End-to-End Remote Sensing Architecture
GeoClass executes all heavy computation serverless-side on Google Earth Engine supercomputing clusters. Client requests specify an Area of Interest (AOI) polygon, a temporal observation window, cloud cover thresholds, and masking preferences.
Raw Sentinel-2 Level-2A surface reflectance granules undergo rigorous masking using both the Scene Classification Layer (SCL) and QA60 opaque cloud and cirrus bitmasks. Cloud shadows (SCL 2), defective pixels, and saturated artifacts are eliminated prior to temporal compositing.
Pixels are aggregated over the specified date window using a median reducer. This rejects intermittent cloud fringes, sensor anomalies, and transient haze while preserving persistent land cover reflectance signatures. Optional seasonal partitioning isolates dry or wet phenological cycles.
On top of 10 optical surface reflectance bands (B2, B3, B4, B5, B6, B7, B8, B8A, B11, B12), mathematical diagnostic indices (NDVI, MNDWI, NDBI, NBR) are computed and added. When enabled, dual-polarized Sentinel-1 C-band SAR backscatter features (VV, VH, and VV/VH cross-polarization ratio) are fused directly into the feature stack.
Ground truth pixels are sampled stratified across 9 Land Use / Land Cover classes using Dynamic World modal predictions. A Random Forest ensemble of decision trees is trained on the fly on Earth Engine, classifying every pixel within the AOI at 10-meter spatial resolution.
Harmonized 9-Class LULC Taxonomy
| Class ID | Class Name | Color Value | Diagnostic Spectral & SAR Characteristics |
|---|---|---|---|
| 0 | Water | #419BDF | High NIR absorption, high MNDWI (>0.1), specular microwave reflection (very low VV/VH backscatter). |
| 1 | Trees / Forest | #397D49 | High red edge and NIR reflectance (NDVI >0.6), high cross-polarized VH microwave volume scattering. |
| 2 | Grass | #88B053 | Moderate NDVI (0.3 to 0.6), low surface roughness, lower VH return than mature forest canopy. |
| 3 | Flooded Vegetation | #7A87C6 | Mixed water/canopy response, double-bounce microwave scattering between water surface and emergent stalks. |
| 4 | Crops | #E49635 | Periodic phenological variations in NDVI, geometric field parcel structures, moderate SAR backscatter. |
| 5 | Shrub & Scrub | #DFC35A | Low-stature woody vegetation, intermediate NIR reflectance between grass and closed canopy. |
| 6 | Built-Up / Urban | #C4281B | High NDBI (>0.05), high SWIR reflectance, corner-reflector dihedral microwave bounce (intense VV return). |
| 7 | Bare Ground | #A59B8F | Flat spectral response across visible to NIR, low NDVI (<0.1), surface roughness driven SAR response. |
| 8 | Snow & Ice | #B39FE1 | Extremely high visible reflectance, sharp absorption in SWIR bands B11 and B12. |
Multi-Mission Earth Observation Constellations
GeoClass bridges European Space Agency (Copernicus) and NASA / USGS constellations. Through our STAC catalog integration and Earth Engine bindings, users can dynamically switch optical baselines between Sentinel-2 and Landsat 8/9, or fuse Sentinel-1 synthetic aperture radar.
| Constellation | Operator | Sensor Type | Spatial Resolution | Temporal Revisit | Atmospheric Resilience | Primary Role in GeoClass |
|---|---|---|---|---|---|---|
| Copernicus Sentinel-2 | ESA / European Union | MSI (Multi-Spectral 13 Bands) | 10m / 20m | 5 days (Constellation 2A + 2B) | SCL & QA60 Cloud Screening | High-resolution optical classification, 10m spectral indices (NDVI, NDRE) |
| USGS / NASA Landsat 8 & 9 | USGS / NASA | OLI / OLI-2 + TIRS (11 Bands) | 30m (Optical) / 100m (Thermal) | 8 days (Combined 8 + 9) | QA_PIXEL Bitmask Screening | Decadal historical continuity, 30m Level-2 Tier-1 surface reflectance cross-validation |
| Copernicus Sentinel-1 | ESA / European Union | C-SAR (Active Microwave 5.405 GHz) | 10m (IW Ground Range Detected) | 6-12 days | 100% Cloud-Penetrating (All-Weather) | Cloud-penetrating radar backscatter fusion (VV, VH), canopy moisture and structural roughness |