Estimation of Forest Structure and Fuel Change Across Mountain Pine Beetle – Attacked Forests Using Mobile and RPAS – Based LiDAR
The recent mountain pine beetle (Dendroctonus ponderosae) outbreak has resulted in widespread mortality of pine trees across western Canada over the past two decades. The changes to forest structure caused by the beetle are well known through ground-based observations. However, the potential changes...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-12-01
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| Series: | Canadian Journal of Remote Sensing |
| Online Access: | http://dx.doi.org/10.1080/07038992.2025.2505418 |
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| author | Evan C. Gerbrecht Nicholas C. Coops Allan L. Carroll Christopher W. Bater Leonard Buechner |
| author_facet | Evan C. Gerbrecht Nicholas C. Coops Allan L. Carroll Christopher W. Bater Leonard Buechner |
| author_sort | Evan C. Gerbrecht |
| collection | DOAJ |
| description | The recent mountain pine beetle (Dendroctonus ponderosae) outbreak has resulted in widespread mortality of pine trees across western Canada over the past two decades. The changes to forest structure caused by the beetle are well known through ground-based observations. However, the potential changes to fuels for wildfires associated with altered forest structure are not well known nor incorporated into fire fuel models. In this study, we used light detection and ranging (LiDAR) to quantify variations in forest structure and wildfire fuels caused by mountain pine beetle (MPB) infestation. From this data, we created models that characterize fuels following MPB attack. LiDAR metrics were extracted from three-dimensional point clouds acquired using remotely piloted aircraft systems (RPAS) and mobile laser scanning (MLS), both individually and combined. Fuel components in the stand were then modeled across a range of MPB attack severities. Results indicated the fused model was most accurate at predicting canopy fuel load (R2 = 0.80), while MLS had the best model performance for shrub fuel load (R2 = 0.68) and coarse woody debris fuel load (R2 = 0.68). This study demonstrates the ability of LiDAR to accurately characterize forest fuel loads in MPB-infested forests. |
| format | Article |
| id | doaj-art-e260296ac45a4a23acace0ee0d62d99e |
| institution | OA Journals |
| issn | 1712-7971 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Canadian Journal of Remote Sensing |
| spelling | doaj-art-e260296ac45a4a23acace0ee0d62d99e2025-08-20T02:07:51ZengTaylor & Francis GroupCanadian Journal of Remote Sensing1712-79712025-12-0151110.1080/07038992.2025.25054182505418Estimation of Forest Structure and Fuel Change Across Mountain Pine Beetle – Attacked Forests Using Mobile and RPAS – Based LiDAREvan C. Gerbrecht0Nicholas C. Coops1Allan L. Carroll2Christopher W. Bater3Leonard Buechner4Integrated Remote Sensing Studio, Department of Forest Resources Management, University of British ColumbiaIntegrated Remote Sensing Studio, Department of Forest Resources Management, University of British ColumbiaForest Insect Disturbance Ecology Lab, Department of Forest and Conservation Sciences, University of British ColumbiaCanadian Forest Service (Pacific Forestry Centre), Natural Resources CanadaFaculty for Aerospace Engineering and Geodesy, University of StuttgartThe recent mountain pine beetle (Dendroctonus ponderosae) outbreak has resulted in widespread mortality of pine trees across western Canada over the past two decades. The changes to forest structure caused by the beetle are well known through ground-based observations. However, the potential changes to fuels for wildfires associated with altered forest structure are not well known nor incorporated into fire fuel models. In this study, we used light detection and ranging (LiDAR) to quantify variations in forest structure and wildfire fuels caused by mountain pine beetle (MPB) infestation. From this data, we created models that characterize fuels following MPB attack. LiDAR metrics were extracted from three-dimensional point clouds acquired using remotely piloted aircraft systems (RPAS) and mobile laser scanning (MLS), both individually and combined. Fuel components in the stand were then modeled across a range of MPB attack severities. Results indicated the fused model was most accurate at predicting canopy fuel load (R2 = 0.80), while MLS had the best model performance for shrub fuel load (R2 = 0.68) and coarse woody debris fuel load (R2 = 0.68). This study demonstrates the ability of LiDAR to accurately characterize forest fuel loads in MPB-infested forests.http://dx.doi.org/10.1080/07038992.2025.2505418 |
| spellingShingle | Evan C. Gerbrecht Nicholas C. Coops Allan L. Carroll Christopher W. Bater Leonard Buechner Estimation of Forest Structure and Fuel Change Across Mountain Pine Beetle – Attacked Forests Using Mobile and RPAS – Based LiDAR Canadian Journal of Remote Sensing |
| title | Estimation of Forest Structure and Fuel Change Across Mountain Pine Beetle – Attacked Forests Using Mobile and RPAS – Based LiDAR |
| title_full | Estimation of Forest Structure and Fuel Change Across Mountain Pine Beetle – Attacked Forests Using Mobile and RPAS – Based LiDAR |
| title_fullStr | Estimation of Forest Structure and Fuel Change Across Mountain Pine Beetle – Attacked Forests Using Mobile and RPAS – Based LiDAR |
| title_full_unstemmed | Estimation of Forest Structure and Fuel Change Across Mountain Pine Beetle – Attacked Forests Using Mobile and RPAS – Based LiDAR |
| title_short | Estimation of Forest Structure and Fuel Change Across Mountain Pine Beetle – Attacked Forests Using Mobile and RPAS – Based LiDAR |
| title_sort | estimation of forest structure and fuel change across mountain pine beetle attacked forests using mobile and rpas based lidar |
| url | http://dx.doi.org/10.1080/07038992.2025.2505418 |
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