AINTELLIGENCE
Farm monitoring

Farm monitoring

Continuous visibility over cocoa plantations using Sentinel-1 radar, Sentinel-2 (including vegetation indices such as NDVI), high-resolution drone imagery where you provide it, and protected-area context from WDPA. Flag stressed areas early and send teams or drones only where it matters—with high confidence in our screening layer.

Screening focus
Plantation health overview
Typical revisit
Sentinel-2 cadence
Core inputs
Sentinel, drone, WDPA
Outputs
Maps, scores, alerts
What you get

Inputs we use

We name the data sources that feed monitoring; detailed processing stays on our side.

Sentinel-2 optical

Regular revisit for canopy greenness and vegetation index trends across your polygons.

Sentinel-2

Seasonal change signals

Compare current observations to typical patterns for the same period and crop.

Seasonal

Sentinel-1 radar

All-weather coverage when clouds block optical sensors.

Sentinel-1

Drone imagery

Optional higher-resolution flights you upload tie field truth to satellite context.

Drone

WDPA protected areas

Context on nearby protected land alongside your farm boundaries.

WDPA

Alerts & prioritisation

Notifications when a plot needs a closer look—so agronomists spend time on the right farms.

Operations
Workflow

How farm monitoring works

Upload farm boundaries

Submit GeoJSON for one plot or many. We pull the latest suitable Sentinel passes and align optional drone data you add.

Monitoring run

Our platform combines the inputs above into a health and anomaly view—without publishing internal model or pipeline details here.

Prioritise field action

Use maps and alerts to route scouts or drones. When imagery suggests disease, continue with the disease detection module.

Get started

Start farm monitoring

Upload boundaries to begin a monitoring run for your plots.

Start monitoringNext: disease detection when plots need a closer look