Evaluating GEDI data fusions for continuous characterizations of forest wildlife habitat Article Swipe
Jody C. Vogeler
,
Patrick A. Fekety
,
Lisa H. Elliott
,
Neal C. Swayze
,
Steven K. Filippelli
,
Brent Barry
,
Joseph D. Holbrook
,
Kerri T. Vierling
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3389/frsen.2023.1196554
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3389/frsen.2023.1196554
Continuous characterizations of forest structure are critical for modeling wildlife habitat as well as for assessing trade-offs with additional ecosystem services. To overcome the spatial and temporal limitations of airborne lidar data for studying wide-ranging animals and for monitoring wildlife habitat through time, novel sampling data sources, including the space-borne Global Ecosystem Dynamics Investigation (GEDI) lidar instrument, may be incorporated within data fusion frameworks to scale up satellite-based estimates of forest structure across continuous spatial extents. The objectives of this study were to: 1) investigate the value and limitations of satellite data sources for generating GEDI-fusion models and 30 m resolution predictive maps of eight forest structure measures across six western U.S. states (Colorado, Wyoming, Idaho, Oregon, Washington, and Montana); 2) evaluate the suitability of GEDI as a reference data source and assess any spatiotemporal biases of GEDI-fusion maps using samples of airborne lidar data; and 3) examine differences in GEDI-fusion products for inclusion within wildlife habitat models for three keystone woodpecker species with varying forest structure needs. We focused on two fusion models, one that combined Landsat, Sentinel-1 Synthetic Aperture Radar, disturbance, topographic, and bioclimatic predictor information (combined model), and one that was restricted to Landsat, topographic, and bioclimatic predictors (Landsat/topo/bio model). Model performance varied across the eight GEDI structure measures although all representing moderate to high predictive performance (model testing R 2 values ranging from 0.36 to 0.76). Results were similar between fusion models, as well as for map validations for years of model creation (2019–2020) and hindcasted years (2016–2018). Within our wildlife case studies, modeling encounter rates of the three woodpecker species using GEDI-fusion inputs yielded AUC values ranging from 0.76–0.87 with observed relationships that followed our ecological understanding of the species. While our results show promise for the use of remote sensing data fusions for scaling up GEDI structure metrics of value for habitat modeling and other applications across broad continuous extents, further assessments are needed to test their performance within habitat modeling for additional species of conservation interest as well as biodiversity assessments.
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Metadata
- Type
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- Language
- en
- Landing Page
- https://doi.org/10.3389/frsen.2023.1196554
- OA Status
- gold
- Cited By
- 18
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All OpenAlex metadata
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https://openalex.org/W4381431914Canonical identifier for this work in OpenAlex
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https://doi.org/10.3389/frsen.2023.1196554Digital Object Identifier
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Evaluating GEDI data fusions for continuous characterizations of forest wildlife habitatWork title
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articleOpenAlex work type
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enPrimary language
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2023Year of publication
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2023-06-20Full publication date if available
- Authors
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Jody C. Vogeler, Patrick A. Fekety, Lisa H. Elliott, Neal C. Swayze, Steven K. Filippelli, Brent Barry, Joseph D. Holbrook, Kerri T. VierlingList of authors in order
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https://doi.org/10.3389/frsen.2023.1196554Publisher landing page
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.3389/frsen.2023.1196554Direct OA link when available
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Wildlife, Lidar, Habitat, Remote sensing, Environmental science, Geography, Ecology, BiologyTop concepts (fields/topics) attached by OpenAlex
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18Total citation count in OpenAlex
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2025: 11, 2024: 7Per-year citation counts (last 5 years)
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