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Sanjay Gangal
Sanjay Gangal
Sanjay Gangal is the President of IBSystems, the parent company of AECCafe.com, MCADCafe, EDACafe.Com, GISCafe.Com, and ShareCG.Com.

GISCafe Industry Predictions for 2024 –Blue Marble Geographics

 
January 31st, 2024 by Sanjay Gangal


By Patrick Cunningham, CEO, Blue Marble Geographics

Patrick Cunningham

Where is Geospatial Technology Headed in 2024

2023 was clearly the year of ChapGPT and Artificial Intelligence (AI) offerings.  The technology has taken the Internet and media by storm with the advent of some actually useful applications amidst a host of seemingly useless applications.  Granted, it’s still early on this front, so I reserve the right to update that take.  Perhaps the most prevalent use is the effect on search and automated support desk assistance, which is already widely rolled out and in use as of early 2024.  Try calling your credit card company or broadband provider, and you are most likely confronted with an AI-assisted automated helpline. If you visit their websites or use their consumer apps, you are definitely going to be confronted with the tech.  As a consumer, I have found some of these tools to be a bit more useful than in the past, but in general, my experience has been that I personally still prefer to talk with a person when I am in need of assistance. The nature of the assistance I seek when reaching out to support is usually not already available in help documentation or other searchable support tools. And though the promise of AI is that it can take that documentation library and infer the logic for the next step in support, I personally have not seen it. So the application of AI is really just another delay to what I want as a consumer. What the data will tell these companies as far as customer satisfaction with these types of tools remains to be seen.

The other big application of AI is that of writing. Ironically, as I sat down to write this article this year, the thought did cross my mind of asking ChatGPT to write up my takes on some of these topics, so in the end all I had to do was a little bit of editing. You’ll have to believe me when I say that I resisted that temptation. That said, it is becoming more and more common for professionals and non-professionals (think students) to take advantage of the speed and relatively decent accuracy of AI robots for writing. In my business, for the first time this past year, we have seen submissions for presentations and scholarship applications that were obviously written by an AI robot. This is a bit disturbing, but really no skin off our backs per se as there are still many high-quality, well-written, and human-driven submissions. However, this is a much bigger problem in academia.  But I digress.

The geospatial version of AI really has been focused on the burgeoning area of machine learning for data processing.  Geospatial software vendors have been focused on software tools that leverage AI for complex data processing challenges.  Data processing challenges that take a lot of person-hours to work through without assistance. The few offerings that have come to the market focus on providing new deep learning solutions in addition to classical machine learning methods. Applying these tools to land cover classification has shown much promise in both the potential speed of processing and the accuracy of results. Object detection, the goal of identifying discreet objects such as cars or buildings, is also becoming more accessible with the advent of ML and DL techniques. Taking a process that was once primarily manual and automating it is a promising, yet complex task. The promise of saving considerable time is balanced with a potentially acceptable loss in quality on a large scale. In the end, if these AI tools deliver, they save time-to-market for many geospatial data projects in a way that could be a game changer. Look for 2024 to see the release of more of these solutions and the next generation of these solutions focused on finding objects. Envision a workflow where the end-user is looking at a storm-ravaged data set or the aftermath of a natural disaster. These tools could eventually direct search and rescue efforts or speed up time for damage assessment. There are many other applications related to this that will appear in the coming years.
Blue Marble Geographics, of course, has been hard at work on these types of solutions. Our latest release of Global Mapper (September 2023) actually saw a related tool for training Lidar data from segmentation. This is not machine learning per se, but it is a tool that trains the software on what type of clusters of Lidar we want it to look for in a dataset. That tool essentially trains the software to look for point cloud structures as defined by the user, such as an airplane or particular building feature.  More on that here:
https://www.bluemarblegeo.com/how-to-train-a-custom-point-cloud-classification-in-global-mapper-pro/
Suffice it to say Blue Marble Geographics will be releasing more offerings in this area in 2024 and beyond, and I am sure the marketplace will see other vendors follow suit.

NATRF2022, where are you?

As we enter 2024, we are hopeful to see more near-final alpha/beta releases of the NATRF2022 and NAPGD2022-related updates from NOAA’s National Geodetic Survey. I have already provided a write-up about this back in 2020, so I guess my ability to predict these things is limited, but I am hopeful. These replacements to the well-known North American Datum models will be more accurate and current standards for coordinate referencing work that has historically been related first mainly to NAD27 (North American Datum of 1927), followed by NAD83 with a few other realizations after that. The new geometric reference frame will be called the North American Terrestrial Reference Frame of 2022 (NATRF22). With data all over North America in various realizations and a lack of a comprehensive transformation set to move data between the realizations to prepare for the eventual new standard, a new toolkit was needed: enter NADCON5. This toolkit, which is supported by Geographic Calculator, is the current basis of the national transformations between any realization within the National Spatial Reference System. It completely replaces and supersedes the original NADCON kits. This toolkit allows definitive transformation of data in any epoch of the NSRS, all the way back to the US Standard Datum (pre-NAD27). Additionally, it will be the tool that supports the forthcoming NATRF2022 models. Due to unforeseen delays in the 10-year project plan, governmental in nature, and also pandemic in nature, the toolkit is slated for release sometime in 2025. When that happens, Blue Marble Geographics software and staff will be ready to assist geospatial experts and novices alike.

Another point I like to bring up most every year is the progression of 3D geospatial.  For Blue Marble Geographics’s side of the geospatial software industry, this needs to be qualified.   Our primary users are surveyors, engineers, and architects —professionals who are looking for highly accurate, powerful, and analytical tools for mapping work.  So, when I discuss the emergence or growing popularity of 3D in this space, I am not just talking about the equivalent of a 3D view in Google Maps on your iPhone. I am talking about 3D modeling, data processing, and analysis. Our users are increasingly pushing the envelope around real-world applications for this type of surveying and engineering. Think landscape architecture, think as-built engineering, flood prediction, solar modeling and assessment, and wind modeling.  We are seeing more and more of our users creating mapping tools and products that, on the one hand, look like a video game but, on the other, offer super accurate and powerful 3D modeling. Some applications that we have seen a great uptick in include golf courses, pipeline and utilities, applied engineering, and more.   What is so compelling and interesting about these applications is that they span the usage case from simulation and gaming (think virtual golf) to mobile and location tools (think on-course apps for positioning and measuring) to as-built engineering and resource management (think watershed analysis and cut and fill to 3D rendering for planning and presentation). Where else will these types of comprehensive 3D geospatial workflows appear? We are very excited to see what our customers come up with in 2024.

About Author:

Patrick Cunningham is the President & CEO of Blue Marble Geographics Geographics (www.bluemarblegeo.com). Cunningham offers over two decades of experience in software development, marketing, sales, consulting, and project management.  Under his leadership, Blue Marble Geographics Geographics 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 an at-large member of the Univerity of Southern Maine Muskie Board of Advisors, a state-appointed member of the Maine Geolibrary Board, and a Maine Innovation Economy Board member.  He holds a master’s in sociology from the University of New Hampshire.

Category: Industry Predictions

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