BLOG
—
Top Geospatial Trends of 2020
By Dr. Qassim Abdullah, Chief Scientist, Woolpert
Let’s talk trends again—geospatial technology trends, that is. In this year’s edition of my annual blog, I’ll review the trends I forecasted at this time last year, note how those predictions panned out, and project how these and other trends are expected to evolve throughout 2020 and beyond.
Data Democratization: Big Data Needs Big Tools
Data democratization, in its simplest definition, provides streamlined access to technical expertise. It takes complex topics, from machine learning or application development to sales processes or economic analyses, and shares them in a way that can be easily understood without extensive experience, skills or training.
Big data and data science play a pivotal role in data democratization. Last year, I highlighted how location-based applications like smart buildings, self-driving cars and crowd sourcing collect valuable information around the clock. I noted that this big data can be used to create new GIS databases or update existing ones in real time to yield benefits to diverse sectors that include planning, construction, utilities, transportation, government and energy.
“What’s lacking are the analytical and modeling tools needed to mine, extract and convert such information to knowledge,” my younger self wrote. “We are about to witness energized activities around the development of these tools, which surely will transform big data into something new and powerful.”
The only way to grow in this field is by adopting the latest advances in the fields of machine learning, artificial intelligence and deep learning to shorten the time needed to mine data and transform it into something else. Unfortunately, over the last year, the geospatial community did not make many advances to develop tools for the use of big data. Although I believed at the time that our industry was ready to digest, embrace and benefit from this concept, over 2019 it became apparent that the equation of how data meets algorithm and turns it into a decision has continued to evade the geospatial community. The community needs more time to digest such concepts.
To address this chasm and to spur the development of big data tools, I believe the geospatial community should take a cue from Google and Amazon. These giant tech companies are proactively utilizing big data and sharing it with users, especially in the security and social media sectors. Google and Amazon offer advanced machine learning tools and applications that decrease the learning curve for users, effectively eliminating the need to have specialized skills and tools to excel in this field.
Think Small—Miniaturized Sensors
Also last year, I envisioned the geospatial industry would benefit from the investment of companies like Google, Apple and LG by advancing highly capable miniaturized imaging and lidar systems for mapping applications.
Here again though, we witnessed the very slow (practically negligible) adaptation of these tools for mapping applications. The limited, laser-based tools the smartphone companies implemented showed that no serious attempt was made by these high-tech giants to provide their users with a miniature lidar system.
There are advanced imaging systems in the Apple iPhone 11, for example, that have the potential for indoor and close-range 3D mapping. But, while these cameras are very advanced, they still lack the needed software for 3D modeling.
On a positive note, miniaturized lidar systems developed to serve the auto industry are accelerating faster than the ones targeted by the tech companies. A system like Leddar Vu8, an affordable and versatile lidar sensor module developed by LeddarTech, looks likely to provide effective mapping with drones.
I am optimistic that the companies that have invested in patents for advanced lidar systems will eventually develop and implement miniature lidar systems in smartphones. They just didn’t answer the call in 2019.
Living in the Cloud
Last year, I stated how “we continue to witness impressive growth in high-performance computing networks.” This predication was right on.
Progress was made by agencies throughout 2019 to move their computing powers into the cloud, and many more companies are offering cloud data hosting and processing. Whether through Amazon, Google or other cloud providers, users and developers are provided with sophisticated platforms like serverless cloud computing. These platforms allow developers to run apps and services without having to manage and operate costly and complicated server infrastructure.
This past year also saw an increased demand and additional offerings for data cloud hosting and processing services. Woolpert, for example, announced its STREAM:RASTER™ service. The true power of STREAM:RASTER, based on the serverless cloud computing architecture, is its ease of integrating users’ favorite geospatial applications, map libraries and GIS clients, like ArcGIS Online, ArcGIS Desktop or QGIS.
Lidar, Lidar, Everywhere
In 2019, lidar manufacturers continued to make huge technological advances, both in traditional linear-mode lidar and in new technologies, like single photon. These breakthroughs will continue this year, offering more efficient data acquisition and more affordable lidar data to support national programs such as the U.S. Geological Survey’s 3D Elevation Program (3DEP).
The improvements in lidar data density, quality and accuracy will continue to attract new users and new applications in 2020. This will be especially true in the engineering and 3D modeling sectors. Last year, we observed some activity in advancing unmanned aircraft system (UAS) or drone-based lidar data acquisition. A few lidar manufacturers either added UAS-based lidar systems to their production lines or added new lidar models. Quanergy Systems is the latest company to enter the drone-based lidar market, competing with RIEGL and Velodyne Lidar with their newest lidar sensor, the M8.
Other companies are increasingly integrating drone-based lidar systems to compete with established companies, including Phoenix LiDAR Systems, YellowScan and LiDARUSA. The most recent firm to do this is GeoCue, which last year debuted its True View 410. The True View 410 is based on Quanergy M8 technology and work by Routescene, which created its unmanned aircraft vehicle (UAV) LidarPod based on Velodyne technology.
Marrying BIM to GIS
Also last January, I stated that building information modeling (BIM), virtual reality and augmented reality are becoming an integral part of the digital construction revolution. Although there was not a major breakthrough here in 2019, these technologies have continued to grow steadily.
For the mapping and geospatial industry, these tools need to be augmented with efficient GIS databases and applications to reach their full potential. In 2020, the trend will be integrating BIM with GIS. This will be driven, at least in part, by the fast growth in indoor and outdoor lidar scanning.
A “Smart” Revolution
Recent technology trends enable us to better manage and protect our facilities, roads and infrastructure. As was evident prior to last year, during 2019, and now after, smart technologies will continue to escalate in multiple directions and for many applications.
Specific to this year, the concept of smart cities and intelligent transportation systems (ITS) will become bigger in utility and transportation communities. This growth will gain momentum with the expansion of big data, machine learning and deep learning.
As autonomous driving continues to make strides and more car manufacturers go down this road, there will be greater need for technology to understand infrastructure details and conditions using artificial intelligence and geospatial data. The geospatial community and the architecture and engineering industries are poised to earn a substantial market share of the services needed to support the smart revolution, and this will help drive these technologies.
Mapping-as-a-Service (MaaS)
Speculated data acquisition, on-demand geospatial data and data subscription services will continue to grow in 2020 and throughout the decade. This data offering will become the most logical and affordable avenue of geospatial data acquisition, especially for agencies who need updated coverage on a regular basis.
Demand for MaaS has created an upward trend of subscription-based, imagery-based products by companies like Geomni, Near Map and Hexagon—the latter through its HxGN Content Program. This demand also has generated partnerships to support this deliverable. In 2019, Woolpert and iXblue Sea Operations division, part of iXblue Group based in France, formed a strategic partnership to provide aerial mapping services to clients in Australia, New Zealand and across the South Pacific. Under this partnership, Woolpert and iXblue will collect, process and deliver airborne digital imagery, topographic lidar and bathymetric lidar operations from helicopter and fixed-wing platforms to provide custom solutions to commercial and government clients.
These geospatial trends will continue to blossom throughout 2020, as the need for advanced technologies continues to rise. I look forward to seeing what the year will bring.
Qassim A. Abdullah, Ph.D., PLS, CP
The Woolpert chief scientist and senior associate has more than 40 years of combined industrial, R&D and academic experience in analytical photogrammetry, digital remote sensing, and civil and surveying engineering. When he’s not presenting at geospatial conferences around the world, Qassim teaches photogrammetry and remote sensing courses at the University of Maryland and Penn State, authors a monthly column for the ASPRS journal PE&RS, and mentors R&D activities within woolpert_labs.
Share this Post
