UAV/UAS: The next influx of spatial data

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data and become an invaluable resource for those responding to emergency situations who were previously reliant on out-of-date and expensive mapping products.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.