Identification of Silvicultural Practices in Mediterranean Forests Integrating Landsat Time Series and a Single Coverage of ALS Data
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area and Data
2.1.1. ALS Data
2.1.2. Landsat Time Series
2.2. Detection of Harvesting Practices
2.2.1. Forest Mask
2.2.2. BFAST Implementation
2.2.3. Selection of Training Points
2.3. Classification Models
2.3.1. Random Forests Models
2.3.2. Validation
2.4. Fusion Maps
- (i)
- FUSION. A fusion map was created by selecting the most frequent class amongst the six VIs change maps. For example, in Figure 5 clear-cutting is selected, as it happens in 3 out of 6 VI maps;
- (ii)
- F MAX. A fusion map was created by selecting the class with the greatest reliability measure in any of the VI change maps. For example, in Figure 5 thinning is chosen, since the reliability measure of TCG (50%) is the greatest; and
- (iii)
- F SUM. A fusion map was created by selecting the overall most voted class, i.e., summing reliability measures of the all VI change maps. For example, in Figure 5 clear-cutting is selected, as the total reliability measure of its three selecting VI (60%) exceeds the reliability measure of the thinning class (50%).
3. Results
3.1. VIs Overall Accuracy Performance
3.2. Performance in Classification of Forestry Practices
3.3. Fusion Maps
4. Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Vegetation Index | Formula | Reference |
---|---|---|
NDVI | (NIR − RED)/(NIR + RED) | [48] |
NDMI | (NIR − SWIR1)/(NIR + SWIR1) | [49] |
NBR | (NIR − SWIR2)/(NIR + SWIR2) | [50] |
TCB | [51,52,53] | |
TCG | [51,52,53] | |
TCW | [51,52,53] |
Scenario A Monitoring Period: 2005–2010 ALS after Change | Scenario B Monitoring Period: 2011–2016 ALS before Change | |||
---|---|---|---|---|
The most successful VIs: TCB | The most successful VIs: NBR | |||
Class | Commission error | Omission error | Commission error | Omission error |
Cutting with seed-trees | 44.68 | 0.00 | 55.56 | 13.04 |
Clear-cutting | 15.00 | 8.11 | 31.25 | 5.38 |
Thinning | 35.65 | 22.35 | 40.24 | 26.87 |
No change | 4.75 | 13.51 | 5.37 | 9.46 |
Fusion approach | Fusion approach | |||
Class | Commission error | Omission error | Commission error | Omission error |
Cutting with seed-trees | 25.71 | 0.00 | 55.26 | 26.09 |
Clear-cutting | 20.93 | 8.11 | 23.91 | 10.26 |
Thinning | 28.83 | 7.06 | 29.17 | 37.80 |
No change | 2.28 | 13.79 | 3.63 | 6.76 |
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Esteban, J.; Fernández-Landa, A.; Tomé, J.L.; Gómez, C.; Marchamalo, M. Identification of Silvicultural Practices in Mediterranean Forests Integrating Landsat Time Series and a Single Coverage of ALS Data. Remote Sens. 2021, 13, 3611. https://doi.org/10.3390/rs13183611
Esteban J, Fernández-Landa A, Tomé JL, Gómez C, Marchamalo M. Identification of Silvicultural Practices in Mediterranean Forests Integrating Landsat Time Series and a Single Coverage of ALS Data. Remote Sensing. 2021; 13(18):3611. https://doi.org/10.3390/rs13183611
Chicago/Turabian StyleEsteban, Jessica, Alfredo Fernández-Landa, José Luis Tomé, Cristina Gómez, and Miguel Marchamalo. 2021. "Identification of Silvicultural Practices in Mediterranean Forests Integrating Landsat Time Series and a Single Coverage of ALS Data" Remote Sensing 13, no. 18: 3611. https://doi.org/10.3390/rs13183611