Potential of Sentinel-2A Data to Model Surface and Canopy Fuel Characteristics in Relation to Crown Fire Hazard
Abstract
:1. Introduction
2. Materials and Methods
2.1. Plot Network
2.2. Tree Variables
2.3. Surface Fuel Variables
2.4. Canopy Fuel Variables
2.5. Sentinel-2A Data Set
2.6. Data Analysis
2.7. Crown Fire Behavior Simulation
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Species | Statistic | Tree Variables (n = 10,831) | Stand Variables (n = 123) | Surface and Canopy Fuels Variables (n = 123 *) | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
d (cm) | h (m) | hblc (m) | t (years) | N (stems ha−1) | G (m2 ha−1) | H (m) | SFL (Mg ha−1) | FSG (m) | CBH (m) | CBD (kg m−3) | ||
P. pinaster | Mean | 21.12 | 14.96 | 8.63 | 23.67 | 1028.22 | 39.08 | 16.08 | 44.99 | 8.35 | 8.66 | 0.1655 |
Std. dev. | 6.50 | 2.96 | 2.48 | 4.18 | 480.64 | 9.34 | 2.69 | 10.22 | 2.32 | 2.31 | 0.0503 | |
Min. | 3.90 | 5.60 | 2.3 | 18 | 407 | 20.04 | 10.98 | 30.24 | 4.18 | 4.53 | 0.0846 | |
Max. | 48.50 | 23.7 | 15.9 | 38 | 3095 | 66.08 | 21.35 | 78.49 | 12.65 | 13.03 | 0.3369 | |
P. radiata | Mean | 21.92 | 20.13 | 10.34 | 22.43 | 838.47 | 34.57 | 22.67 | 49.42 | 9.67 | 10.15 | 0.1140 |
Std. dev. | 6.78 | 3.88 | 3.18 | 2.06 | 427.53 | 9.88 | 2.78 | 21.28 | 2.78 | 2.53 | 0.0462 | |
Min. | 2.75 | 5.80 | 1.10 | 18 | 316 | 15.59 | 16.15 | 24.47 | 4.70 | 5.51 | 0.0372 | |
Max. | 47.55 | 30.10 | 20.70 | 28 | 2899 | 66.63 | 27.23 | 116.03 | 14.88 | 15.83 | 0.2840 |
Scene | Acquisition Date | Solar Elevation (°) | Solar Azimuth (°) |
---|---|---|---|
S-2A_tile_20160801_29TMH | 1 August 2016 | 61.92 | 148.41 |
S-2A_tile_20160719_29TNG | 19 July 2016 | 63.25 | 144.23 |
S-2A_tile_20160801_29TNH | 1 August 2016 | 61.92 | 148.41 |
S-2A_tile_20160719_29TPG | 19 July 2016 | 63.25 | 144.23 |
S-2A_tile_20160719_29TPH | 19 July 2016 | 63.25 | 144.23 |
S-2A_tile_20160719_29TPJ | 19 July 2016 | 63.25 | 144.23 |
S-2A_tile_20160719_29TQH | 19 July 2016 | 63.25 | 144.23 |
Sentinel-2A/MSI (µm) | Band | Resolution (m) |
---|---|---|
Band 2 (0.46–0.52) | Blue | 10 |
Band 3 (0.54–0.58) | Green | 10 |
Band 4 (0.65–0.68) | Red | 10 |
Band 5 (0.7–0.71) | Red-edge-1 | 20 |
Band 6 (0.73–0.75) | Red-edge-2 | 20 |
Band 7 (0.76–0.78) | Red-edge-3 | 20 |
Band 8 (0.78–0.90) | NIR | 10 |
Band 8A (0.85–0.87) | Narrow NIR | 20 |
Band 11 (1.56–1.65) | SWIR-1 | 20 |
Band 12 (2.10–2.28) | SWIR-2 | 20 |
Vegetation Index | Formulation | S-2A Bands Used |
---|---|---|
NDVI [47] | ||
SAVI [48] | ||
MSAVI [49] | ||
EVI [50] | ||
RENDVI [51] |
Observed | User’s Accuracy | ||||||||
---|---|---|---|---|---|---|---|---|---|
P. pinaster | P. radiata | ||||||||
C | MT | HT | C | MT | HT | ||||
Predicted | P. pinaster | C | 19 | 4 | 3 | 0 | 1 | 0 | 79.17% |
MT | 2 | 18 | 1 | 1 | 0 | 0 | 75.00% | ||
HT | 1 | 0 | 18 | 0 | 2 | 0 | 84.21% | ||
P. radiata | C | 0 | 0 | 0 | 16 | 0 | 0 | 100% | |
MT | 0 | 0 | 0 | 1 | 16 | 3 | 80.00% | ||
HT | 0 | 0 | 0 | 1 | 0 | 16 | 94.12% | ||
Producer’s accuracy | 86.36% | 81.82% | 81.82% | 84.21% | 84.21% | 84.21% | 83.74% |
Fuel Variable | RF | MARS | ||
---|---|---|---|---|
rRMSE | rRMSE | |||
SFL (Mg ha−1) | 34.79% | 0.1233 | 43.21% | 0.0180 |
FSG (m) | 24.05% | 0.3755 | 27.08% | 0.3285 |
CBH (m) | 20.23% | 0.4771 | 26.69% | 0.3104 |
CBD (kg m−3) | 32.76% | 0.3125 | 33.97% | 0.2972 |
Species and Treatment | Burning Conditions | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
Low | Moderate | Extreme | ||||||||
Active | Passive | Surface | Active | Passive | Surface | Active | Passive | Surface | ||
P. pinaster | C | 0% | 0% | 100% | 77.3% | 9.1% | 13.6% | 100% | 0% | 0% |
HT | 0% | 0% | 100% | 18.2% | 59.1% | 22.7% | 100% | 0% | 0% | |
P. radiata | C | 0% | 0% | 100% | 15.8% | 42.1% | 42.1% | 100% | 0% | 0% |
HT | 0% | 0% | 100% | 0% | 68.4% | 31.6% | 73.7% | 26.3% | 0% |
Observed | ||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Pinus pinaster | Pinus radiata | |||||||||||||
MARS Predictions | Control | Heavy Thinning | Control | Heavy Thinning | ||||||||||
Active | Passive | Surface | Active | Passive | Surface | Active | Passive | Surface | Active | Passive | Surface | |||
Pinus pinaster | Control | Active | 33 | 0 | 1 | 3 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Passive | 1 | 2 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ||
Surface | 1 | 0 | 19 | 0 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | ||
Thinned | Active | 4 | 0 | 1 | 19 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | |
Passive | 0 | 0 | 1 | 3 | 8 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | ||
Surface | 0 | 0 | 3 | 1 | 1 | 21 | 0 | 0 | 1 | 0 | 0 | 0 | ||
Pinus radiata | Control | Active | 0 | 0 | 0 | 0 | 0 | 0 | 17 | 1 | 0 | 0 | 0 | 0 |
Passive | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 3 | 2 | 0 | 0 | 0 | ||
Surface | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 20 | 0 | 0 | 0 | ||
Thinned | Active | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 13 | 6 | 0 | |
Passive | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 1 | 10 | 5 | ||
Surface | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 2 | 20 | ||
Observed | ||||||||||||||
Active | Passive | Surface | User’s Accuracy | |||||||||||
MARS predictions | Active | 91 | 9 | 4 | 87.5% | Overall accuracy | 84.1% | |||||||
Passive | 8 | 26 | 10 | 59.1% | Kappa statistic | 0.7476 | ||||||||
Surface | 2 | 6 | 90 | 91.8% | ||||||||||
Producer’s accuracy | 90.1% | 63.4% | 86.5% | 84.1% |
Observed | ||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Pinus pinaster | Pinus radiata | |||||||||||||
RF Predictions | Control | Heavy Thinning | Control | Heavy Thinning | ||||||||||
Active | Passive | Surface | Active | Passive | Surface | Active | Passive | Surface | Active | Passive | Surface | |||
Pinus pinaster | Control | Active | 34 | 1 | 1 | 3 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Passive | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ||
Surface | 0 | 0 | 19 | 0 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | ||
Thinned | Active | 4 | 0 | 2 | 20 | 2 | 5 | 1 | 1 | 0 | 0 | 0 | 0 | |
Passive | 0 | 0 | 0 | 3 | 8 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ||
Surface | 0 | 0 | 3 | 0 | 0 | 19 | 0 | 0 | 1 | 0 | 0 | 0 | ||
Pinus radiata | Control | Active | 0 | 0 | 0 | 0 | 0 | 0 | 16 | 2 | 1 | 0 | 0 | 0 |
Passive | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 5 | 5 | 0 | 0 | 0 | ||
Surface | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 16 | 0 | 0 | 0 | ||
Thinned | Active | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 14 | 2 | 0 | |
Passive | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 16 | 5 | ||
Surface | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 20 | ||
Observed | ||||||||||||||
Active | Passive | Surface | User’s Accuracy | |||||||||||
RF predictions | Active | 94 | 10 | 9 | 83.2% | Overall accuracy | 84.6% | |||||||
Passive | 7 | 31 | 12 | 62.0% | Kappa statistic | 0.7567 | ||||||||
Surface | 0 | 0 | 83 | 100% | ||||||||||
Producer’s accuracy | 93.1% | 75.6% | 79.8% | 84.6% |
© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Arellano-Pérez, S.; Castedo-Dorado, F.; López-Sánchez, C.A.; González-Ferreiro, E.; Yang, Z.; Díaz-Varela, R.A.; Álvarez-González, J.G.; Vega, J.A.; Ruiz-González, A.D. Potential of Sentinel-2A Data to Model Surface and Canopy Fuel Characteristics in Relation to Crown Fire Hazard. Remote Sens. 2018, 10, 1645. https://doi.org/10.3390/rs10101645
Arellano-Pérez S, Castedo-Dorado F, López-Sánchez CA, González-Ferreiro E, Yang Z, Díaz-Varela RA, Álvarez-González JG, Vega JA, Ruiz-González AD. Potential of Sentinel-2A Data to Model Surface and Canopy Fuel Characteristics in Relation to Crown Fire Hazard. Remote Sensing. 2018; 10(10):1645. https://doi.org/10.3390/rs10101645
Chicago/Turabian StyleArellano-Pérez, Stéfano, Fernando Castedo-Dorado, Carlos Antonio López-Sánchez, Eduardo González-Ferreiro, Zhiqiang Yang, Ramón Alberto Díaz-Varela, Juan Gabriel Álvarez-González, José Antonio Vega, and Ana Daría Ruiz-González. 2018. "Potential of Sentinel-2A Data to Model Surface and Canopy Fuel Characteristics in Relation to Crown Fire Hazard" Remote Sensing 10, no. 10: 1645. https://doi.org/10.3390/rs10101645