Using Annual Landsat Time Series for the Detection of Dry Forest Degradation Processes in South-Central Angola
Abstract
:1. Introduction
- Assess the extent and location of forest degradation areas and differentiate between modification processes;
- Identify the main underlying drivers of forest degradation;
- Assess the difference in degradation on later cultivated areas and on non-converted forest areas.
2. Study Area
3. Data
4. Methods
5. Results and Discussion
6. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Significance | Intercept | ||
---|---|---|---|
Insignificant | min–0 | overperforming | |
Sign. negative | 0–3 | underperforming | |
Sign. positive | 3–max | strongly underperforming | |
Mean Absolute Error | Maximum Residuum | ||
min–1 | steady trend | −3–3 | no disturbances |
1–3 | medium deviations | <−3 or >3 | additional disturbances |
3–max | strong deviations |
Class | Parameters | Example |
---|---|---|
Stable, dense forest/woodland |
| |
Steady forest degradation |
| |
Steady forest degradation with selective use |
|
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Schneibel, A.; Frantz, D.; Röder, A.; Stellmes, M.; Fischer, K.; Hill, J. Using Annual Landsat Time Series for the Detection of Dry Forest Degradation Processes in South-Central Angola. Remote Sens. 2017, 9, 905. https://doi.org/10.3390/rs9090905
Schneibel A, Frantz D, Röder A, Stellmes M, Fischer K, Hill J. Using Annual Landsat Time Series for the Detection of Dry Forest Degradation Processes in South-Central Angola. Remote Sensing. 2017; 9(9):905. https://doi.org/10.3390/rs9090905
Chicago/Turabian StyleSchneibel, Anne, David Frantz, Achim Röder, Marion Stellmes, Kim Fischer, and Joachim Hill. 2017. "Using Annual Landsat Time Series for the Detection of Dry Forest Degradation Processes in South-Central Angola" Remote Sensing 9, no. 9: 905. https://doi.org/10.3390/rs9090905