A little more than three years ago, I penned a column about geospatial technology frontiers. While acknowledging the expansion of GIS technology across more and more disciplines, the column aimed to summarize some of the main areas of research and development, where the vision has been clear for some time, but where technology limitations have hampered progress. The areas I outlined then all still seem to frame today’s challenges, so what kind of progress have we made?
Online mapping continues to be a driving force behind the industry, and if anything, its influence on R&D spending has accelerated. Online mapping isn’t a challenge as much as it is an enabler to realize meaningful advances more quickly. Online geospatial ecosystems have continued to evolve to support more integration, and the competition for winning online experiences has led to a great deal of improved data availability in a rather short time. Below are quoted main points from the original piece, along with an update through the lens of what’s happening and possible today.
“What’s still missing in geovisualization is the seamless movement between broad geography into realistic detail to include the interiors of buildings.” On this front, recent efforts are taking interior mapping very seriously, collecting data with 3D spherical cameras as in Google StreetView, and modeling social collection points with precision. Aiding these efforts are new handheld chipsets that promise precise positioning both indoor and out. While aimed at consumer interior navigation, the interest in creating augmented realities will spur greater investment in modeling and navigation tools, making the seamless visualization of our world at all scales an accelerated probability.
“The interoperability of data formats and models is the first step toward creating seamless models at all scales that also combine the intelligence of both BIM and CAD for the exciting concept of intelligent 3D models.” On this front, we haven’t seen much progress on the interoperability front between vendors, but we have seen great leaps in the integration capabilities within product lines. Major vendors are more seamlessly fusing their own environments as in Autodesk’s Infrastructure Modeler, Esri’s City Engine, and Bentley’s 3D Cities efforts. There are real end-user frustrations with workflow among and between tools that still need to be addressed, and standards efforts continue to make progress on many fronts, although no real breakthrough has occurred.
Temporal and Real-Time GIS
In the previous assessment there were separate line items for temporal, real-time GIS, and automated change detection. I’m combining all three of these areas in this column, because increasingly we’re talking about “dynamic” or “intelligent” maps that constantly evolve with new inputs, and that vision incorporates each of these areas. These aren’t just new names to frame a vision, they’re quickly becoming reality.
“Inroads are being made to incorporate live video and environmental sensors within a GIS framework, and to connect these ground inputs with space-based instruments for a deeper and broader understanding of events as they unfold.” High-profile advancements have occurred to integrate greater input during events, with citizen feedback through social media gaining great ground. The term social media wasn’t around three years ago, and its integration has proved the value of citizens as sensors. By incorporating these inputs with mapping, a great deal of clarity has been added to situations as they unfold.
The goal of “gaining insight by slowing or speeding up time to reveal earth processes, and more directly modeling the movement of Earth’s inhabitants” is still there and increasingly enabled by quicker access to data, and greater integration of data feeds. Deep temporal explorations are a ways off, but there’s certainly progress.
The Semantic Web
The idea of the semantic web where it “evolves as a medium for knowledge exchange to the point where it will understand the requests of both people and machines” is well on the way as the Internet of Things becomes reality. As in the previous assessment, location continues to be a key component of speeding interactions and trusting information, which are critical issues for the semantic web to become reality.
The previous column didn’t make much mention of sensors in the context of the semantic web, but they are an integral component. In sensing we’re seeing a great deal of activity in the development of low-cost sensing pods that can be added to existing environments seamlessly and wirelessly, making the proliferation of sensors so much easier than before. As in Twine, more sensors come with a programmable interface to freely customize to the the needed environment. In addition to this tool, there have been recent air monitoring tools as well as add-ons to smart phones that automate reporting. With greater access to sensors, and with increasing in means to process event-driven inputs (see Safe Software’s FME 2012), the semantic web is much closer today.
“Spatial reasoning and analysis are an important aspect of geospatial technology, yet most practitioners just scratch the surface of spatial statistics and the map algebra that can reward the analyst with great insight.” While we’re making maps more easily accessible, and even compartmentalizing map analysis in apps that automate some of the processing, deep map-based insights continue to be the exception rather than the norm.
“A need for much more research into the simplification and automation of spatial analysis in order for the geospatial toolset to reveal greater insights,” is an ongoing goal. Inroads are being made with the burgeoning area of location intelligence, and again the Web is a great enabler. The harnessing of the cloud for rigorous and compute-intensive analysis is certainly helping by reducing the cost and aiding access to capacity. What perhaps is missing most is evangelism of the types of questions that can be answered when addressing problems through the spatio-temporal lens.
It is instructive look back from time to time in order to realize the pace of advancement. Whole new types of functionality have been realized in a short time, and many more are around the corner. It holds true that while, “the current state of geospatial practice has come a long way since the tools were conceived, we’re still not scratching the surface of the amount of insight that can be unleashed” when the full potential of geospatial technology is realized.