This session shows how large scale aerial LiDAR data can be transformed into reliable results within hours using an AI driven workflow. You will learn how Pointly classifies more than 70,000 square kilometers into custom classes with high accuracy and fast turnaround times. The talk provides practical insights into building scalable AI workflows for geospatial data and highlights what it takes to deliver precise results to clients at national scale using technology made in Germany.

Implementing Digital Twins that integrates real-time sensor data, 3D GIS, BIM, and operational systems to provide a single, authoritative view of infrastructure and urban environments. Customer examples on improving planning, design, and operations by simulating scenarios, detecting patterns, and visualizing the impacts of decisions before they occur, reducing risk, cost, and downtime. Enable smarter, more resilient organizations with digital twins that support predictive maintenance, sustainability initiatives, and seamless coordination across agencies and stakeholders.

How can a single integrated platform transform the way cities plan their future, manage risks, and monitor critical infrastructure? This session answers that question through two real-world implementations at scale: Roma Capitale and the Campania Region. The presentation introduces usBIM.geotwin, the open-standard platform from ACCA that bridges the gap between GIS and BIM — enabling public administrations to build, query, and act upon living Geospatial Digital Twins of their territory. Rather than treating geospatial data and building information as separate silos, the platform fuses them into a unified, actionable environment where urban planners, risk managers, and infrastructure engineers can work from the same source of truth. The Roma Capitale case study explores how geospatial digital twin technology is being applied to support urban planning decisions across one of Europe's most complex metropolitan areas — integrating heterogeneous data layers (cadastral, environmental, mobility, utilities) into a coherent territorial model that supports both strategic planning and day-to-day operational needs. The Campania case study shifts the focus to infrastructure safety: specifically, the monitoring and management of bridges and road infrastructure across the region. The session demonstrates how GIS-BIM integration enables continuous structural awareness, anomaly detection workflows, and evidence-based maintenance prioritization — moving infrastructure management from reactive to proactive. Across both cases, the session emphasizes a central thesis: this is not a bespoke solution built for two exceptional clients. The architecture, workflows, and integration patterns demonstrated here are designed to be replicated by any public administration — regardless of size or technical capacity — that needs to move toward data-driven territorial governance. Attendees will leave with a clear understanding of what a production-ready Geospatial Digital Twin looks like in practice, what integration challenges arise when combining GIS and BIM at city and regional scale, and how the methodology can be adapted to their own institutional context.

This session explores how the California Department of Transportation (Caltrans) has transitioned from reactive project oversight to proactive digital orchestration by integrating reality capture workflows into a unified common data environment. By focusing on the end-to-end lifecycle of infrastructure delivery, the presentation demonstrates how seamless field-to-office data streams automate culvert inspections, verify as-built quantities in real-time and significantly accelerate payment approval cycles. These workflows provide a scalable blueprint for the European market, addressing universal requirements such as ISO 19650 (BIM) standards, cross-platform interoperability and the modernization of complex infrastructure networks. Attendees will gain actionable insights into transforming raw field data into a strategic asset that mitigates risk and ensures total project transparency for public and private owners alike.

This presentation outlines a robotic spatial measurement and monitoring approach that links digital design information with field implementation, visual guidance, surveying, and repeated observation of change over time. The system combines optical sensing, robotic positioning, spatial referencing, remote operation, photogrammetry, and AI-assisted interpretation to support design-to-field workflows, project monitoring, mapping, structural monitoring, and quality verification within a unified measurement framework. The work is relevant to construction, engineering, and asset inspection where high precision, repeatability, safety, and non-contact operation are important. Its novelty lies in bringing photogrammetric measurement and AI-assisted analysis into surveying workflows that have traditionally relied on in-person and largely manual methods, while integrating visual guidance, remote operation, and monitoring into a connected process. This creates a basis for safer and more consistent field operations, and for more direct comparison between design intent, measured state, and observed change.

Complex industrial and retrofit projects require more than fast data capture. They need reliable, usable information that can support modelling, coordination, and informed project decisions. This session explores how modern Capture Reality workflows can be applied in real project environments to improve efficiency in the field while maintaining confidence in the final dataset. Using a practical, application-led approach, the presentation will show how terrestrial laser scanning and mobile capture workflows can be used to document challenging sites, including areas with restricted access, congested geometry, and mixed indoor and outdoor conditions. It will also demonstrate how trusted capture data can support downstream modelling workflows, including applications such as ClearEdge3D EdgeWise, helping teams move more quickly from field data to model-ready deliverables. Attendees will gain insight into how Capture Reality can deliver measurable project value beyond documentation alone. By connecting field productivity with downstream usability, this session will highlight how teams can reduce time on site, shorten turnaround to usable outputs, and support better decision-making across industrial and retrofit projects.

VertiGIS Networks is the solution for network planning and documentation throughout the entire lifecycle for utility and waste management companies as well as telecommunications providers. Use VertiGIS Networks to efficiently process your data and manage it based on the Esri Utility Network. View your data online and offline with the VertiGIS Network Explorer. Use the VertiGIS Network Simulator to optimally plan infrastructure and simulate network impacts. Organize facility maintenance with VertiGIS Network Maintenance and ensure operational reliability. VertiGIS Networks supports all types of Esri Utility Networks.

With NET scan by TKI, power lines and infrastructure are captured quickly and with high precision as a 3D digital twin. The presentation demonstrates how LiDAR scanning, precise GNSS data, and digital power models help optimize and accelerate energy infrastructure projects: enabling faster documentation, outstanding quality, and transparent collaboration between all project stakeholders. This creates up-to-date, high-quality as-built data, speeds up documentation processes, and sustainably improves data quality for planning, construction, and operation.

Assignments and Career Opportunities in the Bundeswehr Geoinformation Service

The annual Survey School Research Symposium and Competition brings together the next generation of geospatial innovators to bridge traditional fieldwork with advanced tech like LiDAR and photogrammetry. This year's winning presenter will break down their groundbreaking research, showcasing a high-precision, real-world application that perfectly balances cutting-edge geospatial workflows with strict survey-grade accuracy. Attendees will gain a direct look into the exact methodologies, field challenges, and data processing techniques that set the standard for the future of the geomatics industry.

Mobile laser scanning technology enables the rapid acquisition of highly detailed 3D representations of road environments in a single survey pass while travelling at normal road speeds. The efficiency of this data collection process has transformed surveying workflows across many engineering projects. Despite these advances, feature extraction, particularly the generation of CAD- and GIS-compatible outputs, remains a significant challenge. This is especially true for linear roadway assets such as curbs and lane markings. Extracting these features from mobile LiDAR datasets is an extremely tedious and time-consuming process. Although semi-automated tools have helped, they still require substantial user intervention and many hours of manual drafting. To address these limitations, this presentation introduces Reflektar’s novel AI framework for the fully automated, network-scale extraction of curbs and pavement markings from mobile LiDAR point clouds. The framework combines supervised deep learning for feature detection with an unsupervised machine learning pipeline that vectorizes semantic attributes based on the detection results. The outputs include CAD- and GIS-compatible representations of roadway features such as top and bottom of curb, , lane lines, dashed markings, arrows, and other pavement marking symbols. By eliminating the need for manual interaction, the proposed framework enables scalable deployment across hundreds of kilometers of roadway. The presentation describes the proposed framework and shares the results of citywide deployment of the novel Reflektar framework. The presentation also discusses challenging boundary cases. Results from testing across diverse environments and multiple mobile mapping systems are also presented.

Satellite imagery has become a cornerstone of modern geospatial intelligence, enabling scalable, repeatable, and globally consistent mapping capabilities. As the demand for up-to-date geospatial data intensifies - driven by defense, security, and civil applications - satellite-based cartography is increasingly positioned as a complementary, and in some cases alternative, solution to airborne and drone-based data acquisition. Compared to aerial or UAV platforms, satellites offer unique advantages in terms of global accessibility, rapid revisit, and operational independence. They enable mapping in denied or contested environments, where deploying aircraft or drones may be impractical or politically sensitive. This makes them particularly relevant for defense applications such as MGCP (Multinational Geospatial Co-production Program) and MUVD (Multinational Urban Vector Data), where standardized, interoperable, and frequently updated geospatial datasets are critical. From a technical standpoint, recent advances in very high-resolution optical satellites now support both 2D and 3D mapping workflows, including digital surface models and building reconstruction. While aerial data still provides superior resolution and flexibility for certain local use cases, satellite imagery has reached a level of maturity that allows it to address a growing share of mapping needs, especially when coverage, timeliness, and scale are prioritized over absolute precision. Satellite-based mapping also enables rapid mapping workflows, including crisis response, obstacle detection for air and ground navigation, and trafficability assessment. In such contexts, the ability to quickly task satellites and process large volumes of data becomes a decisive advantage. Artificial Intelligence is playing an increasingly important role across the cartographic production chain. In particular, deep learning techniques significantly enhance geometry extraction, enabling automated detection and vectorization of features such as buildings, roads and land cover. This contributes to improved productivity and reduced turnaround times. However, AI should not be seen as a silver bullet, especially for complex, specification-driven products like MGCP or MUVD. These datasets require high levels of semantic richness, consistency, and compliance with strict data models. While progress is being made, automated attribute extraction remains a key challenge. Emerging approaches leveraging Large Language Models (LLMs) and Vision-Language Models (VLMs) offer promising perspectives for semantic interpretation and attribute population, but their operational maturity is still evolving. As a result, human expertise remains essential, particularly for validation, enrichment, and handling edge cases. It is likely that, in the foreseeable future, high-quality vector databases will continue to rely on a hybrid approach combining AI-assisted extraction and manual refinement. Similarly, the transformation from structured geospatial databases to finalized cartographic products, respecting symbology, generalization rules, and user-specific requirements, remains largely manual today. Here again, generative AI and FMs (Foundation Models) could play a transformative role, by learning cartographic rules and automating map generation. Yet significant work remains to ensure reliability, explainability, and standard compliance. In conclusion, satellite-based mapping is entering a new phase of maturity, driven by both sensor capabilities and AI advancements. While it does not replace aerial or UAV solutions, it offers a powerful, scalable complement, particularly for defense and large-area applications. The integration of AI across the production chain holds great promise, but must be approached with realism: the future of cartography will be hybrid, combining automation and human expertise to deliver trusted geospatial intelligence at scale.

Orthophotos are one of the most widely used outputs in geospatial workflows - but in practice, they often fail to show what actually matters on the ground. This session demonstrates how different types of orthophotos can dramatically impact the accuracy, clarity, and usability of your data. Using real project examples processed in 3Dsurvey, we will compare traditional orthophotos, true orthophotos, custom plane projections and newly developed ground orthophotos, showing how each method impacts visibility, measurement reliability, and downstream workflows such as planning, while improving the clarity of features. A special focus will be placed on the new Ground Orthophoto feature (introduced in 2026), a bottom-up projection method that removes visual obstructions like vegetation, roofs, and overhangs to reveal otherwise hidden ground features that matter most. This enables users to detect critical elements such as: - Road edges and surface conditions - Manholes and utilities - Terrain discontinuities and breaklines The result is not just a better image, but better decisions, fewer site errors, and more reliable project outcomes. This session shows how improved geospatial outputs lead to higher-quality deliverables.

Recreating physical working environments for cross-departmental alignment has traditionally been costly and logistically complex. This session highlights how Cintoo and Ricoh’s Gaussian Splatting technology empowers CapEx and OpEx teams to rapidly generate photorealistic digital twins. Discover how this advanced spatial technology enables fast, accurate facility captures, breaking down data silos for seamless collaboration. We will examine the immediate, measurable ROI of this approach: by replacing traditional site inspections with rapid visual workflows, organizations drastically reduce travel expenses, security overheads, and insurance risks, ultimately accelerating decision-making and eliminating the friction of physical distance.

Infrastructure operators face a common challenge: planning, construction and maintenance of road and rail networks require current, reliable as-built data – ideally captured without interrupting live operation. Drawing on completed road and rail projects, this talk shows how modular mobile mapping systems (including the Trimble MX9) capture dense, high-precision point clouds and high-resolution imagery in a single pass at up to 100 km/h – without track closures and, on the rail side, based on a Deutsche Bahn product approval under Ril 883.6000. The focus is on how this data turns into concrete decisions: alignment and clearance-gauge data for planning, AI-based automatic asset detection for inventory databases, and BIM as-built models and digital twins for operation and maintenance. Using examples such as the capture of several thousand route kilometres and selected rail and motorway projects, the presentation covers achievable accuracies, the workflow from raw capture to decision-ready model, and the economic comparison with conventional methods. It addresses infrastructure operators, surveying and engineering firms and BIM/digital-twin owners.

As industries face increasing pressure to map faster, safer, and with greater precision, geospatial professionals are looking for technologies capable of addressing complex environments without compromising efficiency or data quality. From dense vegetation and critical infrastructure to coastal and shallow-water environments, the demand for versatile and operational mapping solutions has never been higher. During this session, YellowScan will showcase how modern UAV LiDAR technologies are evolving to meet these market challenges through complementary topographic and bathymetric solutions. Attendees will discover how lightweight, drone-agnostic LiDAR systems enable rapid, high-precision data acquisition across both terrestrial and underwater environments while simplifying operational workflows. The presentation will highlight real-world applications in surveying, environmental monitoring, infrastructure inspection, coastal resilience, and corridor mapping, demonstrating how geospatial teams can improve productivity, reduce field constraints, and access previously difficult-to-capture data. The session will also explore the growing convergence between topography and bathymetry, and how integrated UAV LiDAR workflows are shaping the future of geospatial intelligence for public agencies, engineering firms, and private operators worldwide.

Professional mobile mapping systems achieve centimeter-level accuracy through the tight integration of navigation-grade IMUs, survey-grade GNSS, and calibrated laser scanners. This paper assesses the relative and absolute accuracy of a vehicle-mounted test platform that combines a NovAtel SPAN tightly coupled GNSS/IMU with a mid-grade Velodyne VLP-16 LiDAR, evaluated along a 1.2 km test loop on The Ohio State University campus. The mobile-cloud georeferencing is driven entirely by the SPAN-processed GNSS/IMU trajectory, post-processed in NovAtel Inertial Explorer; three additional survey-grade PPK GNSS receivers are processed independently and serve as cross-checks on the trajectory. Direct georeferencing is performed in the standard ECEF formulation with per-point trajectory interpolation. An independent reference point cloud of the same area is acquired with a Leica RTC360 terrestrial laser scanner, registered and tied down to GNSS-derived ground control so that the TLS cloud carries an independent absolute geodetic datum. Absolute accuracy is then evaluated directly: identifiable features on building façades are coordinated independently in each cloud, and the coordinate differences between the mobile-cloud and TLS positions of the same features quantify the absolute georeferencing error of the directly georeferenced mobile cloud. Relative accuracy is evaluated separately from the internal geometry of each cloud: structure dimensions, inter-feature distances, and inter-feature angles are measured in the mobile cloud and in the TLS and compared, isolating the shape-preservation performance of the platform from any constant offset between the two reference frames. An auxiliary SHARE SLAM S20 handheld scanner mounted on the same vehicle is described as supplementary platform context; its data is not used in the accuracy assessment due to unreliable GNSS/IMU/SLAM integration at vehicle speeds.

AI agents are taking over workflow automation across all sorts of industries, automating workflows that could never be automated before. Spatial software and spatial data workflows won't be an exception. This shift is already changing how practitioners work with spatial data - and creating both pressure and opportunity for the software makers who serve them. In this practical talk, you'll see firsthand how agents already work with spatial data, in a live demo on a multi-epoch monitoring use case. For anyone building or buying spatial software, this is a grounded look at the transition unfolding in the category. You will walk away with a clear picture of what is now becoming possible, and how you can get started automating your own workflows using AI agents.

Every manufacturer can show an impressive accuracy specification. Few can demonstrate that two surveys performed a year apart can reliably measure a 5 mm movement instead of simply reproducing measurement noise. This presentation explores the difference between geometric accuracy and TimeShift capability—and why they should never be treated as the same performance indicator. Josip Rukavina, founder and CEO of Vectrino, challenges the industry's traditional focus on absolute accuracy. Drawing on real-world inspections of breakwaters, quay walls and other marine infrastructure, he demonstrates why repeatability, stable georeferencing and consistent acquisition are the true foundations of reliable change detection. Through the SeeUnderSea™ methodology, he explains how TimeShift inspections transform individual surveys into measurable asset histories that support confident maintenance and investment decisions. Because the real question is not whether your digital twin is accurate. The real question is whether it can tell you what changed.

This session presents a complete aerial surveying workflow built on DJI enterprise solutions – from hardware to software – and demonstrates how it empowers diverse industries. The hardware foundation includes the compact M4E visible‑light drone, the L3 LiDAR scanner, and the D‑RTK 3 multi-functional station for cm level positioning. On the software side, Terra, Modify, and Reality deliver seamless post‑processing from photogrammetry to point cloud 3D reconstruction, editing and viewing. Together, this integrated hardware‑software ecosystem delivers one unified workflow that scales across multiple sectors: surveying & mapping, public security & surveillance, infrastructure inspection, AEC (architecture, engineering & construction), and forestry management, etc. Real‑world use cases and performance insights will be shared to show how the same workflow solves industry‑specific challenges with efficiency and precision.

Destructive ground movements caused by tunnel construction, legacy mining, and climate change are gradual processes that often have massive consequences. When infrastructure—from railroad embankments and highway sections to entire city neighbourhoods—is affected, we face more than just structural damage and restrictions on use. We are confronted with the question of responsibility and liability: Who bears the (financial) responsibility when critical infrastructure is damaged or fails unexpectedly? In practice, action is often not taken until the first cracks are already visible. But by that point, repair costs and legal risks have already risen dramatically. How can we proactively address these complex risks and clarify liability issues before significant damage occurs? The answer lies in precise spatiotemporal monitoring. In this presentation, we’ll use concrete real-world examples (Munich, Essen, Hamburg, …) to show how we can measure ground movements from space early and reliably. You’ll learn how high-resolution InSAR measurements are actively used in practice to monitor induced ground movements, safely support construction projects, and protect the integrity of infrastructure based on data.

Insufficient information on underground conditions remains one of the main reasons for delays and cost overruns in construction projects. The use of digital models and analyses of soil conditions help to minimize risks in infrastructure projects. Large infrastructure projects are characterized by spatial, temporal and technical dependencies. The history and the entire life cycle are increasingly considered, relationships with the environment and integration into other systems are mapped more comprehensively in models and digital twins. To capture infrastructure in its complete context, the Z-coordinate is of crucial importance. Practical examples illustrate the relevance of comprehensive information about the conditions in the underground even beyond the construction phase. In concrete projects, the benefits of digital twins, the use of artificial intelligence or the added value of methods such as BIM / FME will be presented. This is the only way to achieve greater security in the planning, financing, approval, construction and operation of buildings, plants and networks.

Discover how CHCNAV PointX brings together PointNet network RTK and PointSky satellite-based correction services within one integrated positioning infrastructure. Learn how intelligent service selection and switching can reduce dependence on local infrastructure, simplify field operations, and extend reliable centimeter-level positioning across connected, remote, and connectivity-limited environments.

Explore how regulatory workflows can evolve to support efficient, compliant, and scalable UAS operations in geomatics. Learn about current approval challenges, emerging regulatory trends, and practical approaches to accelerating drone operations while maintaining safety and compliance.

Meet drone operators, surveyors, engineers, manufacturers, and regulators for an informal networking apéro following the Application Dome keynote. Enjoy drinks, exchange ideas, and expand your professional drone network at INTERGEO 2026.

Germany is running one of the largest coordinated LiDAR campaigns in Europe. The Digital Twin Germany (DigiZ-DE) program, led by the Federal Agency for Cartography and Geodesy (BKG), is surveying 356,794 km² of the country at a point density of 40 pts/m², roughly four to eight times higher than typical national LiDAR surveys. The result is a unified 3D model of the entire country, supporting urban planning, crisis management, and long-term sustainability. At this scale, automation isn't a convenience. It's a necessity. In this session, Flai shares how AI-powered LiDAR point cloud classification is being applied across the DigiZ-DE program: classifying ground, vegetation, buildings, water, bridges, power lines, wind turbines, and project-specific object classes in a single automated run. Key takeaways: - How AI-driven LiDAR classification scales to country-level point cloud volumes - Strip-level noise classification, granular power line categorization, and dedicated handling of project-specific classes like wind turbines - Why a 12-class ASPRS-based scheme, extended with custom classes, works at national scale - Local vs. cloud processing trade-offs for large LiDAR programs This talk is aimed at national mapping agencies, regional surveying authorities, and geospatial production teams running large LiDAR programs. It offers a concrete look at what AI-supported classification makes possible today. Background: an independent overview was published in GIM International, "Processing nationwide data for Germany's digital twin": https://www.gim-international.com/content/article/processing-nationwide-data-for-germany-s-digital-twin

With the new Version 6, Smallworld sets the current GIS standard, featuring established database version management (multi-user, planning data), the industry-standard PostgreSQL, and the option for cloud operation. In particular, the specialist modules for energy and water networks (Smallworld NRM) set the standard in terms of data and functional models, already include 3D functions and are the foundation for 3D importer or new 3D network model. Adjacent peripheral processes in GIS documentation are provided with an efficient means of precise line surveying directly via smartphone using the NAVA augmented reality app, without the need for conventional and costly measuring equipment. For GIS data usage, the Lovion system represents the industry standard: in network operations, network management or network construction, network processes are fully digitised on the basis of GIS and asset data and work management. The companies in the Smallworld Alliance always keep future GIS applications in mind. Whilst GIS power users are equipped with a rich client and CAD functions, all other users can also utilise the GIS data with a light client (Lovion or web solutions) for data visualisation and maintenance, making use of AI services for quality assurance, GIS operation and analysis.

Pointly provides an AI powered engine that automatically performs classification and CAD data extraction from point clouds, as well as generating structured GeoJSON and BIM relevant outputs. The solution is designed for large scale applications, enabling fast, consistent and scalable processing to support efficient analysis and downstream workflows. We will present how Pointly’s 3D AI models are applied in real world use cases across multiple industries, including railway, powerline corridor and mobile mapping projects.

Infrastructure worksites rarely rely on equipment, cloud services, and model-based workflows from just one manufacturer. Machine control systems, surveying instruments, and model-based workflows must work together across mixed fleets, different brands, and parallel operational processes. In practice, this often leads to fragmented data flows, manual conversions, duplicated work, and unnecessary complexity on site. ISO/TS 15143-4 provides a foundation for a common language in these heterogeneous environments. The standard supports interoperable workflows between machine control and surveying by defining how information is structured and exchanged. Importantly, it also defines communication between manufacturers’ cloud services (VIS) and a central site management cloud (SMS), enabling more consistent and scalable data exchange across the worksite ecosystem. Beyond improving interoperability, the standard also creates opportunities for new kinds of connected ecosystems across infrastructure worksites. It can help bring machines, measurement devices, software platforms, and cloud-based services into the same operational framework, reducing integration barriers and enabling more open collaboration between technologies from different vendors. This presentation explores the practical challenges of mixed-brand infrastructure worksites and shows how standardization can help address them. It highlights typical bottlenecks in connecting machines, measurement devices, and cloud services, and discusses how ISO/TS 15143-4 can enable more open, reliable, and efficient collaboration across the site. The session also shows how Novatron is turning standardized interoperability into practical solutions for modern infrastructure projects.