SustainBench
Sustainability benchmark suite across agriculture, poverty, land cover, water, climate-action, and related geospatial ML tasks.
18rows
task_scoreprimary metric
2026-05-27sampled
Metadata
Metrics
R2, F1 Pixel, F1 Image, Macro F1, Accuracy, RMSE (lower is better), Dice, Kappa
| Rank | Subject | Score | Model Match | Provenance | Sampled |
|---|---|---|---|---|---|
| 1 | Baseline: KNN (Poverty prediction over space) | 0.63 | — | Imported | 2026-05-27 |
| 2 | Baseline: modified ResNet-18 using all satellite bands (Poverty prediction over time) | 0.35 | — | Imported | 2026-05-27 |
| 1 | U-Net (Weakly supervised cropland classification) | 0.88 | — | Imported | 2026-05-27 |
| 1 | Rustowicz et al. (Crop type classification) | 57.3 | — | Imported | 2026-05-27 |
| 1 | Rustowicz et al. (Crop type classification) | 69.7 | — | Imported | 2026-05-27 |
| 1 | You et al. (Crop yield prediction) | 0.37 | — | Imported | 2026-05-27 |
| 1 | Wang et al. (Crop yield prediction) | 0.62 | — | Imported | 2026-05-27 |
| 1 | Wang et al. (Crop yield prediction) | 0.42 | — | Imported | 2026-05-27 |
| 1 | Aung et al. (Field delineation) | 0.61 | — | Imported | 2026-05-27 |
| 1 | Baseline: KNN (Child mortality rate) | 0.01 | — | Imported | 2026-05-27 |
| 1 | Baseline: KNN (Women BMI) | 0.42 | — | Imported | 2026-05-27 |
| 12 | GCN (Lee et al.) (Women BMI) | 0.57 (India) | — | Imported | 2026-05-27 |
| 1 | Baseline: KNN (Women educational attainment) | 0.26 | — | Imported | 2026-05-27 |
| 1 | Baseline: KNN (Water quality index) | 0.40 | — | Imported | 2026-05-27 |
| 1 | Baseline: KNN (Sanitation index) | 0.36 | — | Imported | 2026-05-27 |
| 16 | Lee et al. (Brick kiln detection) | 94.2% | — | Imported | 2026-05-27 |
| 1 | Tile2Vec with ResNet-50 (Representation learning for land cover) | 0.55 (n= 1,000) 0.58 (n= 10,000) | — | Imported | 2026-05-27 |
| 1 | MAML with shallow 1D CNN (Out-of-domain land cover classification) | 0.32 (1-shot, 2-way) | — | Imported | 2026-05-27 |
No matching rows.