Integration of satellite imagery for crop surveillance

Purpose

1.1. Deliver real-time or periodic satellite imagery for surveillance of crop health, growth stages, and early warning of threats.
1.2. Automate collection, processing, and analysis to detect anomalies, drought stress, pest/disease outbreaks, and optimize field interventions.
1.3. Enable historical trend analysis, accurate yield forecasting, and compliance documentation for regulatory or insurance requirements.

Trigger Conditions

2.1. Scheduled collection based on season, growth stage, or user-defined intervals (e.g., every 5 days).
2.2. Event-driven, such as precipitation above/below threshold, detected weather anomalies, or model-triggered alerts.
2.3. On-demand via field operator request or integration with farm management backend.

Platform variants

3.1. Google Earth Engine
• Feature: Assets → Satellite Image Collection
• Setting: JavaScript API – `ee.ImageCollection("COPERNICUS/S2").filterDate("YYYY-MM-DD", "YYYY-MM-DD")`
3.2. AWS Ground Station
• Feature: Data Capture API
• Setting: Configure observation schedule for field geocoordinates
3.3. Microsoft Azure FarmBeats
• Feature: Satellite Data Connector
• Setting: FarmBeats portal – link imagery analytics workflow
3.4. Planet Labs
• Feature: Planet API (Data/Imagery)
• Setting: `data/v1/item-types/satellite-imagery/items` and delivery webhook
3.5. Sentinel Hub
• Feature: Process API
• Setting: `process` endpoint with AOI polygon for field boundary
3.6. Descartes Labs
• Feature: Remote Sensing API
• Setting: `images:search` and `raster:compute` for NDVI extraction
3.7. SpaceKnow
• Feature: Insights Platform API
• Setting: Crop monitoring module, configure AOI and production type
3.8. Airbus OneAtlas
• Feature: Access API
• Setting: Tasking service for periodic monitoring or archive search
3.9. Maxar SecureWatch
• Feature: Imagery API
• Setting: Search by date/lat-long, trigger download or alert
3.10. Mapbox
• Feature: Satellite Layer and Raster Tiles
• Setting: Overlay live imagery on farm map UI
3.11. Agrio
• Feature: Crop Surveillance API
• Setting: Automate push upon detection of crop stress indicators
3.12. IBM The Weather Company
• Feature: Agricultural Analytics API
• Setting: Integrate imagery enrichment, anomaly detection
3.13. EOX Cloudless
• Feature: EO Browser API
• Setting: Fetch visualized satellite composites via API
3.14. OpenAerialMap
• Feature: OAM API
• Setting: Periodic search for recent open satellite/Aerial captures
3.15. SkyWatch EarthCache
• Feature: Subscription & Delivery API
• Setting: Set up recurring deliveries for field polygons
3.16. Ag-Analytics
• Feature: Field-Level Imagery API
• Setting: Schedule NDVI/EVI time series extraction
3.17. Cropio
• Feature: Satellite Monitoring
• Setting: Notification triggers for vegetation index drop
3.18. EOS Data Analytics
• Feature: Field Image Delivery API
• Setting: Auto-schedule by field, defined frequency
3.19. GeoPard Agriculture
• Feature: Imagery Sync
• Setting: AOI-based syncing with GIS layer mapping
3.20. Sentinel Playground
• Feature: Imagery Query Tool
• Setting: Programmatic search/filter and extraction for AOI
3.21. SkyFi
• Feature: Tasking and Imagery API
• Setting: Schedule custom acquisition for crop zones
3.22. Pixxel
• Feature: Hyperspectral Imagery API
• Setting: Onboard field geofence for automatic monitoring
3.23. TerraBella (Google)
• Feature: Automated Monitoring
• Setting: Configure alert preferences for potential losses

Benefits

4.1. Continuous, objective crop assessment for timely management decisions.
4.2. Reduction in manual scouting and increased early-warning accuracy.
4.3. Improved yield prediction, input allocation, and sustainability reporting.
4.4. Facilitates precision agriculture with up-to-date field variability mapping.
4.5. Scalability across multiple fields/regions with no on-ground infrastructure needed.