Complex financial information is hidden in plain sight all over the planet, according to James Crawford, CEO of Orbital Insight. The number of ships docked at a Malaysian port, even the color of a wheat field in western Nebraska, are actually signs, Crawford explained to me, visible indicators of economic activity, not just for a local region but for an entire global industry.
Seen this way, mundane landscapes previously deemed unworthy of analysis can, in fact, be meticulously—and profitably—scrutinized. This newfound appreciation is not aesthetic, of course, but fiscal, as even the growing shadows of a Chinese construction site can be interpreted as valuable clues about the strength of the underlying economy.
Crawford’s company, Orbital Insight, is one of a new breed of market-research firms pioneering the use of high-resolution satellite imagery. This is called geo-analytics, or geography crossed with the algorithmic firepower of Big Data. With access to satellite images—refreshed on a daily basis and available at a scale of one meter per pixel—companies such as Orbital Insight use artificially intelligent deep-learning algorithms to sort through the data and look for patterns.
Often this is just about change-detection: that is, looking for a particular pixel that has flipped from one color to another, thus indicating a new agricultural condition or the beginning of major construction work. Other times, it is all about quantity: methodically counting the number of cars parked outside a shopping mall in Minneapolis, or the trucks lined up outside a Chinese steel yard. In either case, it’s about combining machine vision with data science, or giving computational power a large enough visual dataset to work with.
Visual evidence captured by satellites is thus now subject to narrative interpretation for the purpose of extracting potential financial insight—and this potential financial insight can then be sold to paying customers. This, in fact, is Orbital Insight’s operating business model, marketing its geo-analytic expertise to hedge funds, U.S. government agencies, and nonprofits alike for what those groups might be able to learn from satellite data. Nonprofits, for example, might look for the level of water in a remote desert lake or threatened reservoir, or the true extent of a developing city as it sprawls into a nearby national park, for indications of what policies they might next pursue; hedge funds might see this same data and decide to short certain commodities.