Enterprise API

Satellite analytics via API

Integrate field-level crop monitoring into your own platform. Plant health, water stress, protein content and more — delivered as images, GeoTIFFs and structured data through a single GraphQL endpoint.

GraphQL Playground
# Request plant health analysis
mutation
processPlantHealth(
polygonId: "abc-123"
startDate: "2025-06-01"
endDate: "2025-08-31"
)
Status
Result requestId
10 m
Pixel resolution
2–7 days
Revisit frequency
2018 →
Historical data from
14+
Analysis types
How it works

Four steps to satellite insight

The API follows a simple request → process → retrieve workflow. All communication happens through a single GraphQL endpoint.

1

Register a polygon

Define your field boundaries using GeoJSON coordinates. The API calculates area automatically.

2

Request an analysis

Call a processing mutation with polygon ID, date range and the analysis type you need.

3

Monitor progress

Track the request status while satellite data is downloaded and processed.

4

Retrieve results

Get back PNG images, GeoTIFFs and JSON statistics for every available date in your range.

Available analyses

Everything you need for precision agriculture

From standard vegetation indices to proprietary crop models — choose the analyses that fit your use case.

🌿

Plant Health (NDVI)

Assess crop vigor and identify underperforming zones using the Normalized Difference Vegetation Index.

processPlantHealth()
💧

Water Stress (NDWI)

Detect hydration issues early with the Normalized Difference Water Index before yield is affected.

processWaterStress()
📊

Vegetation Indices

General health indicators using light reflectance patterns to evaluate overall crop performance.

processVegetationIndices()
🌡️

Soil Moisture

Evaluate soil water status across the field to identify irrigation problems before they impact growth.

processSoilMoisture()
🧪

Crude Protein

Real-time protein content data for forage grass — essential for feed quality monitoring and harvest timing.

processCrudeProtein()
🌾

Dry Matter Content

Determine optimal forage harvest timing with satellite-derived dry matter estimates across the field.

processDryMatter()
🌱

Biomass

Measure above-ground biomass to understand crop density and estimate yield potential.

processBiomass()
🧬

Soil Organic Carbon

Assess carbon levels in soil organic matter — a key indicator of long-term soil health and fertility.

processSoilOrganicCarbon()
🥔

Potato Analyses

Predict starch content, yield and disease risk with proprietary models built for potato production.

processPotatoAnalysis()
GraphQL API

Query exactly what you need

The API is built on GraphQL, giving you full control over the data you request. No over-fetching, no unnecessary payloads — just the fields your application needs.

  • Single endpoint for all operations
  • Built-in API sandbox for testing
  • Self-documenting schema with Explorer
  • Token-based authentication
Register a polygon
mutation
generatePolygon(
label: "North Field"
benefactor: "farm-01"
coordinates: [[
  [10.42, 63.41],
  [10.44, 63.42],
  ...
]]
)
Status
Result
  polygonId
  hectares
Output formats

Multiple formats per analysis

Every analysis returns results in three formats so you can use what fits your pipeline best — visual overlays for dashboards, GeoTIFFs for GIS workflows, or JSON for data processing.

  • PNG — Color-coded field maps with legend
  • GeoTIFF — Geo-referenced raster data for GIS
  • JSON — Statistical summaries per date
Retrieve results
query
retrievePlantHealth(
polygonId: "abc-123"
startDate: "2025-06-01"
endDate: "2025-08-31"
)
colorlegend
png
tif
json
Technical specifications

Platform details

Key parameters and limits to keep in mind when integrating.

🛰️ Satellite imagery

Resolution10 × 10 meters
Revisit frequency2–7 days
Historical dataFrom 1 Jan 2018
Latest availableYesterday
Cloud coverFiltered automatically

⚙️ API limits

Max polygon size1 000 ha
Daily veg. index limit50 ha per polygon
Max time range1 year per request
ProtocolGraphQL over HTTPS
AuthenticationBearer token

📦 Response formats

Visual mapsPNG with color legend
Raster dataGeoTIFF
StatisticsJSON per date
Coordinate formatGeoJSON [lon, lat]
Date formatYYYY-MM-DD

🌱 Supported crops

Forage grassFull suite
PotatoStarch, yield, disease
All cropsVegetation indices
All cropsSoil analyses
All cropsWater stress
Good to know

Satellite imagery limitations

Satellite data is powerful but has inherent constraints. Understanding these helps you build reliable integrations and set the right expectations.

  • Cloud cover — Clear skies required for usable imagery. Cloudy days produce no results.
  • Resolution — At 10 m per pixel, individual plants are not visible. The data shows field-level variation.
  • Revisit gaps — 2–7 days between passes means fast-developing issues may be missed.
  • Correlation, not causation — The data shows where differences exist, not what causes them. Combine with field knowledge for best results.
Check data availability
query
retrieveSatelliteDownload(
polygonId: "abc-123"
startDate: "2025-06-01"
endDate: "2025-06-30"
)
availableDays
cloudyDays
unavailableDays
Documentation

Explore the full API reference

Detailed guides, code examples and technical reference for every endpoint.

Ready to integrate?

Get in touch to discuss your use case and receive API credentials. We typically respond within one business day.

Enterprise pricing · Custom quotas available · Dedicated support