The Utility of Sentinel-2 Spectral Data in Quantifying Above-Ground Carbon Stock in an Urban Reforested Landscape
Abstract
:1. Introduction
2. Materials and Methods
2.1. The Study Area
2.2. Field-Survey and Data Collection
2.3. Allometric Modelling of Aboveground Biomass and Carbon Stock
2.4. Image Acquisition and Pre-Processing
2.5. Statistical Analysis
2.6. Optimal Predictor Variables Selection
2.7. Model Validation and Accuracy Assessment
3. Results
3.1. Carbon Stock of Reforested Trees
3.2. Random Forest Model Optimization
3.3. Variable Importance Selection
3.4. Random Forest Model Prediction Performance
4. Discussion
5. Conclusions
- The spectral information derived from Sentinel-2 MSI can be effectively used to model or predict climate regulating ecosystem services such as carbon stock in reforested urban landscape.
- Spectral indices (e.g., NDVI, EVI, MSRI, and NDVIRE) are useful in enhancing prediction performance of carbon stock in reforested urban environment.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Indices | Formulae | References |
---|---|---|
NDVI | [45] | |
EVI | [46] | |
TVI1 | [47] | |
GNDVI | [48] | |
Clgreen | [49] | |
RVI | [50] | |
MSRI | [51] | |
TVI2 | [52] | |
AVI | [53] | |
MTVI1 | [54] | |
MTVI2 | [54] | |
NPCRI | [55] | |
NDVIRE | [29] | |
ClRE | [49] | |
MSRIRE | [51] |
Prediction Dataset | Mean C (t·ha−1) | R2 (%) | RMSE (t·ha−1) | MAE (t·h−1) |
---|---|---|---|---|
Calibration | 3.389 | 79.82 | 0.378 (11.15%) | 0.189 |
Validation | 3.642 | 77.96 | 0.466 (12.79%) | 0.233 |
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Mngadi, M.; Odindi, J.; Mutanga, O. The Utility of Sentinel-2 Spectral Data in Quantifying Above-Ground Carbon Stock in an Urban Reforested Landscape. Remote Sens. 2021, 13, 4281. https://doi.org/10.3390/rs13214281
Mngadi M, Odindi J, Mutanga O. The Utility of Sentinel-2 Spectral Data in Quantifying Above-Ground Carbon Stock in an Urban Reforested Landscape. Remote Sensing. 2021; 13(21):4281. https://doi.org/10.3390/rs13214281
Chicago/Turabian StyleMngadi, Mthembeni, John Odindi, and Onisimo Mutanga. 2021. "The Utility of Sentinel-2 Spectral Data in Quantifying Above-Ground Carbon Stock in an Urban Reforested Landscape" Remote Sensing 13, no. 21: 4281. https://doi.org/10.3390/rs13214281