Using space based sensors VanderSat sees what cannot be seen.
VanderSat is a leading global provider of commercial high‑resolution soil moisture data, products and services.
Organisations across the globe are using our insights. From NASA and ESA to farmers, governments and universities.
The Dutch are well known for their water management skills. Water is in our genes. From the early middle ages onwards, we have reclaimed and defended land from the sea. A skill that goes hand in hand with water management, spatial planning, water supply and water quality. A history that revolves around adaptation to water, VanderSat is proud to build on that legacy.
Whether you operate regionally, nationally or globally. VanderSat provides the highest resolution, cost-effective and information-rich soil moisture data in the world. With daily observations you can make better, more informed decisions at any scale - whether you are monitoring crops, predicting the weather, performing predictive analysis, or preventing forest fires. We deliver key input at an unprecedented scale.
> 3500 organisations are already using our satellite based soil moisture data
VanderSat's proprietary method provides global NRT soil moisture data.
No models or assumptions:
VanderSat provides daily satellite observations with actionable results.
Using microwaves we are able to see through clouds and fog, so 'daily observations' really means daily.
Direct access to super computing facilities and infrastructure, crucial for satellite data processing and analytics
Putting things in perspective is key. We have a history of 38 years of satellite observed soil moisture data.
No models or assumptions; VanderSat provides daily satellite observations with actionable results.
A 62.500 times leap forward moving from 25x25 kilometers to 100x100 meters resolution
Meet the Team
Our team has over 40 years' experience of scientific remote sensing.
VanderSat’s proprietary methodology is taking advantage of data from a combination of satellites (multi-sensor) as well as different kinds of data (multi-frequency). This methodology combined with specifically designed algorithms is far beyond the current state-of-the art, even in the academic arena.
Thoughts, musings, and ruminations from VanderSat