GISCafe Voice Industry Predictions for 2021 – Part 5

Better cloud and remote GIS tools, virtual and augmented reality have now blossomed in response to the demands put forth on our industry by the pandemic. Gaining access to analysis-ready geospatial data at a scale and with granularity never before possible is on the horizon. We thought we already knew about digital twins, but now we find out they are finally born? This is the way of the future and much more, we learn by checking in with companies Blue Marble and Omnisci, two companies with a finger on the pulse of what to watch for in geospatial.

Patrick Cunningham, President and CEO, GISP, Blue Marble

Blue Marble

Where is Geospatial Technology Heading in 2021

Like all who would sit down and write their predictions for 2021, I am immediately drawn to recall what my predictions were for 2020. Certainly, they did not contain an iota or inkling of the pending global pandemic and its effect on all industries.  Widespread stay-at-home orders and dramatic changes in the way economies all over the world functioned by the spring of 2021 had both direct and indirect impacts on the day-to-day operations of geospatial businesses.  Perhaps the most visible was the almost immediate focus on COVID-19 outbreak maps, predictive epidemiology in GIS, and a sense of GIS professionals trying to do their part to warn and report for the greater good.  This effort immediately reminded me of what is often considered to be one of the first examples of  GIS analysis: mapping the cholera outbreak of London 1854 by John Snow (link: https://en.wikipedia.org/wiki/1854_Broad_Street_cholera_outbreak).

Just as I stated at the beginning of 2020, the GIS industry is continuing to ride a wave of interest in drone or UAV data collection and processing.  This will continue to move forward as the technology is compelling, affordable, and advantageous to local project work.   Software companies such as Blue Marble Geographics are working on products that expand the data processing capacity and the quality of the derivative 3D geospatial datasets from the ‘Structure from Motion’ process.   This effort and interest will continue in 2021.

Related to 3D GIS is the increased, some would say commonplace, usage of virtual reality (VR) and augmented reality (AR) gaming devices in the consumer market.  The popularity of these gaming devices was evident in their robust sales during the holiday season.  There has also been an increased acceptance and growing popularity of video gaming as a form of organized competition.  Gaming is now recognized as a  “sport” and is even being offered in schools in conjunction with traditional sports such as soccer or basketball.  This expansion of the gaming market tied to the increased popularity of VR and AR in the consumer market will affirm GIS software companies’ original efforts in the area.  This trend is analogous to the Apple iPhone entering the business market.  When the iPhone was originally released, it was considered a consumer-focused product, however business professionals loved it, and eventually, the iPhone overtook the Blackberry as the dominant mobile device for professionals.

GIS software companies are beginning to recognize the potential applications of VR/AR GIS but have been hesitant to release tools or products for this area of the market.  With the expansion and acceptance of these devices in the consumer market, they will see the affirmation they need to focus on software development efforts in this area.  Look for more GIS software releases focusing on AR/VR by the end of 2021.

The pandemic had another major effect on business in 2020: the rapid transition to a remote workforce.  Companies such as Blue Marble are now operating almost 100% remotely.  This change in the business landscape has accelerated the development of better cloud and remote GIS tools.   Blue Marble quickly responded to this challenge by adding remote desktop licensing to our software to provide remote customers easy and full access to their essential software tools.  Blue Marble also released the first generation of a cloud version of the Geographic Calculator, coinciding with an update to GeoCalc Online.  Look for more cloud versions of GIS and remote-enabled tools in 2021 and beyond as a result of changes in workforce dynamic brought on by the pandemic, as these changes will have long term effects.

Finally, we all hope that 2021 will also be known as the year that the pandemic ended.  With the worldwide roll-out of vaccines well underway, there is cause for optimism, and that is something we can all use more of in the coming year.

Patrick Cunningham, President and CEO, GISP, offers over two decades of experience in software development, marketing, sales, consulting, and project management.  Under his leadership, Blue Marble has become the world leader in coordinate conversion software (the Geographic Calculator) and low-cost GIS software with the 2011 acquisition of Global Mapper. Cunningham is Chair of the Maine GIS Users Group, a state-appointed member of the Maine Geolibrary Board, a member of the NEURISA board, a GISP, and holds a master’s in sociology from the University of New Hampshire.

Dr. Michael Flaxman, Spatial Data Science Practice Lead, OmniSci

Omnisci

GeoPredictions for 2021

OmniSci is a GPU-based analytics framework which converges spatial and temporal analytics for big data.  It is used for problems too big for conventional GIS, typically involving datasets with hundreds of millions to billions of geographic features.  This gives us some insights into the kinds of things people will want to do as such datasets become more common.  I would highlight three trends to watch in 2021: the rise of geoML pipelines fed by high resolution datastreams, standardization of discrete global grid systems, and the combination of these elements in interactive digital twin systems.

The Year of geoML

Machine learning is being applied at scale to the tasks of image classification, and there have been impressive advances last year in both the capabilities of such systems, and in “MLOps” which bring them solidly into production as “analysis ready data.”  From a GIS analyst’s perspective this supports the building of systems which are always up-to-date, and thus of considerably higher operational value than conventional “one off” map or project-based workflows.  As one example, I’d expect the majority of forest analyses to start being based on annualized or even monthly ML classifications.

A great example of this is the “California Forest Observatory” which provides 10m Sentinel-2-based forest height and condition assessments.  If you were planning any sort of analysis based on forest cover, would you pick 5-year-old Landsat-TM-based 30m data, or this year’s data at 10m?  On the commercial side, I’d similarly call out Ecopia which applies similar technology to high resolution urban imagery.  For those needing customized pipelines or more specialized data as service, there are now specialized open source projects (Solaris, Open Data Cube), and commercial services (Up42, Tesselo) that let you perform image cleanup and ML data extraction on demand.

Standardized DGGS See Widespread Adoption

Discrete global grids, despite their awkward name, are an important advance which I expect to take off in 2021.  Uber’s h3 system, which is based on hexagons, is a major contender in its own right.  The h3 system supports very-efficient access to equally-spaced neighbors, which makes it particularly powerful for GPS accessibility analysis at scale.  However what makes widespread much more likely is its incorporation within a broader open source project with serious multivendor support – the Placekey initiative.

There have been numerous prior attempts at generating systematic and unique global place names, and none have quite made it into common practice.  PlaceKey may have finally got this right.  PlaceKeys include both a “where” and a “what” component, with the “where” provided by an h3 encoding at fixed scale.    The “what” component currently includes addresses and sub-addresses, which provides a pretty good starting incentive for PlaceKey use.  Since PlaceKeys are “just a key” to a relational database, you can essentially get highly-efficient address lookups for the price of a simple join.  Since fast joins are built into pretty much every database on earth, without even requiring geodatabase support, this seems easy to adopt and easy to use.

Digital Twins are Born

This concept has been bouncing around since at least Al Gore’s “Digital Earth” vision setting.  The idea is that geodatabases are available in which features represent real-world objects rather than class abstractions, and that the current condition of those features are continuously available as attributes.  For example, think of a data layer not of every forest patch, but of every tree with a time series of observations of its condition.  The databases built this year will increasingly have these characteristics.  For example, consider Microsoft’s building footprint datasets, available now as open data.  Rather than to scope GIS systems operating on abstractions of buildings and address locations, I think systems built this year will simply use the granular data as their primary source, and build courser scale aggregations or abstractions on-demand.

At OmniSci, we have a number of customers across completely different domains who are adding near real time granular environmental information to their business information systems.  Utilities are monitoring individual trees around their powerlines for strike tree and fire risk. Telcos are modeling ‘clutter’ including both buildings and vegetation at 1 meter resolution to better model 5g cell phone signal propagation.  Logistics firms are integrating driver behavior with live and projected weather data into their routing and planning solutions.  Despite different business use cases, knowing what’s going on around your assets is increasingly important, and modern tech stacks are automating the monitoring pipelines.

Overall, this will be a very exciting year for geospatial practitioners.  We will be gaining access to “analysis-ready” geospatial data at a scale and with granularity never before possible.  This will bring some friction with legacy tools and methods not designed to handle these data and analytic volumes gracefully.  But the reward will be that our work will be of considerably-higher business and operational value to more people.

Dr. Michael Flaxman, Spatial Data Science Practice Lead, OmniSci

Dr. Michael Flaxman’s primary research interest is in participatory tools for spatial simulation modeling as applied to the planning and design of cities and regions. He has served on the faculties of MIT, Harvard and the University of Oregon. Dr. Flaxman has practiced GIS-based planning in 17 countries, including one year as a Fulbright fellow in Canada. Dr. Flaxman previously served as industry manager for Architecture, Engineering and Construction at ESRI, the world’s largest developer of GIS technology. Dr. Flaxman received his doctorate in design from Harvard University in 2001 and holds a master’s in Community and Regional Pl

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