New developments in measurement technologies are changing how we work in geospatial fields by making things faster, more accurate, and better connected. This presentation looks at how improved automation helps surveyors collect data quickly and with fewer errors, even in tough environments. We also emphasise the crucial role of mobile connectivity in sharing data, collaborating between field and office, and managing sensors in real-time, helping teams to stay flexible and informed. These core surveying solutions come together to create new, efficient workflows that tackle major challenges in the geospatial industry.

In today’s data-driven infrastructure landscape, managing vast amounts of geospatial data is no small feat. This session introduces TopoShare™, a powerful platform that transforms how surveyors, engineers, and project managers govern, organize, and share point cloud data, images, coordinates, and metadata across the digital twin lifecycle. We’ll explore how TopoShare™ ensures scalable, cost-effective cloud storage and seamless integration with TopoDOT® for centralized project access. Attendees will learn how automated structuring and a robust web-based portal streamline internal workflows and external collaboration, reducing fragmentation and improving decision-making. Through real-world case studies, we’ll showcase tangible benefits, including increased operational efficiency and enhanced client engagement. Additionally, we’ll examine how TopoShare™ enables an “on-demand” digital twin model, delivering high-fidelity geospatial data dynamically and affordably. Join us to discover how TopoShare™ redefines geospatial data governance and empowers your team with a smarter, more agile approach to digital twin production.

How to improve the efficiency of construction site management? Here is the answer! The DJI Dock 3 enables effortless automation of recurring construction site monitoring tasks. By scheduling remote data collection flights, project teams can regularly capture high-precision aerial data without deploying on-site personnel. Thanks to its mechanical shutter and RTK capability, Dock 3 delivers centimeter-level accuracy—ideal for progress tracking, documentation, and quality assurance. Routine flights can generate multiple outputs such as 3D models, DSMs, DEMs, point clouds, and orthomosaic maps, offering deep insights into the site's development status. Collected data is seamlessly uploaded to DJI FlightHub 2 or integrated with your preferred Construction Management Software, supporting timely project reviews and enhancing collaboration across teams—whether in the field or at the office.

Today, LiDAR is the tool of choice for geospatial professionals seeking accurate, high-resolution 3D data across diverse environments. However, collecting data across aerial, terrestrial, and indoor domains remains technically and operationally challenging. This presentation explores a unified approach to LiDAR mapping that integrates unmanned aerial vehicle (UAV)-based scanning, handheld mobile mapping, and cloud-based processing to streamline end-to-end workflows. CHC Navigation will explore how aerial platforms equipped with lightweight LiDAR sensors can rapidly cover large or complex terrains, generating precise point clouds for topographic surveys, infrastructure corridors, and environmental monitoring. Additionally, mobile laser scanners that use a combination of SLAM and GNSS/INS positioning allow for the quick and flexible capture of indoor spaces, urban streetscapes, and GNSS-denied zones with minimal setup and disruption. The real advantage lies in combining these data streams into a single, coherent dataset. Centralized, cloud-based processing environments allow users to fuse aerial and terrestrial LiDAR data, apply trajectory corrections, classify point clouds, and generate final deliverables, such as digital terrain models (DTMs), 3D meshes, and vectorized outputs. Unifying platforms and automating data processing eliminates many traditional pain points, such as disconnected tools, time-consuming file transfers, and inconsistent results. Whether you are mapping a dense urban corridor, scanning building interiors for BIM, or conducting environmental analysis across varied terrain, this session provides insight into how a harmonized LiDAR workflow can transform your data acquisition strategy.

UAV/Drohnen, Laserscanner und auch mobile Mapping Methoden haben in den letzten Jahren einen enormen Beitrag zur Digitalisierung in Bau-/Infrastrukturprojekten geleistet. Spezialisierte Softwarelösungen ermöglichen einerseits die einfache Auswertung der Daten und helfen andererseits in heterogenen Anwendungsfällen. X2BIM als Cloudlösung ist im Umfeld der Bahninfrastruktur seit mehreren Jahren etabliert. Die SAAS ermöglicht es, komplexe Fragestellungen, die bislang in einer Vielzahl Anwendungen analog und digital bearbeitet werden mussten, in einer einzelnen Cloudumgebung abzudecken. Punktwolken, GIS und BIM Daten lassen sich in X2BIM kombinieren und analysieren. Im Projektteam kann so transparent und effizient kollaboriert werden. Kombiniert man die Vielfalt an Erfassungsmethoden zusätzlich mit KI Methodik wie Deeplearning, sprechen wir nicht mehr von Digitalisierung als Selbstzweck, sondern von Automatisierung in der Steuerung, Durchführung und Überwachung von Infrastrukturprojekten. Anhand von Beispielen aus der Verschneidung von mobile-Mapping und UAV-Daten, sowie der Integration von KI repräsentieren wir Automatisierungsansätze in der Softwarelösung X2BIM.

In a context of diffusion of technologies dedicated to 3D reconstruction, characterized by the need of simple and fast acquisition, accuracy and high resolutions models, Stonex offers a new and unique technology. The new mobile mapping solution NUVO is an innovative and easy-to-use mobile mapping system, based on camera and photogrammetry reconstruction. The integrated GNSS and Visual camera ensure trajectory continuity and accurate results. The modular and upgradable solution can suit different customer needs, allowing surveying both on foot or with a vehicle and making mapping a one-person job. The main breakthrough lies in the ability to recognise road features directly in the field, allowing real-time assessment of the conditions and, eventually, adding any information for GIS surveys and BIM reconstruction.

Demonstrating the versatility of SLAM-based LiDAR for 3D vegetation mapping across a range of environments — from shaded grasslands in solar parks to winter wheat fields, Mediterranean dehesas, and arid shrublands.

Discover how DJI Terra is revolutionizing the way industries create and work with digital twins. This powerful 3D mapping software transforms drone data into highly accurate 2D maps and 3D models—fast, reliable, and precise. Whether you're in surveying, construction, or public safety, DJI Terra enables you to turn raw drone aerial imagery into actionable insights with centimeter-level accuracy. From real-time mapping to large-scale reconstruction, it’s built for the demands of modern geospatial work. Join us to explore how DJI Terra fits into the digital twin revolution—learn how to harness its full potential and bring your data to life like never before.

Cintoo is a cloud platform for managing and collaborating on reality capture data. It transforms point clouds from laser scanners into high-resolution 3D meshes that integrate seamlessly with ArcGIS. Our new ESRI integration brings true 1:1 high fidelity mesh representations of your scan data in your GIS workflows, preserving full LiDAR accuracy. Cintoo 3D Mesh also includes 360° images captured during scanning, enabling immersive panoramic experiences. Learn how this integration is transforming the way geospatial professionals visualize, analyze, and interact with reality capture data in ESRI.

Zuverlässige zentimetergenaue Präzision bleibt eine der größten Herausforderungen für Vermessungsingenieure, die in blockierten Umgebungen wie engen Gassen, dichten Wäldern oder in der Nähe von Hochhäusern arbeiten. Herkömmliche GNSS-Systeme können unter diesen Bedingungen oft keine gleichbleibende Genauigkeit über mehrere Messungen hinweg liefern, was Vermessungsingenieure dazu zwingt, auf weniger effiziente Methoden wie Totalstationen zurückzugreifen. Diese Präsentation stellt eine neue Lösung mit dem neuen CHCNAV ViLi i100 Visual-LiDAR GNSS-Receiver vor, um diese Einschränkungen zu überwinden und die Zuverlässigkeit in der Vermessung neu zu definieren. Das System kombiniert Multi-Source GNSS, LiDAR und Multi-Visual-Technologie. Teilnehmer erfahren, wie der ViLi i100 Multi-Sensor-Fusion nutzt – darunter fortschrittliche GNSS-Signalfilterung und die verbesserte SFix 2.0 Engine –, um stabile, sprungfreie Positionierungen mit einer Genauigkeit von besser als 5 cm sicherzustellen, selbst wenn GNSS-Signale blockiert sind. In vollständig GNSS-freien Umgebungen kann diese Lösung dennoch eine Genauigkeit von 5 cm innerhalb eines 20 m Radius gewährleisten und macht so den Einsatz von Totalstationen überflüssig. Durch den Fokus darauf, wie diese Innovationen in alltäglichen Vermessungs- und Bauszenarien angewendet werden können, bietet diese Session den Teilnehmern wertvolle Einblicke, wie aufkommende Sensorfusionstechnologien Genauigkeit, Zuverlässigkeit und Effizienz in der Geopraxis neu definieren. JETZT können Sie jeder Fix vertrauen.

As GNSS technology rapidly evolves, its reach is expanding beyond traditional high-end applications into the hands of everyday users. This presentation explores the accelerating adoption of GNSS, driven by affordable chipsets and open signals, and its integration into consumer technologies like autonomous vehicles and drones. We’ll examine the challenges of market convergence, where consumer-focused companies often lack the deep GNSS expertise needed for reliable performance—highlighting the critical role of collaboration with geospatial professionals. The session will also delve into the power of technological integration, showcasing how GNSS combined with IMUs and cameras is revolutionizing positioning accuracy in complex environments. Attendees will gain insights into cutting-edge industry correction services such as RTK, PPP, TopNet Live, and SkyBridge Pro, which are enhancing precision across industries. Finally, we’ll look ahead to a future shaped by the convergence of consumer and professional GNSS markets—unlocking new opportunities, driving innovation, and transforming sectors like construction, agriculture, and surveying.

Creating accurate indoor floor plans has traditionally been a slow, manual process—requiring time, expertise, and extensive post-processing. But with the latest advancements in scanning technology and smart software tools, that’s changing fast. In this session, we’ll explore how 3Dsurvey 3.1 streamlines indoor mapping by enabling automated floor plan generation directly from point cloud data. You'll see how to work with SLAM-based devices and 360° spherical imagery, using intuitive tools like X-ray views and automatic line detection to turn complex scans into clean, CAD-friendly 2D drawings. We’ll walk through the full workflow—from importing point clouds and aligning scans to extracting building outlines and refining outputs with easy-to-use editing tools. You’ll also learn how to snap directly to real 3D data, visualize scan positions, and export results seamlessly to third-party CAD software. Whether you're mapping buildings for renovation, documentation, or facility management, this session will show you how to speed up data collection, automate tedious steps, and produce high-quality floor plans in a fraction of the time. Perfect for surveyors, AEC professionals, and anyone working with indoor environments.

Die digitale Verfügbarkeit von Daten erlaubt es alle relevanten Informationen zu einem Infrastrukturobjekt in die Betrachtung mit einzubeziehen. Für das Beispiel einer Brücke wären das die detaillierten Angaben zur Geometrie, Materialien wie auch die physikalischen Eigenschaften. Es macht keinen Sinn eine Brücke isoliert und ohne Raumbezug zu betrachten. Sie hat eine klar definierte Position, an der sie steht (bzw. stehen wird oder gestanden hat), stellt ein entscheidendes Bindeglied in einem Straßen- oder Schienennetz dar und ist Teil eines Mobilitätskonzeptes. Die Brücke ist umgeben von Flächen mit unterschiedlicher Nutzung, sie ist evtl. betroffen von Hochwasser, Starkregen, Waldbränden oder Erdbeben. Neue Datenquellen von Sensoren und Inspektionen liefern engmaschige Angaben über den Zustand und aktuelle Nutzung. Für alle Teilaspekte einer Brücke gibt es über die Phasen des Lebenszyklus hinweg und die konkreten Anforderungen die jeweiligen optimierten Parameter, Strukturen und Standards. GIS, CAD, FEA, BIM, Dateien, Datenbanken, LIDAR Scan, Luftbilder, Satellitenaufnahmen aber auch zugehörige Sachdaten und Prozesse haben alle ihre Berechtigung. Der Digitale Zwilling ist ein leistungsstarkes Konzept alle digitalen Informationen von einem realen Infrastrukturobjekt in einer dynamischen und intuitiv verständlichen Form zu erfassen, zu verwalten und auch zu analysieren. Die Integration von GIS und BIM spielt eine zentrale Rolle. Die vermeintlichen Widersprüche von Struktur und Standards zu Datenvielfalt und Offenheit werden aufgelöst. Einen entscheidenden Beitrag zur Konvergenz der Disziplinen leisten auch relevante Verbände. Die Initiativen und Aktivitäten von bitkom, buildingSMART und Deutscher Dachverband für Geoinformation werden exemplarisch dafür vorgestellt und über den aktuellen Stand hinaus wird ein Blick in die Zukunft von Infrastruktur Datenmanagement geworfen.

This presentation demonstrates a 3D web application for real-time visualization of CO₂ emissions and district heating demand using GeoAI and open geospatial data. By integrating ALKIS cadastral data, CityGML building models, and infrastructure layers within QGIS and PostgreSQL, the system creates an interactive urban digital twin powered by CesiumJS. A custom-built GeoAI model estimates CO₂ emissions and heating demand at the building level, based on attributes such as usage type, construction year, geometry, and roof structure. Users can update these parameters directly in QGIS or remotely via QFieldCloud, with all changes reflected live in the 3D environment. Buildings are dynamically styled based on their CO₂ output or connection status to the district heating network. Key features: GeoAI-powered estimation of CO₂ emissions and heating demandReal-time data synchronization via Django REST APIsIntegration of ALKIS and CityGML for detailed urban modelingVisualization and planning of district heating networksCross-platform data editing using QGIS and QFieldCloud This demo offers a scalable and open-source approach to building interactive 3D digital twins that support climate-responsive planning, energy infrastructure design, and municipal decision-making.

Was genau ist die Definition eines Digitalen Zwillings? Wo stehen wir bei aktuellen Projekten und in welchen Bereichen gibt es noch Nachholbedarf. Das Beispiel „Wasser“ liefert mit den unterschiedlichen Aspekten Klarheit. Experten aus der „Kommission Wasser“ des Deutschen Dachverband für Geoinformation und Gäste diskutieren den Stand der Implementierung von Digitalen Zwillingen in der Wasserpraxis und an welchen Stellen das Erfolgskonzept aktuell noch an Grenzen stößt. Die leitungsgebundenen Teile des Wasserkreislaufs werden bereits in hydraulischen Modellen umfassend dargestellt und die digitale Datengrundlage erlaubt die effektive Nutzung für Betrieb, Wartung und auch komplexe Simulationen. Wasser in Form von Niederschlägen, Oberflächenabfluss, Evapotranspiration oder Versickerung erfordert spezielle Parameter und Modelle, um Herausforderungen beim Grundwassermanagement, Starkregenereignissen oder auch Stadtklima erfolgreich zu adressieren. In Anschluss an die Podiumsdiskussion stehen die Panelisten für Fragen und Antworten am Stand des Deutschen Dachverbandes für Geoinformation (Halle 12.0 / Stand 0C029) zur Verfügung. Alle Zuhörerinnen und Zuhörer sind herzlich eingeladen dort aktiv in die Diskussion mit einzusteigen und die Themen bei einem kleinen Empfang zu vertiefen. Die Podiumsdiskussion ist Teil der Twin Talk Veranstaltungsreihe.

This joint presentation by Leica Geosystems and TopoDOT unveils a significant advancement in mobile mapping workflows: the seamless integration of International Roughness Index (IRI) analysis directly from point cloud data. Traditionally derived through specialized equipment and time-intensive surveys, IRI, an essential indicator of pavement quality, can now be extracted efficiently and accurately using TopoDOT software applied to data captured by Leica Geosystems' mobile mapping platforms. By incorporating this feature into the mobile mapping ecosystem, Leica and TopoDOT offer a smarter, faster, and more cost-effective solution for transportation agencies, infrastructure managers, and survey professionals. Attendees will learn how this innovation eliminates the need for redundant pavement-specific surveys, enhances safety by minimizing field time, and delivers actionable surface condition metrics alongside high-resolution geospatial data, all from a single data collection. This session will present real-world examples, workflow integration, and value-driven insights to showcase how IRI capabilities elevate the utility and ROI of mobile mapping investments.

Coming soon

Users today leverage a variety of products, tools and data to solve increasingly complex problems. Workflows will vary from project to project. Combining a BIM model from tool 1, civil engineering data from tool 2, reality capture from tool 3, GIS data from tool 4 and 3D context from tool 5 becomes even more complex. Using open standards, like OGC 3D Tiles, and interoperable tools, like open visualization clients, simplify these complex data wrangling workflows to accelerate value for the Community. Example - HNTB leverages multiple products to design a new bridge or roadway, including Civil3D, Revit, OpenRoads. They use Cesium to bring this data together, along with Google P3DT to create immersive digital twins within Unity and Unreal for their end users. They selected Cesium for Unity and Cesium Unreal as their visualization clients because they are open source and reduced their average project development by 70% If we want to ensure we continue making the complex simple for developers & users within the 3D and Geospatial communities, openness and interoperability of data and software will be the keystone. https://cesium.com/blog/

The most powerful mobile mapping systems of the next generation are hiding in plain sight. For years, we've overlooked the geospatial potential of the consumer-grade sensors that saturate our daily lives—from the GNSS, IMU, and LiDAR sensors in a smartphone to the integrated cameras of a modern vehicle. This presentation reveals how this ubiquitous hardware can be calibrated and transformed into professional-grade mobile mapping instruments capable of achieving survey-grade accuracy. We will challenge conventional thinking by demonstrating a clear, progressive path from rigorous accuracy assessments of handheld devices to advanced vehicle-based kinematic surveying, all using accessible, off-the-shelf technology. This is the story of how we stop waiting for new tools and start leveraging the geodetic potential of the ones we already have.

We propose a presentation for the INTERGEO Main Stage that will showcase a breakthrough in geospatial AI: the integration of the state-of-the-art Transformer-based architecture into VisionLidar, our 3D point cloud processing platform. This session will demonstrate how the latest advances in deep learning can directly transform the daily workflows of geospatial professionals, making classification of massive LiDAR datasets faster, easier, and more cost-effective than ever before. Key highlights of the presentation: Workflow Acceleration: Attendees will see how kilometers of point cloud data can now be labeled in just minutes, dramatically reducing project turnaround times.Reduced Manual Effort: Thanks to our library of sector-specific Super Models (e.g., for transportation, utilities, and construction), users can adapt the AI to their own datasets with minimal manual labeling, cutting both labor and training time.Accessible AI: Our solution runs on standard hardware, eliminating the need for costly infrastructure, while maintaining top-tier accuracy and reliability.Real-World Impact: We will present use cases from municipalities and engineering firms showing how VisionLidar with AI improves productivity and supports large-scale digital twin and asset management initiatives.This talk is not just about new technology, it’s about empowering professionals across surveying, urban planning, and infrastructure management to harness the power of AI without needing to be AI experts. It aligns perfectly with INTERGEO’s focus on innovation, geospatial systems, and the future of geodata processing. We look forward to presenting this advancement and demonstrating how AI is becoming an intuitive, indispensable tool for the geospatial community.