InSAR starts the process of finding slow motion patterns of movement in the ground and in built objects, everywhere.
Our InSAR process provides:
Time series show how objects have moved since the previous measurement on a millimeter-scale.
Your data are updated as often as satellites acquire an image, up to 5 times per week or as often as you need for your business.
We monitor all kinds of assets, large and small – all over the globe.
High density measurements
Our maps contain up to 100,000 measurements per km2 over large areas. A quantum leap in effectiveness compared to conventional leveling campaigns.
Recordings since 1992
Over many areas you can access data going back to 1992 to assess long term motion of individual objects and the areas around it.
Access your data on our platform and assess where your assets are most at risk.
SkyGeo’s vision on InSAR data processing
‘SkyGeo’s mission is to help our customers, in the best way possible, to solve problems related to their assets, and to provide them with actionable intelligence. In the 15 years of our operational experience, we have learned that the technology of parameter estimation using InSAR is extremely tuneable.
This tuning results in many different potential answers.
At SkyGeo, we take pride in finding the most optimal and actionable solution.’
Without exception, this implies that we engage with our customers to thoroughly understand their need for specific intelligence, and we take all relevant contextual information into account. In other words, SkyGeo does not just “run the algorithm,” as this will always yield sub-optimal results.
Our team consists of experts in all relevant domains, ranging from geodesy, radar technology, geophysics, geology, geo-mechanics, civil engineering, and geo-informatics, mostly at PhD and MSc levels. This way, we are not only able to optimally compute the relevant parameters, but we can excel in data analytics and data interpretation as well.
Most importantly, we are able to minimize the risk of mis-interpretation, oftentimes with dire consequences. Yet, this is only possible if we thoroughly understand our customer’s needs.
Fit-for-purpose data, an example
One example of this ‘tunability’ of SkyGeo’s data processing capability is the ‘point-density/point-quality’ trade-off.
The quality of our estimates is only partly dependent on our methods and algorithms. Instead, the quality is mainly dependent on the characteristics of the Earth’s surface, which is obviously different for every square meter on the planet.
For example, we will not be able to provide reliable displacement estimates over a water surface using InSAR technology, which is a consequence of the physical characteristics of water surfaces in relation to radar waves, and not of algorithms.
Consequently, it is not possible to optimize both the quality and density of points. If more points are needed, this will typically come at the expense of their quality, and if higher quality points are needed, this will come at the expense of density.
There is no generic ‘right’ or ‘wrong’ in this trade-off. At SkyGeo we find the optimal trade-off for each particular use case . We do this based on our interaction with our customers, and it enables us to provide fit-for-purpose data for every use case.