agriculture monitoring

Agriculture: crop health & yield with satellite data

Find the right optical data, compute a vegetation index (NDVI), and turn it into a field-level map you can act on.

Step 01

Search “agriculture”

Type your need in the search box. You land on a topic page listing every dataset with imagery relevant to agriculture.

agriculture monitoring Search
Step 02

Compare datasets

Filter by Free/Paid and category. For crops, Sentinel-2 (10 m, free) is the go-to; PlanetScope (3 m, daily) adds frequency.

Free Free Paid
Step 03

Inspect the dataset

Open a dataset to check resolution, revisit, license and real sample imagery, and set your area of interest (AOI).

sample imagery Resolution Revisit License Price AOI
Step 04

Get the data

Download open data for free, or pull it programmatically via the JSON API (/api/dataset/sentinel-2).

Download API curl \ .../api/dataset/ { slug }
Step 05

Compute NDVI

NDVI = (NIR − Red) / (NIR + Red). Use the analysis-ready NDVI product, or compute it from raw bands. Low values flag stressed crops.

Input Analysis Output
Step 06

Deliver the map

Export the NDVI layer to GIS/BI as GeoTIFF and share a field-level map for scouting and variable-rate application.

Map output

What you get

A field-level NDVI map highlighting crop-stress zones for variable-rate management.

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