REDD+: Quick Assessment of Deforestation Risk Based on Available Data
Abstract
:1. Introduction
2. Materials and Methods
2.1. Random Forests
2.2. Data Used and Variable Selection
2.3. Modeling Using 10 and Four Predictors
2.4. Model Calibration
2.5. Model Validation
- Approximately 95,000 sample pixels were generated by adopting a random sampling from the class “forest” at time t2.
- For each pixel randomly selected, the corresponding value from every map of the independent variables at t2 was extracted.
- The calibrated model and the fitted parameters used in the calibration procedure were used to predict the dependent variable at time t3 for the 95,000 pixels.
- The t3-simulated map, which displays the predicted risk of deforestation, was created by interpolating the entire set of pixels using kriging.
- The performance of the model was assessed by applying the three-map comparison technique and other statistical indicators [46].
2.6. Study Area
3. Results
4. Discussion
5. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Source Map | Data Format | Years Covered | Variable Extracted | Reference Unit | Sources |
---|---|---|---|---|---|
Land cover | Vector | 1983 | - Distance to pasture areas | Meters | [27] |
- Distance to cropland areas | Meters | ||||
- Forest type | Broadleaved/coniferous | ||||
- Forest density | Closed forest/open forest | ||||
Land cover | Vector | 2000 | - Distance to pasture areas | Meters | [28] |
- Distance to cropland areas | Meters | ||||
- Forest type | Broadleaved/coniferous | ||||
- Forest density | Closed forest/open forest | ||||
- Forest cover change | Forest/deforestation | ||||
Land cover | Vector | 2011 | - Forest cover change | Forest/deforestation | [30] |
Digital Elevation Model | Raster | - | - Altitude | Meters above sea level | [31] |
Gridded Population of the World | Raster | 1990, 2000 | - Population density | Persons/km2 | [32] |
- Slope | Degrees | ||||
Protected areas | Raster | From 1980 to 2000 | - Presence/absence of protected areas | Protected/No protected | [33] |
Road network | Vector | 1983, 2000 | - Distance to road | Meters | [34,35] |
Urban settlement | Vector | - | - Distance to urban areas | Meters | [36] |
Screened Predictor Variables | |
---|---|
Used in TenPA | Used in FourPA |
Forest density | Altitude |
Population density | Distance to cropland areas |
Distance to cropland areas | Slope |
Protected areas | Distance to pasture areas |
Forest type | |
Altitude | |
Distance to roads | |
Distance to urban areas | |
Slope | |
Distance to pasture areas |
Reference | ||||||
---|---|---|---|---|---|---|
TenPA | FourPA | |||||
Forest | Deforestation | Simulated Total | Forest | Deforestation | Simulated Total | |
Forest | 44.7 | 7.5 | 52.2 | 51.2 | 12 | 63.2 |
Deforestation | 17.3 | 30.5 | 47.8 | 10.8 | 26 | 36.8 |
Reference Total | 62 | 38 | 100 | 62 | 38 | 100 |
Ten Predictors (TenPA) | Four Predictors (FourPA) | |
---|---|---|
Overall accuracy | 76% | 76% |
Producer’s accuracy | 0.80 | 0.69 |
User’s accuracy | 0.64 | 0.71 |
Figure of merit | 55% | 53% |
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Di Lallo, G.; Mundhenk, P.; Zamora López, S.E.; Marchetti, M.; Köhl, M. REDD+: Quick Assessment of Deforestation Risk Based on Available Data. Forests 2017, 8, 29. https://doi.org/10.3390/f8010029
Di Lallo G, Mundhenk P, Zamora López SE, Marchetti M, Köhl M. REDD+: Quick Assessment of Deforestation Risk Based on Available Data. Forests. 2017; 8(1):29. https://doi.org/10.3390/f8010029
Chicago/Turabian StyleDi Lallo, Giulio, Philip Mundhenk, Sheila Edith Zamora López, Marco Marchetti, and Michael Köhl. 2017. "REDD+: Quick Assessment of Deforestation Risk Based on Available Data" Forests 8, no. 1: 29. https://doi.org/10.3390/f8010029