Terrestrial Laser Scanning for Quantifying Timber Assortments from Standing Trees in a Mixed and Multi-Layered Mediterranean Forest
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Field Data
2.3. Terrestrial Laser Scanning Data
2.4. Data Analysis
2.4.1. Pre-Processing of the Raw TLS Data
2.4.2. Timber-Leaf Discrimination
Geometry-Based Calculation
Predictor Variables Selection
Binary Classification
2.4.3. Stem Detection
2.4.4. Stem Reconstruction
2.4.5. Timber Assortment Assessment
3. Results
3.1. Timber-Leaf Discrimination, Stem Detection, and DBH Estimation
3.2. Stem Reconstruction
3.3. Timber Assortment Assessment
4. Discussion
4.1. Timber-Leaf Discrimination
4.2. Stem Detection and DBH Estimation
4.3. Stem Reconstruction
4.4. Timber Assortment Assessment
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Acknowledgments
Conflicts of Interest
Appendix A
Appendix B
Appendix C
Merchantable (Units) | Non-merchantable (Units) | ||||||
---|---|---|---|---|---|---|---|
Tree Species | Observed Data | Predicted Data | Accuracy | Observed Data | Predicted Data | Accuracy | |
1 | Turkey oak | 62 | 43 | 10 | 11 | ||
2 | European beech | 42 | 36 | 12 | 10 | ||
3 | European ash | 45 | 34 | 10 | 6 | ||
4 | Field maple | 3 | 2 | 0 | 0 | ||
5 | Italian maple | 14 | 11 | 5 | 4 | ||
6 | Small-leaf lime | 8 | 4 | 1 | 1 | ||
7 | European Hop-hornbeam | 4 | 3 | 1 | 1 | ||
8 | Hornbeam | 1 | 1 | 1 | 1 | ||
Sum | 179 | 134 | 40 | 34 | |||
Bias * | 5.6 | 0.8 | |||||
RMSE * | 8.3 | 1.7 |
Appendix D
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Timber Assortments | ||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Assortments | Types | Saw-log Plus | Saw-log | Pulpwood | Other Industrial Roundwood | Fuelwood | ||||||||||
Classes | A1 | A2 | A3 | B1 | B2 | B3 | C1 | C2 | C3 | D1 | D2 | D3 | Fuelwood1 | Fuelwood2 | Fuelwood3 | |
Requirements | STR (cm m−1) | x ≤ 2 | 2 < x ≤ 3.4 | 3.4 < x ≤ 5 | 5 < x ≤ 6.6 | x > 6.6 | ||||||||||
Dmin | Large | Medium | Small | Large | Medium | Small | Large | Medium | Small | Large | Medium | Small | Large | Medium | Small |
Forest structure | TLS data | ||||||
---|---|---|---|---|---|---|---|
ADS | Trees ADS−1 (Trees ha−1) | Stem Density (Level) | Mean (±SD) | Total | Point Density and Spacing (pts m−2 and mm) | ||
DBH (m) | TH (m) | TSV (m3) | TSR (Units) | ||||
1 | 33 (623) | moderate | 0.20 (±0.09) | 18.52 (±5.16) | 13.20 | 7 | 92,244; 3.19 |
2 | 36 (679) | moderate | 0.20 (±0.19) | 13.28 (±8.19) | 23.86 | 9 | 44,310; 4.75 |
3 | 52 (981) | high | 0.16 (±0.13) | 13.72 (±6.79) | 16.32 | 8 | 64,836; 3,92 |
4 | 33 (623) | moderate | 0.21 (±0.14) | 21.27 (±8.97) | 22.81 | 9 | 44,210; 4.76 |
5 | 24 (453) | low | 0.26 (±0.15) | 23.1 (±10.22) | 25.29 | 5 | 36,622; 5.22 |
Sum | 178 | ||||||
Mean | 36 (672) |
Type of logs | ADS | N° logs (Units) | STR (cm m−1) | TAP (cm m−1) | TTv.log (m3) |
---|---|---|---|---|---|
Mean (±SD) | Mean (±SD) | Sum | |||
Merchantable | 1 | 88 | 2.9 (±1.9) | 1.5 (±0.7) | 7.2 |
2 | 45 | 1.6 (±1.3) | 1.8 (±1) | 10.9 | |
3 | 35 | 1.4 (±1.1) | 1.6 (±0.4) | 6.7 | |
4 | 56 | 1.8 (±1.4) | 1.1 (±0.5) | 12.9 | |
5 | 82 | 1.6 (±0.9) | 1.2 (±0.4) | 12.4 | |
TOT | 306 *1 | 1.8 (±1.3) *2 | 1.4 (±0.6) *2 | 10.0 *2 | |
Non-merchantable | 1 | 30 | 2.1 (±4) | 1.3 (±2.6) | 1.1 |
2 | 13 | 1.7 (±2.5) | 0.9 (±1.3) | 1.2 | |
3 | 11 | 1.4 (±1.7) | 0.5 (±1.2) | 0.7 | |
4 | 8 | 2.1 (±2.9) | 1 (±1.4) | 0.4 | |
5 | 17 | 1.3 (±2.6) | 1 (±1.3) | 1.2 | |
TOT | 79 *1 | 1.7 (±2.7) *2 | 0.9 (±1.6) *2 | 0.9 *2 |
ADS | TR (Units) | TLS results | ||||||
---|---|---|---|---|---|---|---|---|
TreeTLS | TruePos | FalsePos | FalseNeg | DR (%) | Completeness (%) | Correctness (%) | ||
(Units) | (Units) | (Units) | (Units) | |||||
1 | 33 | 45 | 30 | 15 | 3 | 90.9 | 90.9 | 66.7 |
2 | 36 | 54 | 29 | 25 | 7 | 80.6 | 80.6 | 53.7 |
3 | 52 | 71 | 45 | 26 | 7 | 86.5 | 86.6 | 63.4 |
4 | 33 | 36 | 28 | 8 | 5 | 84.8 | 84.9 | 77.8 |
5 | 24 | 26 | 19 | 7 | 5 | 79.2 | 79.2 | 73.1 |
Sum | 178 | 232 | 151 | 81 | 27 | |||
Mean (±SD) | 36 (±10) | 46 (±17.2) | 30 (±9.4) | 16 (±9.0) | 5 (±1.7) | 84.4 (±4.7) | 84.4 (±4.7) | 66.9 (±9.3) |
Stem Reconstruction Results | ||||||
---|---|---|---|---|---|---|
Description | ADS | TOTAL | ||||
1 | 2 | 3 | 4 | 5 | ||
TR | 13 | 14 | 13 | 13 | 17 | 70 |
RStem | 10 | 7 | 7 | 11 | 12 | 47 |
TrueRStem | 76.9 | 50 | 53.8 | 84.6 | 70.6 | 67.2 (14.9) |
Observed Data | Predicted Data | |||||
---|---|---|---|---|---|---|
Log Section | Logs | Length of Log (m) | N°logs | Length of Log (m) | ||
Mean (±SD) | Sum | Mean (±SD) | Sum | |||
Merchantable | 179 | 2.50 (±0) | 447.5 | 134 | 2.78 (±0.12) | 372.51 |
Non-merchantable | 40 | 1.35 (±0.69) | 53.9 | 34 | 1.62 (±0.57) | 54.99 |
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Alvites, C.; Santopuoli, G.; Hollaus, M.; Pfeifer, N.; Maesano, M.; Moresi, F.V.; Marchetti, M.; Lasserre, B. Terrestrial Laser Scanning for Quantifying Timber Assortments from Standing Trees in a Mixed and Multi-Layered Mediterranean Forest. Remote Sens. 2021, 13, 4265. https://doi.org/10.3390/rs13214265
Alvites C, Santopuoli G, Hollaus M, Pfeifer N, Maesano M, Moresi FV, Marchetti M, Lasserre B. Terrestrial Laser Scanning for Quantifying Timber Assortments from Standing Trees in a Mixed and Multi-Layered Mediterranean Forest. Remote Sensing. 2021; 13(21):4265. https://doi.org/10.3390/rs13214265
Chicago/Turabian StyleAlvites, Cesar, Giovanni Santopuoli, Markus Hollaus, Norbert Pfeifer, Mauro Maesano, Federico Valerio Moresi, Marco Marchetti, and Bruno Lasserre. 2021. "Terrestrial Laser Scanning for Quantifying Timber Assortments from Standing Trees in a Mixed and Multi-Layered Mediterranean Forest" Remote Sensing 13, no. 21: 4265. https://doi.org/10.3390/rs13214265
APA StyleAlvites, C., Santopuoli, G., Hollaus, M., Pfeifer, N., Maesano, M., Moresi, F. V., Marchetti, M., & Lasserre, B. (2021). Terrestrial Laser Scanning for Quantifying Timber Assortments from Standing Trees in a Mixed and Multi-Layered Mediterranean Forest. Remote Sensing, 13(21), 4265. https://doi.org/10.3390/rs13214265