Modeling structural traits of Aleppo pine (Pinus halepensis Mill.) forests with low-density LiDAR
Mediterranean forests of Aleppo pine (Pinus halepensis Mill.) have a crucial role in climate change, as they are extremely adaptive and provide valuable timber or carbon stocks. However, greater detail quantifying those attributes is needed: although National Forest Inventories are acceptable, conti...
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| Language: | English |
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Taylor & Francis Group
2024-12-01
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| Series: | European Journal of Remote Sensing |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/22797254.2024.2344569 |
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| author | Vicent A. Ribas-Costa Rachel L. Cook Aitor Gastón |
| author_facet | Vicent A. Ribas-Costa Rachel L. Cook Aitor Gastón |
| author_sort | Vicent A. Ribas-Costa |
| collection | DOAJ |
| description | Mediterranean forests of Aleppo pine (Pinus halepensis Mill.) have a crucial role in climate change, as they are extremely adaptive and provide valuable timber or carbon stocks. However, greater detail quantifying those attributes is needed: although National Forest Inventories are acceptable, continuous cover maps are normally lacking. Here, we use the public Spanish low-density LiDAR flights to model above-ground biomass, volume, tree density, basal area and dominant height of naturally regenerated Mediterranean Aleppo pine forests, comparing individual-tree detection and area-based approach. We found R2 and RRMSE among 0.51–0.66 and 40–34% for above-ground biomass, 0.54–0.70 and 34–28% for volume, 0.23–0.45 and 33–28% for tree density, 0.48–0.62 and 32–27% for basal area, and 0.70–0.69 and 11–11% for dominant height. In all cases but dominant height, the area-based approach outperformed the individual-tree detection. Neither time difference between LiDAR flight and ground measurement or past land use affected the area-based approach models, yet the latter had a strong effect on observed productivity. The different definitions of dominant height were equivalent and did not influence the dominant height models. We believe these models, and their corresponding maps, will be a great asset for policymakers and different stakeholders for Aleppo pine forests throughout the Mediterranean basin. |
| format | Article |
| id | doaj-art-613f39a48f2c451e9961649ca9c1fd55 |
| institution | Kabale University |
| issn | 2279-7254 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | European Journal of Remote Sensing |
| spelling | doaj-art-613f39a48f2c451e9961649ca9c1fd552024-12-11T11:43:31ZengTaylor & Francis GroupEuropean Journal of Remote Sensing2279-72542024-12-0157110.1080/22797254.2024.2344569Modeling structural traits of Aleppo pine (Pinus halepensis Mill.) forests with low-density LiDARVicent A. Ribas-Costa0Rachel L. Cook1Aitor Gastón2Centro para la Conservación de la Biodiversidad y el Desarrollo Sostenible (CBDS), ETSI Montes, Forestal y del Medio Natural, Universidad Politécnica de Madrid, Madrid, SpainDepartment of Forestry & Environmental Resources, NC State University, Raleigh, NC, USACentro para la Conservación de la Biodiversidad y el Desarrollo Sostenible (CBDS), ETSI Montes, Forestal y del Medio Natural, Universidad Politécnica de Madrid, Madrid, SpainMediterranean forests of Aleppo pine (Pinus halepensis Mill.) have a crucial role in climate change, as they are extremely adaptive and provide valuable timber or carbon stocks. However, greater detail quantifying those attributes is needed: although National Forest Inventories are acceptable, continuous cover maps are normally lacking. Here, we use the public Spanish low-density LiDAR flights to model above-ground biomass, volume, tree density, basal area and dominant height of naturally regenerated Mediterranean Aleppo pine forests, comparing individual-tree detection and area-based approach. We found R2 and RRMSE among 0.51–0.66 and 40–34% for above-ground biomass, 0.54–0.70 and 34–28% for volume, 0.23–0.45 and 33–28% for tree density, 0.48–0.62 and 32–27% for basal area, and 0.70–0.69 and 11–11% for dominant height. In all cases but dominant height, the area-based approach outperformed the individual-tree detection. Neither time difference between LiDAR flight and ground measurement or past land use affected the area-based approach models, yet the latter had a strong effect on observed productivity. The different definitions of dominant height were equivalent and did not influence the dominant height models. We believe these models, and their corresponding maps, will be a great asset for policymakers and different stakeholders for Aleppo pine forests throughout the Mediterranean basin.https://www.tandfonline.com/doi/10.1080/22797254.2024.2344569LiDARarea-based approachindividual-tree detectionland historic usemediterranean pinewoods |
| spellingShingle | Vicent A. Ribas-Costa Rachel L. Cook Aitor Gastón Modeling structural traits of Aleppo pine (Pinus halepensis Mill.) forests with low-density LiDAR European Journal of Remote Sensing LiDAR area-based approach individual-tree detection land historic use mediterranean pinewoods |
| title | Modeling structural traits of Aleppo pine (Pinus halepensis Mill.) forests with low-density LiDAR |
| title_full | Modeling structural traits of Aleppo pine (Pinus halepensis Mill.) forests with low-density LiDAR |
| title_fullStr | Modeling structural traits of Aleppo pine (Pinus halepensis Mill.) forests with low-density LiDAR |
| title_full_unstemmed | Modeling structural traits of Aleppo pine (Pinus halepensis Mill.) forests with low-density LiDAR |
| title_short | Modeling structural traits of Aleppo pine (Pinus halepensis Mill.) forests with low-density LiDAR |
| title_sort | modeling structural traits of aleppo pine pinus halepensis mill forests with low density lidar |
| topic | LiDAR area-based approach individual-tree detection land historic use mediterranean pinewoods |
| url | https://www.tandfonline.com/doi/10.1080/22797254.2024.2344569 |
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