For decades the lack of geospatial data was a barrier to geographic information system expansion and adoption. While obtaining high-quality spatial data continues to be a challenge, the problems of a lack of available data has quickly turned into the need to manage a glut of information. With the number of sensors and platforms growing exponentially, the data deluge will only increase in pace.
The ability of geospatial technology to make sense of all of this data will prove to be of wide benefit to increasing number of end users. However, the old model of mapping and spatial analysis professionals at the hub of insight won’t apply, instead there will be services and automated systems that feed a broader understanding of place.
It’s helpful to put the number of sensing devices and platforms into perspective:
Together, this collection proliferation is termed Big Data, and with all this data there are increasing interests to quantify these inputs to get a better awareness about operations and to increase efficiency.
Real-Time Data Hubs
Earth observation is of particularly importance right now, with increased populations, reduced resources, and visible global change in climate patterns. The uncertainty of these changes, and their impacts on humans and economies, is being met with a new and more ubiquitous view on planetary patterns. With today’s satellite constellations and airborne platforms capable of imaging the same spot on the earth multiple times per day, we get a much more complete picture of our planet.
This ability is being met with new approaches that are illustrated at a few different scales.
Together these different approaches show a need and interest to harness multiple inputs for a real-time awareness of change in order to mitigate damage and impacts.
New Insight on Design
The combination of sensors and systems, and 3D data capture at high precision, is also helping to revolutionize our management and understanding of our built environment. With precise models of the as-built environment, along with sensors that return details on resource use and other factors, we gain a better handle on the full lifecycle of our structures. Inputs inform designs that return the highest possible performance, and constant monitoring lets us achieve the optimal operation. In the middle the new connectivity with a model-centric workflow, has a great improvement on construction efficiency.
These sensored systems are manifest at many scales, from the better heating and cooling of buildings, toward the better management of utility networks, and all the way to smart cities that include intelligent grids and transportation. The adoption of a smart city approach is a global phenomenon that will spur wider proliferation of sensors to address a wide array of city-scale problems.
Looking back at the seeds of this new sensor and system approach there are a few industries and applications that foretell a whole new level of automation. With precision agriculture, farmers have long reaped the benefits of greater insight into local conditions at a fine scale through automated machines coupled to detailed digital models to improve crop yield. The broad geospatial industry can take cues from the progression in that sector as it’s moving from informing farmers toward the robotic automation of tools and systems.
Traffic sensors and feeds are perhaps the best example for the impact of real-time data coupled with nimble actors. Users of real-time traffic sharing applications such as Waze can expect great deal of time savings for their effort of monitoring and reporting conditions. However, here again we may see a large leap toward automation as today’s sensors have proven capable of driving cars without human control.
It will take years if not decades for the automation trend to take hold, if it does at all. In the meantime, the foundation that the geospatial technology industry has built to make sense of massive amounts of data is set to pay off.