Stories of traders vying to compete and finding new ways to beat the market and eke out profits are nothing new. But what has been interesting of late is the lengths and levels to which trading houses are now able to take the competition to, thanks to real-time data analytics supporting trading indicators and signals, purveyors of which include companies like Genscape and Orbital Insight. Orbital Insight, a startup specializing in analytics and real-time intelligence solutions, was featured in a recent Wall Street Journal writeup (Startups Mine Market-Moving Data From Fields, Parking Lots, WSJ, Nov 20, 2014). Genscape, a more established player, is another outfit that employs sophisticated surveillance and data-crunching technology to supply traders with nonpublic information about topics including oil supplies, electric-power production, retail traffic, and crop yield. Genscape and Orbital are but a couple of players in a broad developing market of “situational intelligence” solutions that provide the infrastructure and the intelligence for rapid real-time data driven decision-making. These two companies, however, are particularly interesting because they provide a view into the promise of geospatial and satellite imagery data and how it can be exploited to disrupt traditional operational and tactical decision-making processes.
Geospatial data is simply data about things and related events indexed in three-dimensional geographic space on earth (with temporal data being collected too for events taking place across time). Geospatial data sources include those of two types: GPS data that is gathered through satellites and ground-based navigation systems, and remote sensing data that involves specialized devices to collect data and transmit it in a digital form (sensors, radars and drones fall in this type). Geospatial data is of interest to private corporations and public entities alike. When triangulated with traditional data sources, personal data, and social media feeds, it can provide valuable insight into real-time sales and logistics activities, enabling real-time optimization. On the public side, geospatial data can provide valuable information on detecting and tracking epidemics, migration of refugees in a conflict zone, or intelligence of geopolitical significance. These are but a handful of use cases that can be made possible through the use of such data.
Once the preserve of secretive governments and intelligence agencies worldwide, geospatial and satellite imagery data is slowly but surely entering commercial and public domains, spawning an entire industry comprising outfits that build and manage the satellite and sensor infrastructure, to manufacturers and suppliers of parts and components that make up the satellites, and not least entities such as Orbital Insight that add value to the raw data by providing real-time actionable information to businesses. Orbital Insight, for example, leverages sophisticated machine learning algorithms and analysis against huge volumes of satellite imagery made available by DigitalGlobe’s Geospatial Big Data™ platform, allowing for accurate, verifiable information to be extracted. Outfits such as DigitalGlobe, Planet Labs, and Blackbridge Geomatics are examples of companies that are making investments to launch and manage the satellite and sensor infrastructure to collect detailed real-time geospatial data. Google, not to be left behind in the space race, jumped into the market with its acquisition of SkyBox Imaging earlier this year. SkyBox intends to a build a constellation of twenty-four satellites that will collect anything and everything across the globe. What’s more, Skybox, unlike other companies such as DigitalGlobe, intends to make available all the data it will collect through its satellite constellation for public and commercial use. But even companies such as SkyBox are not blazing the trail in the satellite business – there are numerous other start-ups that are vying to put into orbit low-cost and disposable nano satellites that will be much more smaller and cheaper to launch and manage. These developments are only going to create and open up an even wider range of applications for private and public use than has been possible heretofore.
These are still very early days for commercial application of geospatial and satellite imagery data, and exciting developments are still ahead of us. For one, the number and kinds of data sources that such applications may possibly need to be able to handle in the future will be exponentially higher: imagine a fleet of satellites, aerial drones, quadcopters and ground-based sensors all providing various kinds of data that could potentially be collated and flanged together. So too will new algorithms and ways of storing and manipulating streaming data at mind-boggling scales, all of which may require a level of thinking beyond what we may currently have.