Model Card: Regional Abiotic Stress Risk Data Layer

Developer setup

• Authenticate with Cropwise – Learn how to authenticate your requests using your credentials.
• Model API Reference - WFS endpoint reference for the regional data layer (typeName=AbioticStress30km).

What it is

Overview

The Regional AgInsights Abiotic Stress Data Layer provides gridded, regional-scale environmental stress intelligence for major agricultural crops. It delivers daily stress severity assessments and historical stress risk profiles across broad geographies, enabling decision-makers — from sales representatives to agronomists — to understand spatial patterns of heat, cold, and frost stress without requiring field-level API calls.

This data layer is a regional, grid-based product within the Regional AgInsights product family. It transforms field-level Abiotic Stress model outputs into standardized 30 × 30 km geospatial layers, served via WFS. It is intended for situational awareness and decision support at territory, county, and country scales.

The data layer does not replace field scouting, local agronomic expertise, or on-ground verification of stress conditions.

Inputs and Outputs

Inputs (generation-side)

At the batch generation level, the underlying Abiotic Stress model is executed per grid centroid with the following inputs:

• Grid centroid coordinates (latitude and longitude), derived from the 30 × 30 km standardized grid
• Crop (corn, soybean — depending on geographic scope)

Optional parameters applied at the generation layer include:

• Severity prediction period (start and end dates) — defaults managed by the batch orchestration pipeline
• Historical period for risk computation — number of years used to calculate stress frequency

Outputs

Each grid cell exposes the following attributes per crop stress type:

• Daily stress severity index (0–9): Quantifies stress intensity based on actual weather data (up to today) and 5-day forecasted conditions.

  • 0 = no stress
  • 9 = extreme severity

• Aggregated stress risk (%): Reflects the historical frequency of stress events above a defined threshold, projected onto the upcoming season timeline.

  • 0% = stress threshold was never exceeded at this timing in the historical period
  • 100% = stress threshold was exceeded every year in the historical period

Stress types available:

• Diurnal heat stress
• Nighttime heat stress
• Frost stress
• Diurnal and nighttime cold stress

How it works

Algorithm principles

The underlying Abiotic Stress model quantifies daily stress intensity using crop-specific physiological thresholds:

• Heat stress (diurnal): Monitors daytime temperatures against crop-specific upper thresholds. Excessive heat disrupts photosynthesis, impairs pollination, and reduces grain filling.
• Heat stress (nocturnal): Assesses nighttime temperatures that disrupt plant respiration and metabolic recovery, reducing biomass accumulation and yield potential.
• Cold stress (diurnal and nocturnal): Evaluates temperatures below optimal ranges but above freezing thresholds. Suboptimal temperatures slow metabolic processes, delay development, and reduce photosynthetic efficiency.
• Frost stress: Detects temperatures near or below crop-specific freezing tolerance thresholds, which can cause growth impairment or permanent tissue death.

Generation (batch → grid)

Regional AgInsights generates predictions on a standardized 30 × 30 km grid by:

1. Constructing a coordinate set of grid centroids filtered to agricultural areas via cropland thresholds.
2. Executing the Abiotic Stress API for each centroid with configured crop and temporal parameters.
3. Managing execution metadata (timestamps, model versions, success rates) with retry logic and rate limiting.
4. Publishing results as geospatial layers.

Serving (consumption)

Layers are served via OGC-compliant WFS endpoints. To obtain the Abiotic Stress layer, use the following typeName:

• AbioticStress30km

Consumers can query features using CQL filters and request JSON or CSV output formats. Authentication is handled via OAuth2 client credentials.

How to use

Intended use

• Sales: Territory-level stress context for customer conversations, campaign targeting, and product positioning (e.g., biologicals, stress-tolerant varieties).
• Marketing / Strategy: Regional opportunity analysis, campaign timing aligned with agronomic stress patterns.
• Supply chain: Incorporate regional abiotic stress signals into planning and logistics.
• Agronomy / R&D: Validation, monitoring, and iterative improvement of stress models across geographies and seasons.
• AI / Data Science: Upstream signal for Cropwise AI natural language queries and downstream predictive workflows.

How to interpret insights

Daily stress severity index

Aggregated stress risk percentage

Limitations

• Predictions are generated using gridded daily weather data (the underlying model uses ~10 × 10 km weather data), which may be inaccurate for specific locations.
• The 30 × 30 km grid resolution does not capture microclimates, sub-field variability, or localized topographic effects.
• Stress thresholds are crop-level and are not specified at the genotype or variety level.
• The layer estimates stress conditions based on weather data; it does not directly measure crop growth, physiological damage, or yield impact.
• Spatial masking rules (cropland thresholds and "main growing regions" definitions) are subject to finalization.
• Temporal conventions (ISO week vs. rolling 7-day) for weekly aggregations are subject to finalization.

System information

Data sources

• Gridded daily weather data (ERA5T and forecasted weather data)
• Crop-specific physiological threshold parameters (managed by agronomy experts)

Update frequency

• Severity: Daily (actual weather up to today + 5-day forecast)
• Risk: Weekly

Spatial and temporal resolution

• Grid size: 30 × 30 km (Regional AgInsights product resolution)
• Temporal granularity: Daily for severity; weekly for risk

Serving endpoint

• WFS: GET /regional-aginsights/v1/wfs?typeName=AbioticStress30km
• Output formats: JSON (GeoJSON FeatureCollection), CSV
• Authentication: OAuth2 client credentials via /oauth/token

Geographic Scope, Crops, and Availability

Filtering & Querying via WFS

The Abiotic Stress layer is queryable via a WFS endpoint using CQL filters. Below is an example request and the available filter keys.

Example query:

curl --location '{BASE_URL}/regional-aginsights/v1/wfs?typeName=AbioticStress30km&outputFormat=json&cql_filter=country_code%3D%27US%27' \
--header 'accept: application/json' \
--header 'Authorization: Bearer $ACCESS_TOKEN'

Note: String values must be wrapped in single quotes ('). When used in a URL, the filter must be URL-encoded (e.g., = → %3D, ' → %27).

These keys can be used in the cql_filter parameter to query the table for Abiotic Stress:

Last update: 20/05/2026