By Seb Lessware, CTO (Chief Technology Officer), 1Spatial

Seb Lesswar

What lies ahead for 2024? It’s all about Geospatial AI: Navigating the Future of Automation, Drones, and Data Aggregation
I predict that all the other predictions will focus on AI (Artificial Intelligence) and it’s hard not to with so much new hype last year. In fact, in my previous years’ predictions, I highlighted that we would see some use-cases for AI in the industry grow while others fall short, depending on the available data. What it didn’t predict was the explosion of interest in Large Language Models made accessibly by OpenAI’s ChatGPT and this will certainly help boost many tasks involving humans interfacing with machines – but it is still a ‘language model’ and not a spatial model. This means that it can help empower users for tasks such as documentation, code, and script writing, or helping interact with complex systems such as for analytics or schema matching, which are generic tasks and not unique to the Geospatial industry.
Meanwhile, truly geospatial uses of AI will be in two principal areas:

• Digitising unstructured data such as imagery, point clouds or PDFs into structured spatial content: This has been happening steadily for a long time though it has never quite achieved the levels of accuracy and automation that were hoped for. It’s used more for anomaly detection (e.g. does the video show a crack in this pipe? Do these trees overhang the railway?) but maybe that continued improvements will make mostly automated data capture and (more importantly) data update and maintenance more achievable.
• Using structured spatial data for analytics and inference: This is an area of opportunity to automate more tasks that are currently manual and require good-quality structured spatial data as input, as well as many examples of ‘the right thing’ to train the models. We expect to do more of these types of projects this year and maybe one day, a tech giant will create a global ‘Large Spatial Model’ equivalent to a Large Language Model, to represent the global natural and built environment – which would make these projects even easier.

One method of capturing this unstructured or semi-structured data is using drones which for several years have been the highlights of geospatial hardware shows. They are widely used for human inspection via cameras, or for point cloud capture for projects but mostly just for human visualisation. If the AI techniques described above improved automated management of structured spatial data, then this would drive the use of drones for not only human interpretation, but structured data capture so one improvement would unlock the other.

In the meantime, there is still a disconnect between the data produced by the design and build phases of construction – held in CAD formats, drawings or point clouds – and the data needed by large scale data management systems of record. The handover and adoption of this information is a big driver for projects that we have been involved in over the last few years. We are seeing a tipping point where the automatic validation and integration of this data is now the norm, so more organisations will adopt this approach. Some projects such as the National Underground Asset register are no longer worrying about ‘how do we ingest, integrate, maintain and share this data?’ but ‘what are the future use-cases for this hugely valuable and up-to-date structured data asset?’.

The growth of automation in data capture and data ingest projects also drive the need for measuring and protecting data quality to ensure that automation does not lead to loss of data quality, which might otherwise have been spotted by the people capturing the data. Automation of data quality alongside automation of data capture means the data is then suitable for powerful use cases such as underpinning digital twins and smart cities. These large-scale data aggregation projects mean that there will be a better data framework from which these smart uses can flourish, and we hope to see more of that in the coming year.

Data aggregation hubs might only be a steppingstone towards a federated data mesh approach. Aggregating data that is mastered in many different systems by physically mirroring it in an up-to-date data hub is great to get consistent data in a consistent structure which provides a single system to manage resilience, performance, security, and role-based access. But there will always be a lag between what is stored in the hub vs the latest version of the data which might be updated on an hourly basis. A federated model in which the data is pulled live from each data mastering organisation’s system would provide an even more up-to-date version of the data.

In the shorter term this is usually achieved using metadata catalogues which can be searched to find and link to relevant data which can be streamed or downloaded. This catalogue approach allows the data to remain in the mastering systems, but they are not usually made available in a consistent structure or format, so it is harder to aggregate this data for use.

Data federation is harder, especially when an agreed structure is needed for virtual aggregation, because it requires an agreement on the structure and encoding of the data as well as a high level of technical maturity at the data custodian to provide live services which are scalable and secure. While there are good standards for data sharing from organisations such as the OGC (Open Geospatial Consortium), and good examples of live data feeds being used in production, it will be interesting to see whether more widespread secure data federation is progressed this year – possibly not yet.

All these capabilities are underpinned by web connectivity and therefore also at risk of hacking and disruption. The AI techniques described above which can automate positive outcomes, can also be used to speed up and empower cyber criminals, terrorists and ‘state actors’ for negative outcomes and so the ongoing security arms race will continue at full speed with continual upgrades, testing and best practices. Whether there are any seismic changes in the security area we don’t know, but it will be an ongoing discipline that needs to be kept up with to sustain and improve confidence in the systems to ensure that they can continue to be connected in a trusted and secure way.

In summary then, many of these developments enable more automation, and automation drives efficiency and opens up new opportunities so we should see various outcomes becoming real this year: Automated AI Data capture experiments will start to show whether they are viable, New data aggregation projects will start to automate ingestion by enforcing rigorous data checks and existing aggregation projects will start to benefit from leveraging their data in new and innovative ways.

About Author:

With a degree in Cybernetics and Computer Science, Seb joined Laser-Scan (which became 1Spatial) in 1997 as a Software Engineer. After working on many projects and a broad range of software as a Senior and then Principal Software Engineer, he then moved into Consultancy and then Product Management which provided insight into customer and industry needs and trends. After leading Product Management for a number of years, Seb is now Chief Technology Officer (CTO) at 1Spatial.

By Mike Klonsinski, President, Berntsen International, Inc.

Accelerating trend in 2024: Connected Asset Management

Mike Klonsinski

The promise of the Internet of Things (IoT) centers on the premise that every object’s data – location, origin, status, interactions – will be part of an interconnected digital world. While industries like manufacturing and healthcare have made significant strides in realizing this promise, the infrastructure sector has faced delays. However, a shift is anticipated in 2024 with the deployment of products and solutions that connect infrastructure assets in the field with Geographic Information Systems (GIS) and Asset Management Systems (AMS).

This evolution is made possible by a few key technological advancements:

1. Development and production of lower cost, reliable sensors to collect and communicate data from ‘things’.
2. Growth in bandwidth and storage that enables even simple products to communicate large amounts of data and be part of the connected world; and
3. Increases in the capabilities of GIS and Asset Management systems to integrate and make sense of large inputs of external data.

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By Jean-Yves Lauture, CTO, Eos Positioning Systems

Jean-Yves Lauture

The upcoming year holds great promise for GIS users who leverage global navigation satellite systems (GNSS) technology. In 2023, many of us closely followed the announcement by the European Union Agency for the Space Programme (EUSPA) that their brand-new Galileo High Accuracy Service (HAS) had entered its first testing phase. This development made 10-20 centimeter-level positioning accuracy available worldwide — as a completely free service. Eos Positioning Systems’s latest GNSS receiver, the Arrow Gold+™, immediately capitalized on this new corrections source, which is broadcast directly from the Galileo constellation GNSS satellites. Now, in 2024, we predict that Galileo HAS will be the most significant game-changer for mobile GIS users globally. This is attributed to two key factors: Firstly, EUSPA has planned operational improvements and enhancements that will drastically boost the performance of Galileo HAS. Secondly, increased availability of Galileo HAS will allow various industries to explore even more use cases that Galileo HAS can uniquely address, surpassing our previous expectations.

Let’s explore the improvements EUSPA plans in the next phase of Galileo HAS. Currently, Galileo HAS is in Phase 1, termed “Initial Service.” With a lot of deployment work happening in 2024 towards Phase 2, we can anticipate a range of performance improvements in preparation for the “Full Service” (date unknown). One of the most exciting enhancements will undoubtedly be the improved convergence time. In the current initial service phase, convergence outside of Europe takes about 30 minutes to achieve approximately 20-centimeter accuracy globally, based on our initial tests. Within the European Union, convergence time is already much shorter than this, down to about 5 minutes. In Phase 2 of Galileo HAS, EUSPA has stated that convergence time will drop to an impressive 5 minutes worldwide, and under 2 minutes within the European Union! This improvement could come relatively soon, and we eagerly await to see if it will happen (or part of it) during 2024. For more details on what to expect in Phase 2, refer to the EUSPA website for Galileo HAS here: https://www.euspa.europa.eu/european-space/galileo/services/galileo-high-accuracy-service-has.

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By Tony Agresta, Executive VP, General Manager, North America at NearMap

Tony Agresta

1. 1. Embedding location intelligence inside of systems for greater integration and solutions

Many different industries are leveraging location intelligence and embedding those solutions within systems to allow for deeper insights and learnings, empowering these industries to respond to their surroundings in a more meaningful way. Everyone wants to build a solution—companies want imagery and AI inside their workflow, however, it must be embedded for greater integration to not disrupt the infrastructure of a company. When an organization embeds this imagery and AI into its workflow through location intelligence, the companies’ workflows become more efficient and streamlined. With this integration, companies that utilize GIS data can better prepare and predict for what challenges may be ahead.

2. 2. The emergence of scalable 3D insights for greater data visualization

3D imagery is an area for growth and deeper analysis. The ability to navigate around an area and visualize proximity to neighboring properties see how things have changed over time is becoming more valuable. In 2024, the use of advanced 3D data sets such as Digital Surface Models will become more widely used to visualize and inspect properties and their surroundings. These insights will drive greater accuracy for a number of industries, like insurance, construction, engineering, roofing and more.

3. Organizations broadly will realize the value of GIS data and technologies

Geographic information systems (GIS) and the data they generate will be vital for companies to address challenges, like those that come with construction, underwriting, property assessment, reinsurance, corporate governance, sales and marketing, claims handling, customer service and more. Mapping and aerial companies will focus on making data layers easier to visualize inside of GIS tools. By creating, managing, analyzing, and mapping huge datasets and then relating them to the world around us, companies will glean valuable insights about spatial patterns and relationships. These companies will continue to realize the value of visualizing data and projections in a real-world context and will look to hire and retain people with a background in GIS, people who can import and analyze layers of data to support decisions.

About Author:

Mr. Agresta has worked in technology for more than 35 years and has extensive experience in sales, marketing, product management, and operations for technology companies focused on analytics, marketing automation, and mapping. His core strengths and expertise are in sales, marketing, product management, product marketing, SaaS, sales engineering, sales enablement and technology marketing.

By Clément Galic, CEO, Unseenlabs

Clément Galic

2024 Market Trend: Enhanced Security as Radio Frequency Signal Detection from Space Transforms Maritime Security
As the CEO of a company specializing in space-based maritime surveillance, I foresee 2024 as a pivotal year for Earth Observation. We’re entering an era where the integration of radio frequency signal detection from space will transform maritime monitoring. This technology not only enhances maritime security but also plays a crucial role in environmental protection by tracking illicit activities at sea. The trend is clear: advanced EO technologies, particularly in maritime domains, are not just about data collection anymore; they’re about delivering precise, actionable intelligence to safeguard our oceans and global maritime interests.

Exhaustive maritime situation awareness is a critical global 2024 initiative. Unseenlabs is the world leader in radio frequency (RF) data and solutions for maritime domain awareness. Unseenlabs processes and analyzes this RF data, and provides unique knowledge for national security operations, for environmental protection, and for an increasing number of applications in the commercial sector.

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