Welcome to GEOMAPI’s documentation!

Welcome to GEOMAPI, a Python toolbox designed to enhance the processing of close-range sensing observations such as images and point clouds of the built environment. It specializes in jointly utilizing Building Information Modeling (BIM) and sensory data. To achieve this, GEOMAPI employs Linked Data (LD) to create resources of various popular sensory modalities.

If you want to learn more about GEOMAPI’s structure, head over to the Getting started section. Similarly, you can check out the Ontology to better understand the data management. If you’re interested in viewing real test cases solved with GEOMAPI code, visit the TEST CASES section.

This Open-Source API is the work of the GEOMATICS research group at KU Leuven, Belgium. If you want to collaborate, visit the team section and let us know.

Information:

• Getting Started
• Nodes
• Functionality
• Ontology

API Reference

• geomapi.nodes
• geomapi.utils
• geomapi.tools

Tutorial:

• Node
• GeometryNode
• ImageNode
• SessionNode
• Node selection

Test Cases:

• Alignment Tools
• Combination Tools
• Construction site progress
• Validation Tools
• Volume calculation

Development:

• User environment
• Developer environment
• Packaging
• Ontology Creation
• Testcase Creation

Contribution

• Team
• `GitHub <https://github.com/KU-Leuven-Geomatics/geomapi>`_

Please do refer to the following publication when using GEOMAPI in your projects.

@article{GEOMAPI,

title = {GEOMAPI: Processing close-range sensing data of construction scenes with semantic web technologies}, journal = {Automation in Construction}, volume = {164}, pages = {105454}, year = {2024}, issn = {0926-5805}, doi = {https://doi.org/10.1016/j.autcon.2024.105454}, url = {https://www.sciencedirect.com/science/article/pii/S0926580524001900}, author = {Maarten Bassier and Jelle Vermandere and Sam De Geyter and Heinder De Winter}, keywords = {Geomatics, Semantic Web Technologies, Construction, Close-range sensing, BIM, Point clouds, Photogrammetry} }