GISCafe industry predictions 2024 – Dewberry

By Mark Safran, Vice President, Senior Program Manager, Dewberry

Mark Safran

Geospatial Mayhem

I wake up in a sweat at two in the morning from a chaotic dream of hyperspectral pixels and pulses of light and synthetic aperture radar rays bombarding the earth like an alien space invasion.

Point clouds swirl through hydrographic canyons, scouring geomorphon rasters out of the way, leaving nothing behind but hydro-flattened rivers and silt choked layers of flood modeling clay.

That’s when things change from bad to worse.

I find myself stuck waist deep in data bricks, my arms held down by writhing, scaly python scrips, and coming at me from all sides, emerging like ghosts from an azure cloud, Storms an army of agents from the halls of AI, carrying RAG fitted LLMs and GeoAPIs.

Definitions: Artificial Intelligence (AI), Retrieval-Augmented Generation (RAG), Large Language Models (LLM), Application Programming Interface (API), GeoAPI: Open Geospatial Consortium (OGC)’s set of programming interfaces for geospatial applications

I’ve been thinking a lot about my predictions for the geospatial industry as we head into 2024. As I contemplated all of the technology advancements of just the past few years, I couldn’t land on just one. There are so many amazing things going on in our industry, new startups, new technology, new data sources, new ways to serve up data, new needs for interpreting data – it just never stops. So, one night I decided to stop thinking about what I wanted to write for this article and go to sleep. And that’s when I had the dream above. I wouldn’t exactly classify it as a nightmare, but I definitely vowed never again to predict things geospatial just before going to sleep!

My 2024 Prediction

Ironically, this ‘dream’ helped me sort through my prediction. I believe one of the biggest opportunities for geospatial growth in 2024 will come from the experts who can cut through this potentially chaotic geospatial landscape to deliver meaningful, specific, and actionable information to their clients.   While we will no doubt continue to see a steady growth in new sensors, software, and the latest AI algorithms, I predict companies and consultants who first start with a solid understanding of their clients’ requirements, and then select and integrate the appropriate data and technologies to meet those needs, will be the winners in 2024.

“Chaotic” Geospatial Landscape

If you are like me, you might be feeling overwhelmed by the myriad numbers of remote sensing and GIS-related technologies emerging over the past several years. Starting with data sources, earth observation satellite sensors such as synthetic aperture radar (SAR), hyperspectral, and now even lidar, are joining the countless electro-optical imagery sensors orbiting in space. And of course, we continue to see improvements in the capabilities of aerial and water (crewed and uncrewed) sensors to map our earth, lakes, and seas. Processing all this data into usable formats, or Analysis Ready Data (ARD), is another area where major investments have been taking place by both data providers and downstream companies with specialized software and processes. Finally, there are the companies focused on developing specific tools and applications to harness data for real-world requirements. Using GIS and image processing platforms, data is evaluated, integrated, and transformed into usable, decision ready solutions. This is an area where machine learning (ML) and artificial intelligence (AI) are drastically improving the speed and accuracy of our results. But, like my chaotic dream poem, all these data and tools and platforms can be daunting. Throw in the new AI capabilities and for our average customers and end-users, it can become a nightmare of geospatial mayhem.

This is where I believe we will begin to see a greater emergence of focused integrators.  Firms that don’t try to provide everything to everyone, but who select key problem areas based on both their knowledge of end user needs and their expertise on the specific pieces of the geospatial landscape.  In fact, we already see some client’s beginning to specifically ask for solutions in this manner.

As an example, the National Geospatial-Intelligence Agency (NGA), which has historically contracted out for the basic ingredients needed to help them perform their analysis mission (source imagery, SAR, foundation data sets, software and tools), is now, under a new program called LUNO-A, seeking contractors who take their knowledge of  specific mission needs such as monitoring facilities and high cadence transportation networks, or detecting changes affecting climate security and natural resources, and leverage geospatial technologies to create mission specific products. LUNO-A requests that contractors leverage non-classified data sources (e.g., SAR, EO, hyperspectral, lidar…), use remote sensing and GIS tools to delineate and produce mission required data in the form of objects, activities, etc., and deliver these products in ongoing schedule-defined increments.

We have noticed other federal, state, and local agencies also going beyond their request for foundation data such as lidar and imagery, or basic GIS capabilities such as creating web maps or developing field surveys, and instead requesting downstream derivative products usually comprised of numerous integrated sources. Some examples include 3D building datasets derived from lidar, elevation derived hydrography (e.g., the US Geological Survey’s 3DHP program) and impervious surfaces to support stormwater management. Many companies have designed their offerings around some of these needs, focusing on one of two key challenges and leverage the datasets, tools, and automated analysis needed to produce their products. A few examples include FloodMapp who offers “street-level flood intelligence delivered as a live mapping feed before, during, and after a flood…”; Climate X provides climate risk analytics; HaydenAI uses AI to provide mobile based safety applications for cities; and AIDash provides intelligent vegetation, sustainability, and utility encroachment systems using a combination of remote sensing and multi-source data fusion functionality.

It’s not just startups who are zeroing in on specific needs and building tools to meet those requirements. Focusing on a key challenge for the Federal Emergency Management Agency (FEMA) disaster response group, Dewberry recently built an integrated GIS solution comprised of multiple field data collection and visualization applications leveraging Esri’s Survey123, Workforce, FieldMaps, and Microsoft’s Power BI built into Dewberry’s DimensionalView™ platform that that led to a 100X increase in productivity for capturing field data and reporting.

Another trend is the collaboration between companies where one firm may have specific client understanding while the other may be developing technologies geared for wider use cases.  For instance, we recently partnered with AI mapping firm, Ecopia, to rapidly create high-definition vector datasets in support of Broadband mapping for various states as well as impervious, land use, land cover, data for NOAA’s Coastal Change Analysis Program (C-CAP). We’re even partnering with an exciting new satellite based lidar firm, NUVIEW, offering our expertise in data production, standards and specifications, and client applications such as forestry, hydrography, and coastal management to help refine their sensor technology.

Conclusion

In 2024, we will continue to see growth in space-borne sensors, new remote sensing systems, automation in SAR, EO, and lidar processing, as well as cloud optimization and advances in spatial AI, but there will probably be even a greater need from new startups as well as long-time client focused firms to understand and harness the power of geospatial science to better serve our clients.

Of course, I started with a poem, so I also need to end with a poem, but this time I turned to AI for help. Here’s the result when I asked ChatGPT to “write a short poem about AI and geospatial.”  Who do you think is the better poet?

AI Maps Earth, by ChatGPT

In circuits deep, where data flows,
AI’s mind, a map it stows.
Geospatial dance, pixels align,
Binary whispers, a coded design.
Satellites gaze, from skies they peer,
AI’s algorithms, crystal clear.
Mapping terrains with electronic grace,
Contours of Earth in a digital embrace.
Latitudes and longitudes, a symphony sung,
AI’s intellect, where knowledge is strung.
Geospatial ballet, pixels pirouette,
In silicon minds, the world they beget.

About Author:

Mark Safran, CP, GISP, is a Vice President and Senior Program Manager for the Geospatial, Mapping, and Survey Division of Dewberry Engineers, Inc., a leading AEC firm offering planning, design, and construction services nationwide. He leverages his expertise in remote sensing and geospatial technologies to support solutions for planetary health, global security, and scientific research.

Category: Industry Predictions

This entry was posted on Thursday, January 25th, 2024 at 1:46 pm. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.