Characterizing forest structural changes in response to non-stand replacing disturbances using bitemporal airborne laser scanning data
Characterizing the extent, severity, and persistence of natural disturbances in forests is crucial in areas as large and heterogeneous as the Canadian boreal forest. Non-stand replacing (NSR) disturbances, in particular, can produce subtle and lagged impacts to forest canopy and structure with mecha...
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Elsevier
2024-12-01
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| Series: | Science of Remote Sensing |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666017224000440 |
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| author | Tommaso Trotto Nicholas C. Coops Alexis Achim Sarah E. Gergel Dominik Roeser |
| author_facet | Tommaso Trotto Nicholas C. Coops Alexis Achim Sarah E. Gergel Dominik Roeser |
| author_sort | Tommaso Trotto |
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| description | Characterizing the extent, severity, and persistence of natural disturbances in forests is crucial in areas as large and heterogeneous as the Canadian boreal forest. Non-stand replacing (NSR) disturbances, in particular, can produce subtle and lagged impacts to forest canopy and structure with mechanisms that remain elusive, and they are challenging to discern using typical remote sensing approaches including aerial photointerpretation and spectral analysis of satellite imagery. Consequently, there is a need for timely and accurate information on the structural modifications due to NSR disturbances to inform proactive forest management practices. To address these needs, we leveraged a unique bitemporal airborne laser scanning (ALS) dataset to characterize changes in the forest structure caused by eastern spruce budworm (ESB, Choristoneura fumiferana (Clem.)), responsible for one of the greatest tree mortality in Canada. A range of infestation severity with varying impacts to forest structure are examined in a mixedwood boreal forest in Lac-Saint Jean, Quebec, Canada. We derived 14 ALS structural change metrics at 10 m spatial resolution, including height, cover, and gappiness 7 years apart (2014–2020). Six distinct structural responses to cumulative ESB infestations severity were identified using cluster analysis from the combination of the 14 change metrics, with canopy cover, the 75th and 25th height percentiles (p75-25) driving cluster separability. Canopy cover and p25 consistently decreased as cumulative infestation severity increased, whereas p75 showed greater variability across the landscape. Photointerpretation of aerial imagery over the same period confirmed the validity of the structural characterization. Further, we studied the role of initial forest structures in modulating the severity of the infestation and found that sparser canopies with cover <65% and shorter trees (p75 < 7.5 m, p25 < 2.5 m) were associated with less severe ESB infestations after 7 years, and controlling for underlying environmental factors. These findings showed the potential of bitemporal ALS data in characterizing structural changes due to ESB infestations at fine scale based on canopy cover and height, relevant for forest management strategies to better target current and future infestations. |
| format | Article |
| id | doaj-art-a6a06b6237474d2fa812c8ef8b793352 |
| institution | OA Journals |
| issn | 2666-0172 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
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| series | Science of Remote Sensing |
| spelling | doaj-art-a6a06b6237474d2fa812c8ef8b7933522025-08-20T01:59:00ZengElsevierScience of Remote Sensing2666-01722024-12-011010016010.1016/j.srs.2024.100160Characterizing forest structural changes in response to non-stand replacing disturbances using bitemporal airborne laser scanning dataTommaso Trotto0Nicholas C. Coops1Alexis Achim2Sarah E. Gergel3Dominik Roeser4Department of Forest Resources Management, University of British Columbia, 2424 Main Mall, Vancouver, BC, V6T 1Z4, Canada; Corresponding author.Department of Forest Resources Management, University of British Columbia, 2424 Main Mall, Vancouver, BC, V6T 1Z4, CanadaCentre de recherche sur les matériaux renouvelables, Département des sciences du bois et de la forêt, Université Laval, 2425 rue de la Terrasse, Québec, QC, G1V 0A6, CanadaDepartment of Forest and Conservation Sciences, Faculty of Forestry, University of British Columbia, 2424 Main Mall, Vancouver, BC, V6T 1Z4, CanadaDepartment of Forest Resources Management, University of British Columbia, 2424 Main Mall, Vancouver, BC, V6T 1Z4, CanadaCharacterizing the extent, severity, and persistence of natural disturbances in forests is crucial in areas as large and heterogeneous as the Canadian boreal forest. Non-stand replacing (NSR) disturbances, in particular, can produce subtle and lagged impacts to forest canopy and structure with mechanisms that remain elusive, and they are challenging to discern using typical remote sensing approaches including aerial photointerpretation and spectral analysis of satellite imagery. Consequently, there is a need for timely and accurate information on the structural modifications due to NSR disturbances to inform proactive forest management practices. To address these needs, we leveraged a unique bitemporal airborne laser scanning (ALS) dataset to characterize changes in the forest structure caused by eastern spruce budworm (ESB, Choristoneura fumiferana (Clem.)), responsible for one of the greatest tree mortality in Canada. A range of infestation severity with varying impacts to forest structure are examined in a mixedwood boreal forest in Lac-Saint Jean, Quebec, Canada. We derived 14 ALS structural change metrics at 10 m spatial resolution, including height, cover, and gappiness 7 years apart (2014–2020). Six distinct structural responses to cumulative ESB infestations severity were identified using cluster analysis from the combination of the 14 change metrics, with canopy cover, the 75th and 25th height percentiles (p75-25) driving cluster separability. Canopy cover and p25 consistently decreased as cumulative infestation severity increased, whereas p75 showed greater variability across the landscape. Photointerpretation of aerial imagery over the same period confirmed the validity of the structural characterization. Further, we studied the role of initial forest structures in modulating the severity of the infestation and found that sparser canopies with cover <65% and shorter trees (p75 < 7.5 m, p25 < 2.5 m) were associated with less severe ESB infestations after 7 years, and controlling for underlying environmental factors. These findings showed the potential of bitemporal ALS data in characterizing structural changes due to ESB infestations at fine scale based on canopy cover and height, relevant for forest management strategies to better target current and future infestations.http://www.sciencedirect.com/science/article/pii/S2666017224000440Boreal forestInsectLidarDisturbance severityCanopy coverClustering |
| spellingShingle | Tommaso Trotto Nicholas C. Coops Alexis Achim Sarah E. Gergel Dominik Roeser Characterizing forest structural changes in response to non-stand replacing disturbances using bitemporal airborne laser scanning data Science of Remote Sensing Boreal forest Insect Lidar Disturbance severity Canopy cover Clustering |
| title | Characterizing forest structural changes in response to non-stand replacing disturbances using bitemporal airborne laser scanning data |
| title_full | Characterizing forest structural changes in response to non-stand replacing disturbances using bitemporal airborne laser scanning data |
| title_fullStr | Characterizing forest structural changes in response to non-stand replacing disturbances using bitemporal airborne laser scanning data |
| title_full_unstemmed | Characterizing forest structural changes in response to non-stand replacing disturbances using bitemporal airborne laser scanning data |
| title_short | Characterizing forest structural changes in response to non-stand replacing disturbances using bitemporal airborne laser scanning data |
| title_sort | characterizing forest structural changes in response to non stand replacing disturbances using bitemporal airborne laser scanning data |
| topic | Boreal forest Insect Lidar Disturbance severity Canopy cover Clustering |
| url | http://www.sciencedirect.com/science/article/pii/S2666017224000440 |
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