Spiral Blue and Otus Intelligence Group have recently completed the first stage of a project involving analysis of ground movement data for Otus’ Surface Movement Risk Index. Otus has combined its synthetic aperture radar expertise with Spiral Blue’s machine learning and artificial intelligence capabilities to create an algorithm capable of monitoring ground movement impacting properties and public infrastructures across Australia. This is the first step towards developing a full Surface Movement Risk Index.
Currently under development, the Surface Movement Risk Index will provide a structural vulnerability score for more than 7.2 million properties across Australia. The index will make it easier than ever to understand and quantify how vulnerable a property is to potential structural damage, perform large scale analysis to assess the impact on property valuations over entire mortgage or investment portfolios, and understand insurance risk. The index is derived from advanced processing of satellite imagery where actual measurements are made off properties, creating a virtual survey network of millions of measurements. Coupled with machine learning and the integration of other non-spatial parameters, the Surface Movement Risk Index provides a clear picture and allows for efficient analysis and mitigation of the risk on your property or client portfolio while minimising the need for costly site visits.
Otus Intelligence Group is a Sydney based spatial intelligence firm playing a key role in democratising the use of advanced spatial intelligence. Otus was featured on the news for their work uncovering surface movement around Sydney’s WestConnex tunneling project.
Spiral Blue is a Sydney based Earth observation services startup that uses machine learning and artificial intelligence to provide next generation data analysis for industries including defence, utilities, and agriculture. They are building Space Edge – a computer for future Earth observation satellites that promises to significantly reduce costs of accessing high quality Earth observation data.