Usage

Soil Organic Carbon

Estimate organic carbon content in the top 10 cm of soil using AI neural networks trained on satellite imagery. Results are reported in grams per kilogram (g/kg).

Overview

Soil organic carbon (SOC) is a key indicator of soil health, fertility, and carbon sequestration potential. This analysis uses AI neural networks to estimate SOC from satellite imagery, requiring that the soil was visibly bare (not covered by vegetation) during the analysis period.

Depth: 0–10 cm
Units: g/kg (grams of organic carbon per kilogram of soil)

Process Soil Organic Carbon

Unlike most analyses, processSoilOrganicCarbon() uses a leadingUpToDate parameter instead of startDate and endDate. The system automatically analyzes a 13-month period ending on the specified date.

GraphQL Mutation

mutation { processSoilOrganicCarbon( polygonId: "abc123-def456-ghi789" leadingUpToDate: "2025-08-31" ) { Status Message Result { requestId } } }

Important: The leadingUpToDate parameter triggers a 13-month lookback analysis using AI neural networks. The soil must have been visibly bare (no vegetation cover) at some point during this 13-month window for accurate results.

Retrieve Soil Organic Carbon

The retrieval query uses the standard polygonId, startDate, and endDate parameters:

GraphQL Query

query { retrieveSoilOrganicCarbon( polygonId: "abc123-def456-ghi789" startDate: "2024-07-31" endDate: "2025-08-31" ) { colorlegend tif png json } }

Response Format

Returns the standard four output types with SOC values in g/kg:

colorlegend — Static reference image for the SOC color scale.
tif — GeoTIFF raster files for GIS processing.
png — Visual PNG images showing carbon distribution.
json — Statistical summaries per date.

Best practice: Run SOC analysis after harvest or during fallow periods when the soil surface is most exposed. Fields with continuous crop cover may produce less reliable results.