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TopoSection.com - Online Landscape and Urban Section Generator Using High-Resolution Geospatial Data

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Description

TopoSection.com is an online application designed to generate landscape and urban cross sections quickly accurately and with minimal complexity.

TopoSection is built for architects urban planners and landscape designers. The platform enables users to produce terrain profiles in just a few seconds directly usable during competition phases conceptual design feasibility studies and urban analysis workflows. The interface follows a straightforward approach: define a section line and instantly generate a ready to use cross section without requiring advanced GIS or CAD manipulation.

The quality of the generated sections relies on the integration of high resolution open geospatial datasets available in Luxembourg. TopoSection combines authoritative national datasets with advanced terrain reconstruction workflows to provide precise and reliable representations of the built and natural environment.

The application integrates detailed 3D building data transportation infrastructure hydrographic networks vegetation layers and high resolution LiDAR terrain models in order to generate coherent multi layered landscape sections.

Thanks to this synthesis of datasets TopoSection can generate cross sections that simultaneously include terrain buildings roads railways water networks vegetation and trees. This multi layered approach provides a precise reading of the landscape and facilitates territorial analysis at multiple scales.

Generated sections can be exported in SVG and DXF formats ensuring compatibility with major design and BIM software including AutoCAD ArchiCAD Autodesk Revit Rhinoceros 3D and SketchUp. This interoperability enables seamless integration into architectural urban planning and landscape design workflows.

TopoSection is therefore positioned as a ready to use production tool that accelerates the creation of reliable graphic documents while simplifying access to complex geospatial data.

Integrated Geospatial Datasets
Buildings - BD L BATI3D LoD2 (ACT 2023)
Building geometries are generated from the Luxembourg national 3D building database BD L BATI3D LoD2. The dataset provides detailed volumetric representations of buildings including roof structures and elevation information allowing accurate integration of the built environment within generated cross sections.
Roads and Transport Infrastructure - BD L GeoBase (ACT 2025)
Transportation networks are derived from the BD L GeoBase database. This dataset includes roads streets mobility infrastructure and railway networks used to reconstruct mobility corridors and urban infrastructure within the section profiles.
Hydrography - BD L TC 2015 (ACT 2015–2018)
Water related elements such as rivers streams and hydrographic networks are integrated from the BD L TC 2015 dataset. These layers contribute to a more accurate interpretation of landscapes and territorial structures.
Green Areas - OpenStreetMap (OSM 2025)
Parks forests grasslands and landscaped open spaces are enriched using OpenStreetMap vegetation layers. These datasets help represent large scale green structures and natural landscape components.
Trees - OpenStreetMap (OSM 2025)
Individual tree locations are integrated using OpenStreetMap tree datasets allowing a finer representation of vegetation and urban canopy structures within the generated sections.
Terrain and Elevation Model - BD L Lidar2024 0.5m (ACT 2024)
Terrain reconstruction is based on the high resolution BD L Lidar2024 0.5m dataset. This LiDAR derived elevation model enables precise representation of slopes topography embankments and terrain variations across Luxembourg.

TopoExport (CAD & BIM)

Topic

Geospatial data

Type

Application

Tags

  • 3d-lidar

  • cadaster

  • cadastral-parcels

  • cadastral-sections-based-on-cada

  • cadastralparcel

  • cadastralzoning

  • cadastre

  • dtm

  • lidar

  • lidar-3d

  • sections-cadastrales

  • terrain

  • terrains

  • territoire

Creation date

January 3, 2026

Last update

May 7, 2026

9 used datasets

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