What’s new in LuciadRIA 2026.1

LuciadRIA 2026.1 adds support for version 2 of the NATO APP-6E military symbology standard, in line with LuciadLightspeed and LuciadFusion. You can now create, style, and edit symbols using the latest joint military symbology defined by APP-6E. LuciadRIA’s support covers the domains of air, land, sea, space, and cyberspace, and includes symbol identifiers for dismounted individuals and stability & civil support operations, as well as the control measure and planning symbols. The cyberspace symbols introduced in the previous release have been upgraded from APP-6E version 1 to version 2.

Just like our product LuciadCPillar, LuciadRIA now introduces support for Gaussian splatting, one of the most exciting recent innovations in 3D geospatial visualization. Gaussian splatting reconstructs real-world environments using millions of tiny 3D Gaussian primitives, producing highly detailed and photorealistic digital scenes that bridge the gap between traditional meshes and reality-capture data. As the technology rapidly gains traction across the geospatial, simulation, and digital-twin industries, support for Gaussian splats ensures that LuciadRIA remains aligned with the latest state-of-the-art visualization capabilities expected by modern users.

The new capability allows developers to seamlessly visualize Gaussian splatting datasets delivered as OGC 3D Tiles, making them easy to integrate into existing 3D workflows. Advanced styling options enable fine-grained control over visual quality, performance, depth interaction, and rendering behavior, allowing applications to scale from lightweight operational systems to high-fidelity digital twins. The result is an immersive viewing experience that combines exceptional realism with the flexibility, performance, and engineering robustness required for professional geospatial applications.

A lot of business data is modeled as vector data or feature data. Most of this data can be loaded as-is. For larger data sources, the use of scale ranges and smart filtering ensures a smooth experience. However, a few types of vector data cover large areas, offer very detailed information, and serve as context or background information. Because of the detail and the large size of individual objects, filtering and scale ranges are not sufficient. Some examples are world shorelines, country borders or contour lines.

In a process that is similar to how 3D data is processed into 3D tiles, these contextual feature layers can be processed into vector tiles or feature tiles. A common format is Mapbox Vector Tiles, a tile format for tile sets of 2D data. The specification is open, which makes it a good exchange format.

LuciadRIA 2026.1 introduces a client for Mapbox Vector Tile datasets, aimed at using them as a background layer. You can load them as TileJSON, the most common way to serve vector tiles on the web and also what a LuciadFusion MBTiles service serves, or straight from a web-hosted PMTiles archive. PMTiles is a useful addition, because the server only has to host a single file: any server with plain file hosting will do. The SQLite-based .mbtiles format itself is not supported, as it is optimized for local file access rather than for the web.

You can create a model and layer for the vector tiles, and LuciadRIA picks up the associated Mapbox GL style to render lines, areas, icons, complex strokes and labels. The client uses the existing label rendering pipeline, and removes overlapping tile boundaries for clean rendering. Tiles are decoded on web workers, and the resulting draw commands are replayed across several frames, so that loading a lot of tiles does not cause frame rate drops. Your datasets are not restricted to the usual Web Mercator tiling scheme either: LuciadRIA derives the tiling scheme from the TileJSON descriptor, so you can also visualize vector tilesets that are tiled in another projection.

LuciadRIA 2026.1 adds a codec for the NATO Vector Graphics (NVG) format, so you can decode and encode NVG content directly in the browser. NVG is widely used to exchange tactical overlays and operational data between command-and-control systems, and bringing it to LuciadRIA lets web applications consume and produce these overlays natively.

The LuciadRIA NVG support is complete, including:

Until now, LuciadRIA could read features from an OGC WFS service, but could not write them back. Applications that needed to persist edits had to fall back on a custom REST service, such as the annotation service that is part of the LuciadRIA samples.

LuciadRIA 2026.1 adds support for Transactional WFS (WFS-T), so that you can persist feature edits straight to a standards-compliant OGC service. WFSFeatureStore now implements the full editing cycle: inserting, updating and deleting features, and locking them so that concurrent editing sessions do not overwrite each other’s work.

Because the store reads the capabilities that the service advertises up front, it knows which operations the server actually supports. New API, such as the WFSOperationName enumeration and the Store.isOperationSupported method, lets your application enable or hide editing functionality accordingly. WFS-T requires a WFS 2.0 service.

LuciadRIA 2026.1 includes several improvements to point cloud rendering.

LuciadRIA 2026.1 adds support for draping video onto a 2D map, extending the video draping capability to the 2D case. This is useful for displaying full-motion video, such as a drone or camera feed, in its correct geographic context on the map. Video is draped as a single-level, single-tile panorama in pinhole projection, oriented downwards towards the Earth. Draping onto a 2D cartesian map is not supported.

When a cartesian map uses a different scale on its X and Y axes, complex stroke styling could appear distorted, because the complex stroke rendering assumed a uniform scale on all axes. LuciadRIA 2026.1 reworks the complex stroke implementation so that pixel-sized complex strokes keep their intended size regardless of the scale of each axis. You can see the difference most easily on the bordered map from the LuciadRIA Toolbox.

The same rework benefits 3D maps. Non-draped, pixel-sized complex strokes are now evaluated in screen space, so that a pattern such as the dashes of a dashed line keeps a constant on-screen size, wherever the camera is. Previously, the pattern was deformed by the perspective as the distance to the camera grew.

Modern development teams increasingly rely on AI-powered coding assistants to accelerate onboarding, reduce development effort, and improve code quality. To support this trend, LuciadRIA 2026.1 now ships with a dedicated AI skill package that helps leading AI coding tools understand the LuciadRIA architecture, APIs, samples, and platform-specific development patterns. The skill guides developers towards the most relevant documentation and code examples, enabling faster and more accurate application development.

Designed with flexibility in mind, the AI skill can be integrated into a variety of popular development environments and AI-assisted workflows. Support is provided for tools such as Claude Code, Cursor, OpenCode, and other assistants capable of consuming external knowledge sources. By making product expertise directly available within the developer’s preferred ecosystem, LuciadRIA helps organizations adopt modern AI-enhanced development practices without being tied to a specific tool chain or vendor.

This LuciadRIA release also features a number of smaller improvements, for example: