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Current & Historical
crop health data

Get current and historical crop health maps, based on satellite data & AI models.

 

Detect insurance fraud, spend less time finding damaged areas on fields or verify claims remotely without having to set foot in the field

Our partners

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Automatic crop type detection and parcel delineation

Want to compare damages to another field?

Find fields close-by with the same crop type to compare the damages and access crop rotation data on a field level to assess whether correct crop rotation methodologies were implemented.

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Crop health maps before and after the claim submission

Was the crop in good condition prior to the loss event?

Verify submitted claim remotely with just a few clicks for indemnity payouts without doing on-field loss adjustment.

 

If physical inspection is needed, having data of least and most damaged areas, will give a fast understanding of which parts of the field to take samples from.

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Yield Estimation 2-3 months before harvesting

Our spatial yield prediction provides yield forecasts up to

2 months before harvest, predicting expected production, yield potential and synthesizing yield maps based on remote sensing data (Sentinel -1 & 2, meteo data and parcel meta-data including crop type, and soil parameters)

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Why us?

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Independent of the weather

CropCop is one of the few experts in the world in using SAR - radar satellite data. Optical satellites can not see through clouds thus SAR is needed to fill the data gaps.

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Global

Satellites are built for scale and provide the most cost-efficient worldwide data for field analysis

Real-Time and Historical data

Timely data available in just a few clicks.  

Historical data is a key resource when gathering proof for correct indemnity calculations.

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Science-Driven

CropCop is a spinoff company from an observatory research group. One third of our team members are PhDs having delievered 5 successful projects to European Space Agency.

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Contact us to learn more!

Let’s have a video call to find the best solution for you!

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