imagery-provider-adaptation
Skill110 starsChanged 3 months agoMITView on GitHub
Imagery provider adaptation skill for HASTE. Encapsulates provider-specific logic for satellite imagery sources (Planet, Vantor, Airbus, etc.). Use when: 'new imagery provider', 'add source type', 'satellite provider', 'Planet', 'Vantor', 'Airbus', 'Pleiades', 'WorldView', 'SkySat', 'imagery ingestion', 'provider adapter'.
In this repository10 other files it gives its agents.
- AGENTS.mdAGENTS.md
- .github/copilot-instructions.mdCopilot instructions
- api-designSkill
- copilot-cli-modesSkill
- debug-test-failuresSkill
- dependency-updateSkill
- deterministic-scriptsSkill
- release-notesSkill
- security-analysisSkill
- validation-diagnosticsSkill
The file
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2 rules. About 0 are common, 0 are distinctive, and 2 are very specific to this project.
≈0
Common · estimate
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≈0
Distinctive · estimate
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- Common
- Distinctive
- Very specific
- Very specific: line 45
Add to the source type configuration in hastegeo.core.models:
- Very specific: line 83
Update ImageryPreProcessor to route to the new handler based on source type.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
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 |
| Vantor | 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., 256Step 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 integrityStep 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 rasterioStep 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 extractionProvider-Specific Gotchas
| Provider | Gotcha | Mitigation |
| Vantor | 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
Configclass - 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
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