture overlapping images with an iPad Pro. We processed images in Agisoft Metashape, using structure‐from‐motion (SfM), to create georeferenced digital elevation models (DEMs) and orthomosaics. We used the Python package segmenteverygrain to semi‐automatically segment the orthomosaic rasters into individual rocks and enable us to quantify size and shape. For classifying areal cover, we created training samples and used a support vector machine algorithm to classify rasters into 3 categories (rock, moss, and vegetation). Using the DEMs, we characterized surface roughness at a 15‐cm resolution. Photogrammetry successfully generated high‐resolution orthomosaics and DEMs for all surveyed plots (GSD ≤1.05 mm). Image segmentation and supervised classification provided detailed quantitative data, revealing variations in rock size, shape, cover types, and surface roughness characteristics. Mean rock volume varied ~60‐fold, and vegetation cover ranged from 0% to 19% across plots. Our workflow provides a scalable and adaptable tool for fine‐scale habitat characterization of structurally complex systems, providing information for species and habitat monitoring. 10.1002/wsb.1613 http://creativecommons.org/licenses/by/4.0/ |
| doi_str_mv | 10.1002/wsb.1613 |
| format | Artículo Open Access |
| id | wiley_oa_10_1002_wsb_1613 |
| institution | Wiley Open Access |
| license_str_mv | http://creativecommons.org/licenses/by/4.0/ |
| publishDate | 2025 |
| publisher | Wiley |
| record_format | wiley_oa |
| spellingShingle | Handheld photogrammetry advances capabilities to systematically characterize broken‐rock habitat Ana T. Ferreira Lisa A. Shipley Amanda T. Stahl Meghan C. Camp Arjan J. H. Meddens Wildlife Society Bulletin Handheld photogrammetry advances capabilities to systematically characterize broken‐rock habitat Ana T. Ferreira Lisa A. Shipley Amanda T. Stahl Meghan C. Camp Arjan J. H. Meddens Wildlife Society Bulletin Abstract Structurally complex habitats play a critical role in the survival of wildlife species by providing food, thermal refuges, and protection from predation. However, the same complex properties that make these habitats suitable for wildlife also make them challenging to characterize and assess their ecological value. Traditional methods for characterizing complex habitats are labor intensive and lack the fine‐scale resolution needed for accurate habitat assessment. We developed a workflow using handheld photogrammetry to systematically map and measure fine‐scale habitat characteristics in broken‐rock patches, and identify key habitat features relevant to rock‐dwelling wildlife. To test our workflow, we established 10 m × 10 m plots at 15 talus patches within the North Cascades National Park Service Complex in Washington, USA, and used a structured approach to capture overlapping images with an iPad Pro. We processed images in Agisoft Metashape, using structure‐from‐motion (SfM), to create georeferenced digital elevation models (DEMs) and orthomosaics. We used the Python package segmenteverygrain to semi‐automatically segment the orthomosaic rasters into individual rocks and enable us to quantify size and shape. For classifying areal cover, we created training samples and used a support vector machine algorithm to classify rasters into 3 categories (rock, moss, and vegetation). Using the DEMs, we characterized surface roughness at a 15‐cm resolution. Photogrammetry successfully generated high‐resolution orthomosaics and DEMs for all surveyed plots (GSD ≤1.05 mm). Image segmentation and supervised classification provided detailed quantitative data, revealing variations in rock size, shape, cover types, and surface roughness characteristics. Mean rock volume varied ~60‐fold, and vegetation cover ranged from 0% to 19% across plots. Our workflow provides a scalable and adaptable tool for fine‐scale habitat characterization of structurally complex systems, providing information for species and habitat monitoring. 10.1002/wsb.1613 http://creativecommons.org/licenses/by/4.0/ |
| title | Handheld photogrammetry advances capabilities to systematically characterize broken‐rock habitat |
| topic | Wildlife Society Bulletin |
| url | https://wildlife.onlinelibrary.wiley.com/doi/10.1002/wsb.1613 |