RECORD
Accuracy of a LiDAR-Based Individual Tree Detection and Attribute Measurement Algorithm Developed to Inform Forest Products Supply Chain and Resource Management
- Title:
- Accuracy of a LiDAR-Based Individual Tree Detection and Attribute Measurement Algorithm Developed to Inform Forest Products Supply Chain and Resource Management
- Creator:
- Sparks, Aaron M.; Smith, Alistair M.S.
- Date Created:
- 2022
- Description:
- Individual Tree Detection (ITD) algorithms that use Airborne Laser Scanning (ALS) data can provide accurate tree locations and measurements of tree-level attributes that are required for stand-to-landscape scale forest inventory and supply chain management. While numerous ITD algorithms exist, few have been assessed for accuracy in stands with complex forest structure and composition, limiting their utility for operational application. In this study, we conduct a preliminary assessment of the ability of the ForestView® algorithm created by Northwest Management Incorporated to detect individual trees, classify tree species, live/dead status, canopy position, and estimate height and diameter at breast height (DBH) in a mixed coniferous forest with an average tree density of 543 (s.d. ±387) trees/hectare. ITD accuracy was high in stands with lower canopy cover (recall: 0.67, precision: 0.8) and lower in stands with higher canopy cover (recall: 0.36, precision: 0.67), mainly owing to omission of suppressed trees that were not detected under the dominant tree canopy. Tree species that were well-represented within the study area had high classification accuracies (producer’s/user’s accuracies > ~60%). The similarity between the ALS estimated and observed tree attributes was high, with no statistical difference in the ALS estimated height and DBH distributions and the field observed height and DBH distributions. RMSEs for tree-level height and DBH were 0.69 m and 7.2 cm, respectively. Overall, this algorithm appears comparable to other ITD and measurement algorithms, but quantitative analyses using benchmark datasets in other forest types and cross-comparisons with other ITD algorithms are needed.
- Document Type:
- Research Article
- Subjects:
- UIEF LiDAR individual tree detection ITD forest products supply chain airborne laser scanning ALS algorithm accuracy ITD accuracy GIS
- Location:
- UIEF
- Latitude:
- 46.869607
- Longitude:
- -116.733856
- Publisher:
- MDPI AG
- Department:
- Forest, Rangeland, and Fire Sciences
- Type:
- Text
Source
- Preferred Citation:
- "Accuracy of a LiDAR-Based Individual Tree Detection and Attribute Measurement Algorithm Developed to Inform Forest Products Supply Chain and Resource Management", UIEF Research Exchange, University of Idaho Library Digital Collections, https://www.lib.uidaho.edu/digital/uief/items/uief_0158.html
Rights
- Rights:
- In copyright, educational use permitted.
- Standardized Rights:
- http://rightsstatements.org/vocab/InC-EDU/1.0/