ANADEM: A Digital Terrain Model for South America
Abstract
:1. Introduction
2. Methods and Data
2.1. Methods Overview
2.2. Study Area
2.3. COPDEM
2.4. GEDI
2.5. Multispectral Data
2.6. ICESat-2
2.7. Data Composition
2.8. Vegetation Bias Removal Algorithm
2.9. Performance Assessment
3. Results and Discussion
3.1. Model Validation
3.2. Spatial Analysis
3.3. Evaluation of Derived Products
3.4. Comparative Assessment with Globally Available Models
4. Conclusions
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Index | Formula | Satellite | Main Reference |
---|---|---|---|
NDMI | Sentinel | [45] | |
MSAVI | Landsat | [46] | |
EVI | Sentinel | [47] |
DEM | Tree Cover (%) | BIAS | RMSE | STD | Median |
---|---|---|---|---|---|
COPDEM | 0 to 20 | 2.18 | 6.4 | 6.02 | 0.24 |
21 to 40 | 4.06 | 6.81 | 5.48 | 2.42 | |
41 to 60 | 8.7 | 11.61 | 7.72 | 6.91 | |
61 to 80 | 16.16 | 18.54 | 9.09 | 15.87 | |
81 to100 | 15.38 | 17.19 | 7.87 | 15.77 | |
ANADEM | 0 to 20 | 1.66 | 5.82 | 5.58 | 0.14 |
21 to 40 | 1.76 | 5.27 | 4.98 | 0.84 | |
41 to 60 | 2.98 | 7.98 | 7.44 | 2.25 | |
61 to 80 | 1.06 | 8.88 | 8.83 | 0.64 | |
81 to 100 | 0.25 | 6.94 | 7.10 | 2.25 |
Model | BIAS | RMSE | STD | Median |
---|---|---|---|---|
SRTM | 10.33 | 16.86 | 12.75 | 9.28 |
COPDEM | 9.56 | 12.40 | 7.24 | 8.50 |
MERIT | 3.88 | 8.94 | 8.00 | 3.00 |
FABDEM | 1.76 | 6.81 | 6.47 | 0.95 |
ANADEM | 1.50 | 6.99 | 6.79 | 0.75 |
Land Cover | Model | BIAS | RMSE | %RMSE | STD | Median |
---|---|---|---|---|---|---|
Pastures (n = 54,242) | SRTM | 5.37 | 10.85 | 2.95 | 9.42 | 3.34 |
COPDEM | 2.1 | 5.33 | 1.45 | 4.89 | 0.45 | |
MERIT | 2.67 | 6.27 | 1.7 | 5.67 | 1.77 | |
FABDEM | 1.88 | 4.95 | 1.34 | 4.57 | 0.45 | |
ANADEM | 1.42 | 4.7 | 1.28 | 4.48 | 0.23 | |
Grasslands (n = 12,073) | SRTM | 2.61 | 6.71 | 2.87 | 6.18 | 2.19 |
COPDEM | 1.26 | 3.81 | 1.63 | 3.59 | 0.27 | |
MERIT | 1.66 | 4.54 | 1.94 | 4.22 | 1.44 | |
FABDEM | 0.97 | 3.41 | 1.46 | 3.27 | 0.27 | |
ANADEM | 0.45 | 3.39 | 1.45 | 3.36 | −0.01 | |
Croplands (n = 18,389) | SRTM | 2.81 | 5.93 | 1.18 | 5.22 | 2.15 |
COPDEM | 0.54 | 2.39 | 0.47 | 2.33 | 0.07 | |
MERIT | 1.72 | 3.57 | 0.71 | 3.12 | 1.5 | |
FABDEM | 0.5 | 2.33 | 0.46 | 2.28 | 0.06 | |
ANADEM | 0.36 | 2.26 | 0.45 | 2.23 | 0.0 | |
Savanna (n = 33,461) | SRTM | 4.53 | 8.99 | 2.25 | 7.76 | 3.79 |
COPDEM | 3.08 | 5.18 | 1.29 | 4.16 | 1.98 | |
MERIT | 2.95 | 5.99 | 1.5 | 5.21 | 2.33 | |
FABDEM | 2.17 | 4.49 | 1.12 | 3.93 | 1.23 | |
ANADEM | 2.35 | 4.75 | 1.18 | 4.12 | 1.46 | |
Forests (n = 100,690) | SRTM | 13.78 | 17.32 | 8.35 | 10.48 | 13.77 |
COPDEM | 14.31 | 16.44 | 7.93 | 8.09 | 14.32 | |
MERIT | 4.69 | 8.89 | 4.28 | 7.55 | 4.36 | |
FABDEM | 0.83 | 6.83 | 3.29 | 6.78 | 0.97 | |
ANADEM | 0.4 | 7.09 | 3.42 | 7.08 | 0.25 | |
Urban areas (n = 1228) | SRTM | 3.7 | 6.94 | 1.65 | 5.87 | 3.05 |
COPDEM | 2.01 | 4.01 | 0.95 | 3.47 | 1.25 | |
MERIT | 2.78 | 5.08 | 1.2 | 4.25 | 2.26 | |
FABDEM | 0.17 | 3.53 | 0.84 | 3.53 | −0.16 | |
ANADEM | 1.83 | 3.78 | 0.9 | 3.31 | 1.18 |
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Laipelt, L.; Comini de Andrade, B.; Collischonn, W.; de Amorim Teixeira, A.; Paiva, R.C.D.d.; Ruhoff, A. ANADEM: A Digital Terrain Model for South America. Remote Sens. 2024, 16, 2321. https://doi.org/10.3390/rs16132321
Laipelt L, Comini de Andrade B, Collischonn W, de Amorim Teixeira A, Paiva RCDd, Ruhoff A. ANADEM: A Digital Terrain Model for South America. Remote Sensing. 2024; 16(13):2321. https://doi.org/10.3390/rs16132321
Chicago/Turabian StyleLaipelt, Leonardo, Bruno Comini de Andrade, Walter Collischonn, Alexandre de Amorim Teixeira, Rodrigo Cauduro Dias de Paiva, and Anderson Ruhoff. 2024. "ANADEM: A Digital Terrain Model for South America" Remote Sensing 16, no. 13: 2321. https://doi.org/10.3390/rs16132321