Imagery Provider Adaptation

Imagery Provider Adaptation

Overview

Structured process for adding new satellite imagery providers to HASTE. Each provider has different data formats, coordinate systems, APIs, band configurations, and delivery methods. This skill encapsulates the provider-specific logic needed to adapt a new source.

Key Concepts

Current Providers

| Provider | Satellites | Format | Bands | Delivery |

|----------|-----------|--------|-------|----------|

| Maxar | WorldView-2/3/4, GeoEye-1 | GeoTIFF | 4-8 bands (BGRN + extras) | S3, STAC, Direct URL |

| Planet | PlanetScope, SkySat | GeoTIFF, COG | 4 bands (BGRN) | Planet API, S3 |

| Airbus | Pleiades, Pleiades Neo, SPOT | GeoTIFF, DIMAP | 4 bands (BGRN) | OneAtlas, S3 |

Provider Adapter Components

Each new provider requires:

• Source Type Definition — Model configuration in hastegeo.core.models
• Download Handler — Provider-specific authentication and download logic
• Band Mapping — Map provider bands to HASTE's expected band order
• Metadata Parser — Extract spatial metadata from provider-specific formats
• Preprocessing Rules — Resolution normalization, radiometric correction
• Tests — Integration tests with sample provider data

Patterns & Techniques

Adding a New Provider: Step-by-Step

Step 1: Define source type

Add to the source type configuration in hastegeo.core.models:

# New source type with provider-specific configuration
class NewProviderConfig(BaseModel):
    provider_name: str
    api_url: str
    band_order: list[str]  # e.g., ["B", "G", "R", "NIR"]
    default_crs: str  # e.g., "EPSG:4326"
    tile_size: int  # e.g., 256

Step 2: Implement download handler

In hastegeo.core.processors.imagery:

# Handle provider-specific authentication and URL patterns
# Use requests with proper auth (API key, OAuth, etc.)
# Stream large files to avoid memory issues
# Validate downloaded file integrity

Step 3: Implement band mapping

# Map provider bands to HASTE standard order
# HASTE expects: [Blue, Green, Red, NIR] for 4-band
# Handle extra bands (e.g., coastal, red-edge, SWIR)
# Handle missing bands (e.g., panchromatic only)

Step 4: Implement preprocessing

# 1. Validate CRS — reproject if needed
# 2. Normalize resolution — resample to target GSD
# 3. Apply radiometric correction if needed
# 4. Generate COG with internal tiling and overviews
# 5. Validate output with rasterio

Step 5: Add to imagery processor

Update ImageryPreProcessor to route to the new handler based on source type.

Step 6: Write tests

# Test with real sample data (small AOI, public data preferred)
# Verify CRS preservation
# Verify band order mapping
# Verify COG compliance
# Verify metadata extraction

Provider-Specific Gotchas

| Provider | Gotcha | Mitigation |

|----------|--------|------------|

| Maxar | Multiple UTM zones in a single order | Check CRS per file, reproject to consistent zone |

| Planet | UDM2 quality masks delivered separately | Download and apply quality mask before processing |

| Airbus | DIMAP format metadata | Parse XML metadata alongside GeoTIFF |

| All | Different nodata conventions | Standardize nodata to 0 or NaN during preprocessing |

Decision Framework

| Scenario | Approach |

|----------|----------|

| Provider uses standard GeoTIFF | Minimal adapter — mostly URL/auth handling |

| Provider uses proprietary format | Full adapter — format conversion + metadata extraction |

| Provider delivers via STAC | Use existing STAC client, add provider-specific auth |

| Provider requires API key | Store in Config, never hardcode |

| Provider delivers in tiles | Implement tile stitching before COG generation |

Quick Reference: COG Output Standard

Format: Cloud Optimized GeoTIFF
Tiling: 256x256 or 512x512 internal tiles
Overviews: Nearest power of 2, down to 256px
Compression: LZW or DEFLATE
CRS: Preserve source CRS (typically UTM or EPSG:4326)
Nodata: 0 for uint8/uint16, NaN for float
Bands: Blue, Green, Red, NIR (minimum)

Common Pitfalls

• Assuming all providers use the same band order — Always check and map explicitly
• Hardcoding provider URLs/keys — Use Config class
• Ignoring quality masks — Bad pixels contaminate training data
• Not testing with edge cases — Antimeridian crossing, polar regions, dateline
• Downloading entire scenes when only a small AOI is needed — Use provider APIs to clip