Retrieving Forest Inventory Variables with Terrestrial Laser Scanning (TLS) in Urban Heterogeneous Forest
We present the point cloud slicing (PCS) algorithm, to post process point cloud data (PCD) from terrestrial laser scanning (TLS). We then test this tool for forest inventory application in urban heterogeneous forests. The methodology was based on a voxel data structure derived from TLS PCD. We retri...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2011-12-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | http://www.mdpi.com/2072-4292/4/1/1/ |
| _version_ | 1819294609721786368 |
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| author | L. Monika Moskal Guang Zheng |
| author_facet | L. Monika Moskal Guang Zheng |
| author_sort | L. Monika Moskal |
| collection | DOAJ |
| description | We present the point cloud slicing (PCS) algorithm, to post process point cloud data (PCD) from terrestrial laser scanning (TLS). We then test this tool for forest inventory application in urban heterogeneous forests. The methodology was based on a voxel data structure derived from TLS PCD. We retrieved biophysical tree parameters including diameter at breast height (DBH), tree height, basal area, and volume. Our results showed that TLS-based metrics explained 91.17% (RMSE = 9.1739 cm, p < 0.001) of the variation in DBH at individual tree level. Though the scanner generated a high-density PCD, only 57.27% (RMSE = 0.7543 m, p < 0.001) accuracy was achieved for predicting tree heights in these very heterogeneous stands. Furthermore, we developed a voxel-based TLS volume estimation method. Our results showed that PCD generated from TLS single location scans only captures 18% of the total tree volume due to an occlusion effect; yet there are significant relationships between the TLS data and field measured parameters for DBH and height, giving promise to the utility of a side scanning approach. Using our method, a terrestrial LiDAR-based inventory, also applicable to mobile- or vehicle-based laser scanning (MLS or VLS), was produced for future calibration of Aerial Laser Scanning (ALS) data and urban forest canopy assessments. |
| first_indexed | 2024-12-24T04:29:03Z |
| format | Article |
| id | doaj.art-8fda87a1081248918ede8e8a7b3baf4b |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-12-24T04:29:03Z |
| publishDate | 2011-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-8fda87a1081248918ede8e8a7b3baf4b2022-12-21T17:15:30ZengMDPI AGRemote Sensing2072-42922011-12-014112010.3390/rs4010001Retrieving Forest Inventory Variables with Terrestrial Laser Scanning (TLS) in Urban Heterogeneous ForestL. Monika MoskalGuang ZhengWe present the point cloud slicing (PCS) algorithm, to post process point cloud data (PCD) from terrestrial laser scanning (TLS). We then test this tool for forest inventory application in urban heterogeneous forests. The methodology was based on a voxel data structure derived from TLS PCD. We retrieved biophysical tree parameters including diameter at breast height (DBH), tree height, basal area, and volume. Our results showed that TLS-based metrics explained 91.17% (RMSE = 9.1739 cm, p < 0.001) of the variation in DBH at individual tree level. Though the scanner generated a high-density PCD, only 57.27% (RMSE = 0.7543 m, p < 0.001) accuracy was achieved for predicting tree heights in these very heterogeneous stands. Furthermore, we developed a voxel-based TLS volume estimation method. Our results showed that PCD generated from TLS single location scans only captures 18% of the total tree volume due to an occlusion effect; yet there are significant relationships between the TLS data and field measured parameters for DBH and height, giving promise to the utility of a side scanning approach. Using our method, a terrestrial LiDAR-based inventory, also applicable to mobile- or vehicle-based laser scanning (MLS or VLS), was produced for future calibration of Aerial Laser Scanning (ALS) data and urban forest canopy assessments.http://www.mdpi.com/2072-4292/4/1/1/terrestrial LiDARforest inventorypoint cloud slicing (PCS)heterogeneous forests, terrestrial laser scanning (TLS)vehicle-based laser scanning (VLS) |
| spellingShingle | L. Monika Moskal Guang Zheng Retrieving Forest Inventory Variables with Terrestrial Laser Scanning (TLS) in Urban Heterogeneous Forest Remote Sensing terrestrial LiDAR forest inventory point cloud slicing (PCS) heterogeneous forests, terrestrial laser scanning (TLS) vehicle-based laser scanning (VLS) |
| title | Retrieving Forest Inventory Variables with Terrestrial Laser Scanning (TLS) in Urban Heterogeneous Forest |
| title_full | Retrieving Forest Inventory Variables with Terrestrial Laser Scanning (TLS) in Urban Heterogeneous Forest |
| title_fullStr | Retrieving Forest Inventory Variables with Terrestrial Laser Scanning (TLS) in Urban Heterogeneous Forest |
| title_full_unstemmed | Retrieving Forest Inventory Variables with Terrestrial Laser Scanning (TLS) in Urban Heterogeneous Forest |
| title_short | Retrieving Forest Inventory Variables with Terrestrial Laser Scanning (TLS) in Urban Heterogeneous Forest |
| title_sort | retrieving forest inventory variables with terrestrial laser scanning tls in urban heterogeneous forest |
| topic | terrestrial LiDAR forest inventory point cloud slicing (PCS) heterogeneous forests, terrestrial laser scanning (TLS) vehicle-based laser scanning (VLS) |
| url | http://www.mdpi.com/2072-4292/4/1/1/ |
| work_keys_str_mv | AT lmonikamoskal retrievingforestinventoryvariableswithterrestriallaserscanningtlsinurbanheterogeneousforest AT guangzheng retrievingforestinventoryvariableswithterrestriallaserscanningtlsinurbanheterogeneousforest |