Lower your basis risk - Manage exposure to risk - Improve operational efficiency - reach untouched markets
Smarter than rainfall data
Traditional index insurance models are often based on rainfall measurement or an NDVI proxy. The data quality of these measurements are accurate but often not sufficient to develop an insurance product. Rainfall data is only available from stations that can be dozens of kilometers away from the area insured. This data may be spatially unrepresentative, which leads to significant increases in basis risks for the underwriters. VanderSat’s signal has a high spatial resolution of 100m by 100m pixels. This results in lower basis risk for any insurer.
Not hindered by clouds
Other data services use satellite images producing normalized difference vegetation index (NDVI) pictures or proxies. These services are hindered by cloudy conditions, which create non predictable large data gaps leading to higher risks for the underwriters. VanderSat’s satellite services are not hindered by clouds and provide a stable data feed in any condition
Observed data, not modeled data
Observations of soil moisture represent the water content available for crops, and is thus directly related to yield. No assumptions on evapotranspiration and/or drainage need to be taken into account, like e.g. precipitation.
Long, consistent time records going back 18 years
Often more than 15 years of history are key to put current observations into perspective. Our archive goes back 18 years.
A leading science team
Our remote sensing data and analytics have been built by the world's leading scientists in the field of hydrological remote sensing and droughts.
We help you build and scale your solution across continents with technical assistance and business development.