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The transferability of airborne laser scanning based tree-level models between different inventory areas
- Source :
- Canadian Journal of Forest Research. 49:228-236
- Publication Year :
- 2019
- Publisher :
- Canadian Science Publishing, 2019.
-
Abstract
- In this paper, we examine the transferability of airborne laser scanning (ALS) based models for individual-tree detection (ITD) from one ALS inventory area (A1) to two other areas (A2 and A3). All areas were located in eastern Finland less than 100 km from each other and were scanned using different ALS devices and parameters. The tree attributes of interest were diameter at breast height (Dbh), height (H), crown base height (Cbh), stem volume (V), and theoretical sawlog volume (Vlog) of Scots pine (Pinus sylvestris L.) with Dbh ≥ 16 cm. All trees were first segmented from the canopy height models, and various ALS metrics were derived for each segment. Then only the segments covering correctly detected pines were chosen for further inspection. The tree attributes were predicted using the k-nearest neighbor (k-NN) imputation. The results showed that the relative root mean square error (RMSE%) values increased for each attribute after the transfers. The RMSE% values were, for A1, A2, and A3, respectively: Dbh, 13.5%, 14.8%, and 18.1%; H, 3.2%, 5.9%, and 6.2%; Cbh, 13.3%, 15.3%, and 18.3%; V, 29.3%, 35.4%, and 39.1%; and Vlog, 38.2%, 54.4% and 51.8%. The observed values indicate that it may be possible to employ ALS-based tree-level k-NN models over different inventory areas without excessive reduction in accuracy, assuming that the tree species are known to be similar.
- Subjects :
- Canopy
Global and Planetary Change
010504 meteorology & atmospheric sciences
Ecology
Laser scanning
Transferability
0211 other engineering and technologies
Forestry
02 engineering and technology
01 natural sciences
k-nearest neighbors algorithm
Tree (data structure)
Environmental science
021101 geological & geomatics engineering
0105 earth and related environmental sciences
Remote sensing
Woody plant
Subjects
Details
- ISSN :
- 12086037 and 00455067
- Volume :
- 49
- Database :
- OpenAIRE
- Journal :
- Canadian Journal of Forest Research
- Accession number :
- edsair.doi...........63f67e80f1ddbc0dccf74a066f398bee