Investigating the contribution of understory to radiative transfer simulations through reconstructing 3-D realistic temperate broadleaf forest scenes based on multi-platform laser scanning
Forests are complex, multi-layered ecosystems mainly comprising an overstory, understory, and soil. Radiative transfer simulations of these forests underpin the theoretical framework for retrieving forest parameters; however, the understory has often been neglected due to limitations in data acquisi...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-06-01
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| Series: | Science of Remote Sensing |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666017225000021 |
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| author | Xiaohan Lin Ainong Li Jinhu Bian Zhengjian Zhang Xi Nan Limin Chen Yi Bai Yi Deng Siyuan Li |
| author_facet | Xiaohan Lin Ainong Li Jinhu Bian Zhengjian Zhang Xi Nan Limin Chen Yi Bai Yi Deng Siyuan Li |
| author_sort | Xiaohan Lin |
| collection | DOAJ |
| description | Forests are complex, multi-layered ecosystems mainly comprising an overstory, understory, and soil. Radiative transfer simulations of these forests underpin the theoretical framework for retrieving forest parameters; however, the understory has often been neglected due to limitations in data acquisition technology. In this study, we assessed the contribution of the understory to canopy reflectance in a temperate broadleaf forest by comparing simulated bidirectional reflectance factor (BRF) differences between forest scenes with and without the understory. These scenes were reconstructed through voxel-based, boundary-based, and ellipsoid-based approaches respectively based on the multi-layered point cloud data acquired via combining unmanned aerial vehicle (UAV) and backpack laser scanning. The results show that the understory influences the simulated BRF across all three forest scene reconstruction approaches, suggesting that canopy reflectance signals can be used to evaluate the understory information, which provides a theoretical foundation for the feasibility of retrieving understory parameters via remote sensing. The understory increases BRF by 80% in shaded regions beneath the overstory in the red and NIR bands, and can increase BRF by 40% in the NIR band for voxel-based and ellipsoid-based forest scenes. Conversely, it reduces the simulated BRF in sunlit soil areas in the red band. Among the three forest reconstruction methods, the canopy reflectance simulation using the boundary-based model can consistently project the most understory information. Notably, the findings also indicate that the reflectance of the forest canopy definitely capture less understory vegetation information as the simulation resolution decreases, for instance, as the simulated resolution decreased from 1 m to 30 m, the absolute difference in the red band between the multi-layered BRF and L50 BRF decreased from 23.93% to 10.22% when using the boundary-based approach. It implies that higher resolution remote sensing observations are more advantageous for the retrieval of understory parameters. This study provides a successful case for modeling the multi-layered forest structure in natural temperate broadleaf forests, and even offers a theoretical reference for facilitating the retrieval of biochemical and biophysical information from the understory by remote sensing. |
| format | Article |
| id | doaj-art-9bd007a8863d40b6b0daa93c6cfe647f |
| institution | Kabale University |
| issn | 2666-0172 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Science of Remote Sensing |
| spelling | doaj-art-9bd007a8863d40b6b0daa93c6cfe647f2025-01-27T04:22:12ZengElsevierScience of Remote Sensing2666-01722025-06-0111100196Investigating the contribution of understory to radiative transfer simulations through reconstructing 3-D realistic temperate broadleaf forest scenes based on multi-platform laser scanningXiaohan Lin0Ainong Li1Jinhu Bian2Zhengjian Zhang3Xi Nan4Limin Chen5Yi Bai6Yi Deng7Siyuan Li8Research Center of Digital Mountain and Remote Sensing Application, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, 610299, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China; Wanglang Mountain Remote Sensing Observation and Research Station of Sichuan Province, Mianyang, 621000, ChinaResearch Center of Digital Mountain and Remote Sensing Application, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, 610299, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China; College of Geography and Planning, Chengdu University of Technology, Chengdu, 610059, China; Wanglang Mountain Remote Sensing Observation and Research Station of Sichuan Province, Mianyang, 621000, China; Corresponding author. Research Center of Digital Mountain and Remote Sensing Application, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, 610299, China.Research Center of Digital Mountain and Remote Sensing Application, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, 610299, China; Wanglang Mountain Remote Sensing Observation and Research Station of Sichuan Province, Mianyang, 621000, ChinaResearch Center of Digital Mountain and Remote Sensing Application, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, 610299, China; Wanglang Mountain Remote Sensing Observation and Research Station of Sichuan Province, Mianyang, 621000, ChinaResearch Center of Digital Mountain and Remote Sensing Application, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, 610299, China; Wanglang Mountain Remote Sensing Observation and Research Station of Sichuan Province, Mianyang, 621000, ChinaResearch Center of Digital Mountain and Remote Sensing Application, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, 610299, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China; Wanglang Mountain Remote Sensing Observation and Research Station of Sichuan Province, Mianyang, 621000, ChinaResearch Center of Digital Mountain and Remote Sensing Application, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, 610299, China; College of Geography and Planning, Chengdu University of Technology, Chengdu, 610059, China; Wanglang Mountain Remote Sensing Observation and Research Station of Sichuan Province, Mianyang, 621000, ChinaResearch Center of Digital Mountain and Remote Sensing Application, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, 610299, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China; Wanglang Mountain Remote Sensing Observation and Research Station of Sichuan Province, Mianyang, 621000, ChinaResearch Center of Digital Mountain and Remote Sensing Application, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, 610299, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China; Wanglang Mountain Remote Sensing Observation and Research Station of Sichuan Province, Mianyang, 621000, ChinaForests are complex, multi-layered ecosystems mainly comprising an overstory, understory, and soil. Radiative transfer simulations of these forests underpin the theoretical framework for retrieving forest parameters; however, the understory has often been neglected due to limitations in data acquisition technology. In this study, we assessed the contribution of the understory to canopy reflectance in a temperate broadleaf forest by comparing simulated bidirectional reflectance factor (BRF) differences between forest scenes with and without the understory. These scenes were reconstructed through voxel-based, boundary-based, and ellipsoid-based approaches respectively based on the multi-layered point cloud data acquired via combining unmanned aerial vehicle (UAV) and backpack laser scanning. The results show that the understory influences the simulated BRF across all three forest scene reconstruction approaches, suggesting that canopy reflectance signals can be used to evaluate the understory information, which provides a theoretical foundation for the feasibility of retrieving understory parameters via remote sensing. The understory increases BRF by 80% in shaded regions beneath the overstory in the red and NIR bands, and can increase BRF by 40% in the NIR band for voxel-based and ellipsoid-based forest scenes. Conversely, it reduces the simulated BRF in sunlit soil areas in the red band. Among the three forest reconstruction methods, the canopy reflectance simulation using the boundary-based model can consistently project the most understory information. Notably, the findings also indicate that the reflectance of the forest canopy definitely capture less understory vegetation information as the simulation resolution decreases, for instance, as the simulated resolution decreased from 1 m to 30 m, the absolute difference in the red band between the multi-layered BRF and L50 BRF decreased from 23.93% to 10.22% when using the boundary-based approach. It implies that higher resolution remote sensing observations are more advantageous for the retrieval of understory parameters. This study provides a successful case for modeling the multi-layered forest structure in natural temperate broadleaf forests, and even offers a theoretical reference for facilitating the retrieval of biochemical and biophysical information from the understory by remote sensing.http://www.sciencedirect.com/science/article/pii/S2666017225000021Radiative transfer simulationMulti-platform lasering scanningForest 3D reconstructionContribution of understoryRemote sensing |
| spellingShingle | Xiaohan Lin Ainong Li Jinhu Bian Zhengjian Zhang Xi Nan Limin Chen Yi Bai Yi Deng Siyuan Li Investigating the contribution of understory to radiative transfer simulations through reconstructing 3-D realistic temperate broadleaf forest scenes based on multi-platform laser scanning Science of Remote Sensing Radiative transfer simulation Multi-platform lasering scanning Forest 3D reconstruction Contribution of understory Remote sensing |
| title | Investigating the contribution of understory to radiative transfer simulations through reconstructing 3-D realistic temperate broadleaf forest scenes based on multi-platform laser scanning |
| title_full | Investigating the contribution of understory to radiative transfer simulations through reconstructing 3-D realistic temperate broadleaf forest scenes based on multi-platform laser scanning |
| title_fullStr | Investigating the contribution of understory to radiative transfer simulations through reconstructing 3-D realistic temperate broadleaf forest scenes based on multi-platform laser scanning |
| title_full_unstemmed | Investigating the contribution of understory to radiative transfer simulations through reconstructing 3-D realistic temperate broadleaf forest scenes based on multi-platform laser scanning |
| title_short | Investigating the contribution of understory to radiative transfer simulations through reconstructing 3-D realistic temperate broadleaf forest scenes based on multi-platform laser scanning |
| title_sort | investigating the contribution of understory to radiative transfer simulations through reconstructing 3 d realistic temperate broadleaf forest scenes based on multi platform laser scanning |
| topic | Radiative transfer simulation Multi-platform lasering scanning Forest 3D reconstruction Contribution of understory Remote sensing |
| url | http://www.sciencedirect.com/science/article/pii/S2666017225000021 |
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