Lidar and Multispectral Imagery Classifications of Balsam Fir Tree Status for Accurate Predictions of Merchantable Volume
| Autor: | Benoît St-Onge, Jean Bégin, Sarah Yoga, Demetrios Gatziolis |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Canopy
Balsam 010504 meteorology & atmospheric sciences merchantable volume Multispectral image 0211 other engineering and technologies 02 engineering and technology multispectral imagery 01 natural sciences forest disturbance tree mortality lidar intensity classification point cloud filtering Clipping (photography) 021101 geological & geomatics engineering 0105 earth and related environmental sciences Ecology Taiga Forestry lcsh:QK900-989 Tree (graph theory) Lidar lcsh:Plant ecology Environmental science Woody plant |
| Zdroj: | Forests, Vol 8, Iss 7, p 253 (2017) Forests; Volume 8; Issue 7; Pages: 253 |
| ISSN: | 1999-4907 |
| Popis: | Recent increases in forest diseases have produced significant mortality in boreal forests. These disturbances influence merchantable volume predictions as they affect the distribution of live and dead trees. In this study, we assessed the use of lidar, alone or combined with multispectral imagery, to classify trees and predict the merchantable volumes of 61 balsam fir plots in a boreal forest in eastern Canada. We delineated single trees on a canopy height model. The number of detected trees represented 92% of field trees. Using lidar intensity and image pixel metrics, trees were classified as live or dead with an overall accuracy of 89% and a kappa coefficient of 0.78. Plots were classified according to their class of mortality (low/high) using a 10.5% threshold. Lidar returns associated with dead trees were clipped. Before clipping, the root mean square errors were of 22.7 m3 ha−1 in the low mortality plots and of 39 m3 ha−1 in the high mortality plots. After clipping, they decreased to 20.9 m3 ha−1 and 32.3 m3 ha−1 respectively. Our study suggests that lidar and multispectral imagery can be used to accurately filter dead balsam fir trees and decrease the merchantable volume prediction error by 17.2% in high mortality plots and by 7.9% in low mortality plots. |
| Databáze: | OpenAIRE |
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