Inexpensive and crowdsourced remote sensing
In an article entitled “The Watchers”, David Samuels discusses a company seeking to deploy small satellites into orbit 500 miles (805 km) above the Earth. This company, Skybox, founded by ex-Stanford University students, seeks to shake up the commercial space imaging industry by doing two things: (1) Deploying smaller, less expensive satellites than what the commercial space imaging industry is currently using, the size of a dormitory room refrigerator, and (2) Using crowdsourcing for data classification. They seek to have ordinary citizens classify the incoming data, as well as do some classification themselves, even from images that the company has collected but does not sell. This could be the number of cars in every WalMart parking lot in the USA, the size of slag heaps outside the world’s largest gold mines in South Africa, and the rate at which the wattage along key stretches of the Ganges River is growing. These bits of information, they reason, are clues about the economic health of countries, industries, and individual businesses. Therefore, this information will be so valuable to investors, environmentalists, activists, and journalists, to name a few, that they will be willing to pay for the information. The company is working with the government of Russia for a launch vehicle and hopes to launch its first satellite this month, SkySat-1.
This story connects well with issues we raise in the book The GIS Guide to Public Domain Data, including data quality and resolution, military vs. civilian uses of data, crowdsourcing, and privacy. The resolution of the images returned from Skybox’s satellites will be comparable–less than 1 meter–to those from large commercial satellite imaging companies such as Digital Globe. However, the cost of constructing them should be considerably less and the size of the satellite itself considerably smaller. Skybox has added numerous advisers with connections in the defense industry “to avoid any military-industrial squelching of its technology before launch.” Relying on crowdsourcing to classify images is not a new concept, but what is new here is the scale at which it could be employed, and that it is embedded in the company’s business model. How standards will be established to assure data quality to potential purchasers of the derived information will be very interesting indeed. Lastly, the idea of inexpensive, high resolution, easy-to-deploy satellites imaging the planet has enormous privacy implications for those of us on the ground, whether from Skybox or for others who are sure to follow.