A new document from the UN describes a 5- to 10-year vision in geospatial information management. Published by the UK Ordnance Survey at the request of the Secretariat for the United Nations Committee of Experts on Global Geospatial Information Management, the lead authors are John Carpenter and Jevon Snell from the Ordnance Survey. The document was commissioned in October 2011 and the first edition was just recently published.
The document is worth examining for all those who are in the field of geospatial technology. The language of the document is thankfully clear and concise, and quite thoughtful, something often lacking in documents such as this. I especially like sentences such as these, “A number of important technology‑driven trends are likely to have a major impact in the coming years, creating previously-unimaginable amounts of location‑referenced information and questioning our very understanding of what constitutes geospatial information.“
The authors have done an excellent job in recognizing the diversity of government, nonprofit, and private sector needs regarding geospatial information. The authors also strike a nice tone by encouraging partnerships and progress so that everyday decisions can be enhanced with a greater volume and a better quality of data as we move forward. Yet, they are realists and realize that this won’t happen overnight. Throughout, the bulleted paragraphs make the entire document accessible and easy to read and understand.
Chapters include key trends (cloud computing, open source, open standards), legal and policy (privacy, liability, funding), skill important in the future (education, extracting value, working with data), the role of private and non-governmental sectors, and the future role of governments. Many of these topics are those that are core to the themes of the GIS Guide to Public Domain Data book, and thus the Public Domain Data book provides a good introduction to and background for the UN document for use on the job or in instruction.
UAVs or UAS (unmanned aerial vehicles or unmanned aerial systems) are a hot topic this year. We have already discussed some of the privacy concerns in an earlier post, and for many, privacy will be the first thing that comes to mind when UAS are mentioned. However, for all the concerns, the increasing adoption of UAVs for capturing aerial imagery is heralding what Mike Tully described in his article for Sensors & Systems, The Rise of the [Geospatial] Machines: The Future with Unmanned Aerial Systems (UAS), as a ‘…..technological earthquake’. Although Tully’s prediction of Jetsonian skies cluttered with remotely operated UAS raises some other concerns, his description of a UAS-borne pizza delivery made me think how much better life could be for those of us who live just outside the current fast-food delivery area.
Pizzas aside, perhaps the most important change that’s coming with UAS is the deluge of information that’s soon to be available to mapping companies and geospatial professionals. Recent technical innovations in UAS design, computing power, data capture techniques and processing software have demonstrated that bulky and expensive sensors (such as manned aircraft) are no longer required to produce high-quality spatial data. Imagery from an increasingly extensive network of light-weight and affordable UAS equipped with cameras, will be continuously relayed to mapping service providers at a fraction of the cost.
Base maps previously updated on an annual or quarterly basis will be updated in a matter of hours, turning the once static background “wallpaper” into what Tully describes as an “operational layer”. This will provide end-users with up-to-date and high-resolution data and become an invaluable resource for those responding to emergency situations who were previously reliant on out-of-date and expensive mapping products. Although crowdsourced local information has helped in these situations, the quality of the data can be variable and in some cases proved too unreliable to be of any benefit.
To make optimum use of this new influx of data, new processes and analytical tools will be required to deal with both the volume and resolution of the data. Just when the dust seemed to be settling after the geospatial cloud revolution, it seems another upheaval is on the way.
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.