Category

• Product Development
  

• Product Sales

• Underwriting
  

• Loss Adjustment
  

• Claims Handling

PRODUCT DESCRIPTION

A crop parcel is mostly uniformly treated by farmers and local weather conditions. Many fields however show a spatial variability in crop performance in the course of the growing season. Such variability is caused by a variety of natural and technology factors.

Where a multiyear recurrent variability is caused by differences in soil types, topography, weather micro-zones, crop growing technologies applied by the farmer, level of precipitation and irrigation access, while more abrupt and unexpected field variability could be caused by extreme weather events (e.g.: hail, storm, flood, drought, etc.).

PRODUCT SPECIFICATIONS

Main processing steps

Satellite information derived from Sentinel-2 can support the evaluation of historical natural field variability as compared to the near real time detection of less/better performing zones within crop parcels.

Input data sources

Optical: Sentinel-2

Radar: n.a.

Supporting data: for development: field yield samples  

Spatial resolution and coverage

Spatial resolution: 10 m

Coverage: crop parcel

Availability: On demand

Accuracy / constraints

Thematic accuracy:  The maps do not represent a physical quantity hence only a qualitative assessment is possible, e.g. by relating the maps with intra-field yield variability, detailed soil maps or crop damage maps. It is advised to perform an assessment with the service provider on a study area to evaluate the quality of the maps for a specific usage and region.

Spatial accuracy:  See Thematic accuracy.

Limitations

Challenging to detect the underlying processes of the intra-field variability: e.g. soil, agricultural management, crop damage.

Ancillary information on weather conditions and crop type are required to interpret the detected crop growth zones.

Frequency / timeliness

Frequency: static maps or updated regularly (+- weekly)

Timeliness: historical data or < 2 weeks

Delivery / output format

Data type: raster, vector

File format: GeoTIFF, Shapefile

Accessibility

Available on demand from EO service providers.

CHALLENGES ADDRESSED - USE CASE(S)

Product Development:

• Index insurance: Risk / crop modelling (Correlation of EO data with in-situ data)
• Index insurance: Relation between weather and impact on crop productivity
• Index insurance: Platform for crop health products
• Elaboration of crop profile: Field crops, vegetables
• Information on forest health and production at different temporal scales (realtime monitoring, historical development)
• Radar data (eliminated cloud cover effects)
• Risk exposure (product design and customer communication)

Product Sales

• Client Outreach
• Pre-contractual Consulting (show-case risk exposure)
• Greater acceptance of index covers by farmers
• Regular market penetration review
• Risk alerts

Underwriting:

• Seasonal portfolio monitoring
• Online platforms or easy-to-use interfaces integrating various data sources (vegetation stress, field boundary changes, comparison)
• Risk / crop zoning
• Actual crop health (vegetation)
• Global/Regional production trends (e.g. monitoring specific crop acreages of surrounding regions/countries)
• Procure better reinsurance terms/capacity from enhanced insurance practice
• Crop calendar and practices
• Regular assessment of risk pricing and product rating

Loss Adjustment:

• Workforce allocation and planning
• Benchmark physical field observations against yield loss detection (e.g. product calibration)
• Risk mapping against crop’s vegetation stages
• Increase credibility of loss adjustment (e.g. show EO data/visualization to support loss adjustment communication to farmer)
• Enhance field survey (better precision with EO data support)
• Detect crop damage at field level
• Assess crop damage at field level
• Distinct field heterogeneity with crop damage

Claims Handling:

• Identification of actual damage size (tons (volume) / ha (area) / price (yield value))
• Quality control assessment of claims before pay-out
• Fraud detection
• Obtaining timely, reliable and consistent data to speed-up the indemnity pay-outs