Identifying Ecosystem Function Shifts in Africa Using Breakpoint Analysis of Long-Term NDVI and RUE Data
Abstract
:1. Introduction
2. Materials and Methods
2.1. NDVI Data
Productivity Indicators
2.2. Time-Series Analyses
- Monotonic: increase (a significant increase with no significant break detected);
- Monotonic: decrease (a significant decrease with no significant break detected);
- Interruption: increase with negative break (a significant increase with a significant break followed by a significant increase);
- Interruption: decrease with positive break (a significant decrease with a significant break followed by a significant decrease);
- Reversal: increase to decrease (a significant increase with a significant break followed by a significant decrease);
- Reversal: decrease to increase (a significant decrease with a significant break followed by a significant increase).
Interpretation of Classified Trends
3. Results and Discussion
3.1. General Patterns
3.2. Regional Patterns
3.3. Limitations
4. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Higginbottom, T.P.; Symeonakis, E. Identifying Ecosystem Function Shifts in Africa Using Breakpoint Analysis of Long-Term NDVI and RUE Data. Remote Sens. 2020, 12, 1894. https://doi.org/10.3390/rs12111894
Higginbottom TP, Symeonakis E. Identifying Ecosystem Function Shifts in Africa Using Breakpoint Analysis of Long-Term NDVI and RUE Data. Remote Sensing. 2020; 12(11):1894. https://doi.org/10.3390/rs12111894
Chicago/Turabian StyleHigginbottom, Thomas P., and Elias Symeonakis. 2020. "Identifying Ecosystem Function Shifts in Africa Using Breakpoint Analysis of Long-Term NDVI and RUE Data" Remote Sensing 12, no. 11: 1894. https://doi.org/10.3390/rs12111894