Quickstart: Your First Crop Health Analysis in 10 Minutes

This guide walks you through everything you need to run your first crop health analysis — from creating an account to reading NDVI values from a registered field. By the end, you’ll have a working API integration and a clear picture of how to interpret vegetation index results for your crops.

Create Your Account

Navigate to app.example.com and sign up with your email address. After registration, check your inbox for a verification email and click the confirmation link to activate your account.

If you’re joining an existing organization, ask your Admin to send you a team invitation from Settings → Team instead of creating a new account independently.

For a detailed walkthrough of profile setup and plan selection, see the Account Setup guide.

Get Your API Key

Once your account is active, generate an API key to authenticate your requests:

Log in to app.example.com.
Go to Settings → API Keys.
Click New Key, give it a descriptive name (for example, quickstart-key), and click Generate.
Copy the key immediately — it is only shown once.

Store your API key in a secure location such as an environment variable or a secrets manager. Never commit it to source control or share it in plain text.

Use your API key as a Bearer token in the Authorization header of every request:

Authorization: Bearer YOUR_API_KEY

Fields are the core unit of the platform — all imagery and analysis is tied to a field boundary. Register your first field by sending a POST request to /fields with a name, crop type, and a GeoJSON polygon defining the boundary.

curl -X POST https://api.example.com/v1/fields \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "North Corn Field",
    "crop_type": "corn",
    "boundary": {
      "type": "Polygon",
      "coordinates": [[
        [-93.123, 41.456],
        [-93.118, 41.456],
        [-93.118, 41.461],
        [-93.123, 41.461],
        [-93.123, 41.456]
      ]]
    }
  }'

import requests

response = requests.post(
    "https://api.example.com/v1/fields",
    headers={
        "Authorization": "Bearer YOUR_API_KEY",
        "Content-Type": "application/json",
    },
    json={
        "name": "North Corn Field",
        "crop_type": "corn",
        "boundary": {
            "type": "Polygon",
            "coordinates": [[
                [-93.123, 41.456],
                [-93.118, 41.456],
                [-93.118, 41.461],
                [-93.123, 41.461],
                [-93.123, 41.456],
            ]],
        },
    },
)

field = response.json()
print(field["id"])  # Save this — you'll need it for analysis requests

const response = await fetch("https://api.example.com/v1/fields", {
  method: "POST",
  headers: {
    "Authorization": "Bearer YOUR_API_KEY",
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    name: "North Corn Field",
    crop_type: "corn",
    boundary: {
      type: "Polygon",
      coordinates: [[
        [-93.123, 41.456],
        [-93.118, 41.456],
        [-93.118, 41.461],
        [-93.123, 41.461],
        [-93.123, 41.456],
      ]],
    },
  }),
});

const field = await response.json();
console.log(field.id); // Save this — you'll need it for analysis requests

A successful response returns a field object containing an id. Copy that id — you’ll use it in the next step.

You can also add fields visually using the map editor in the dashboard. See Connecting Fields for both the UI and upload methods.

Request Crop Health Imagery

With your field registered, request a vegetation index analysis by calling GET /fields/{field_id}/indices. Specify NDVI as the index and provide a target date.

curl "https://api.example.com/v1/fields/YOUR_FIELD_ID/indices?index=NDVI&date=2024-06-15" \
  -H "Authorization: Bearer YOUR_API_KEY"

import requests

field_id = "YOUR_FIELD_ID"

response = requests.get(
    f"https://api.example.com/v1/fields/{field_id}/indices",
    headers={"Authorization": "Bearer YOUR_API_KEY"},
    params={"index": "NDVI", "date": "2024-06-15"},
)

result = response.json()
print(result)

const fieldId = "YOUR_FIELD_ID";

const response = await fetch(
  `https://api.example.com/v1/fields/${fieldId}/indices?index=NDVI&date=2024-06-15`,
  {
    headers: { "Authorization": "Bearer YOUR_API_KEY" },
  }
);

const result = await response.json();
console.log(result);

The response includes per-pixel NDVI values, a field-level mean, and a breakdown of value distribution across the field boundary.

Imagery availability depends on satellite pass frequency and cloud cover for your region. The platform checks multiple satellite sources and returns the closest available scene to your requested date. See the note on refresh rates below.

Interpret Your Results

NDVI (Normalized Difference Vegetation Index) measures the density and health of green vegetation. Values range from -1 to 1 using this scale:

NDVI Range	Interpretation
> 0.6	Dense, healthy vegetation — crops are thriving
0.4 – 0.6	Moderate vegetation — generally acceptable, monitor closely
0.2 – 0.4	Sparse or stressed vegetation — investigate for nutrient deficiency, disease, or drought stress
0.0 – 0.2	Bare soil or severely stressed crops
< 0.0	Water, cloud shadow, or non-vegetated surfaces

Focus on areas where NDVI drops significantly below the field average — these zones are candidates for scouting and variable-rate intervention. Use the dashboard’s zonal map viewer to visualize the spatial distribution across your field.

Set up an automated alert in Settings → Alerts to notify you whenever NDVI in any field zone drops below your defined threshold. This removes the need to check imagery manually after every satellite pass.

Satellite imagery for most regions refreshes every 3–5 days under clear sky conditions. Drone or aerial imagery ingested manually is processed within 2–4 hours of upload. Cloud cover can delay availability — the API returns a cloud_cover_pct field in each imagery response so you can evaluate scene quality before acting on results.

Next Steps

Now that you’ve completed your first analysis, explore these guides to go deeper.

Crop Health Monitoring

Learn how to detect stress, disease pressure, and nutrient deficiencies using multi-index analysis.

Prescription Maps

Generate variable-rate application maps from your NDVI and NDRE results.

Vegetation Indices Reference

Explore all supported indices — NDVI, NDRE, NDWI, EVI, SAVI, and more.

API Overview

Browse the full REST API reference including endpoints, request schemas, and response formats.

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Quickstart: Your First Crop Health Analysis in 10 Minutes

Next Steps

Crop Health Monitoring

Prescription Maps

Vegetation Indices Reference

API Overview

​Next Steps

Crop Health Monitoring

Prescription Maps

Vegetation Indices Reference

API Overview

Next Steps