AtmosGrid — Planetary IntelligenceCOMMERCIAL PRODUCT
Agricultural landscape illustrating the crop decision workflow
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CROP & SEASON INTELLIGENCE

Plan the crop around the season—not the other way around.

Compare crop profiles against season, temperature, rainfall, soil and terrain context. Rank plausible options, expose missing inputs and build a shortlist that can be validated locally.

AVAILABLE · RULE-BASED SCREENINGSee how it works ↓
Illustrative agriculture imagery

THE DECISION IT SUPPORTS

Which crops deserve a closer look for this place and season?

The planner turns a season and every supplied condition into an explainable ranking. It narrows a broad crop catalogue without claiming that coarse weather data describes an individual plot.

Built for

  • Farm advisory teams
  • FPO coordinators
  • Agricultural platforms
  • District planning teams

WHY TEAMS USE IT

Turn broad data into a clearer next step.

Each result is designed to narrow a decision, show the inputs behind it, and surface what must still be checked locally.

01

Shortlist crop options

See crops whose seasonal profile aligns with supplied conditions on a clear screening scale.

02

Spot missing evidence

Expose absent soil, slope, land-cover or weather inputs before confidence is overstated.

03

Compare alternatives

Review crop duration and fit together for irrigation, rotation and harvest discussions.

04

Explain the result

Give agronomists and farmers a traceable screen instead of a black-box crop label.

FROM REGION TO FIELD

See where each signal fits.

Images illustrate the operational setting. They are not live observations; use source timestamps and local measurements for decisions.

Validate the shortlist in the fieldGROUND TRUTH

Validate the shortlist in the field

Variety, management history and crop condition can change the right choice.

Add measured soil evidenceSOIL CONTEXT

Add measured soil evidence

Measured pH and moisture improve the screen; unknowns remain explicit.

Place the field in its wider seasonREGIONAL VIEW

Place the field in its wider season

Weather and satellite products add context without pretending to be parcel measurements.

THE INFORMATION STACK

What goes in—and what it helps explain.

Availability is stated per input. AtmosGrid never converts a missing parcel observation into a made-up field value.

INFORMATIONSOURCEHOW IT IS USEDSTATUS
01SeasonCaller / local calendarLimits candidates to kharif, rabi or zaid profiles.REQUIRED
02TemperatureAtmosGrid GFS / callerChecks conditions against each crop profile.OPTIONAL
03Seasonal rainfallForecast or callerScreens water availability against indicative ranges.OPTIONAL
04Soil pHField test / health cardFlags crops outside the measured chemical range.CLIENT INPUT
05SlopeSurvey / future DEMScreens drainage, erosion and mechanisation constraints.CLIENT INPUT
06Land coverField record / future rasterChecks compatibility with cropping.CLIENT INPUT

A PRACTICAL WORKFLOW

From input to reviewable decision.

The workflow keeps model context, field evidence and human approval in their proper places.

  1. 01

    Choose season and location

    Coordinates provide context and are never used to invent field attributes.

  2. 02

    Add what is actually known

    Supply measured values and leave unknown values absent so they appear as gaps.

  3. 03

    Review score and confidence together

    A high score with low confidence is not a final recommendation.

  4. 04

    Validate farm constraints

    Check variety, irrigation, sowing window, rotation, pests and local advice.

  5. 05

    Record the human decision

    Keep the agronomist or farmer as the final decision owner.

HOW INFORMATION BECOMES USEFUL

Examples of decisions it can inform.

These are screening patterns, not automatic instructions. Operational thresholds and local advisories remain authoritative.

SCENARIO 01

Wheat or chickpea for rabi

Signal
Cool-season fit, rainfall range and measured pH.
Useful action
Prioritise better-matched options for field review.
Check before acting
Residual moisture, variety and sowing dates.
SCENARIO 02

Rainfed kharif portfolio

Signal
Rainfall and temperature fit across maize, millet, groundnut and cotton.
Useful action
Create a diversified shortlist for consultation.
Check before acting
Rainfall distribution matters as much as total.
SCENARIO 03

Crop proposed outside normal season

Signal
Season mismatch reduces eligibility.
Useful action
Escalate for protected-cultivation review.
Check before acting
Profiles do not model greenhouse conditions.

FOR PRODUCT TEAMS

A transparent API contract.

The response exposes gaps and limitations so an application can explain confidence instead of hiding it.

POST/api/v1/agriculture/india/crop-season-plan

Example request

{
  "season": "rabi",
  "meanTemperatureC": 20,
  "seasonRainfallMm": 500,
  "soilPh": 6.8
}
JSONdecision response

Example response

{
  "recommendations": [
    { "crop": "Wheat", "score": 90,
      "confidence": "screening-medium" }
  ],
  "dataGaps": ["terrain.slopePercent",
    "landCover.class"]
}

CAPABILITY BOUNDARIES

Useful now. Honest about what comes next.

Supported now

  • Eight India crop screening profiles
  • Kharif, rabi and zaid validation
  • Temperature, rainfall, pH, slope and land-cover scoring
  • Rank, confidence and explicit data gaps

Additional data required

  • Local variety and sowing guidance
  • Irrigation availability and water quality
  • Field history, pests and rotation constraints
  • Authoritative parcel-scale environmental layers

BUILD RESPONSIBLY

Use the result to focus attention—not replace field judgment.

Pair AtmosGrid’s regional weather context with local measurements, crop stage, variety guidance and qualified agricultural advice.

Read the API documentation ↗Open the India viewer ↗Explore all crop tools ↗