SafeBridge is a light-weight open-source tool for the Python programming language that estimates bridge damage indicators with low latency by combining remotely sensed and processed data (Multi-Temporal InSAR time series) with algorithms to process topologies in the geospatial domain.
For furher information and underlying research, you can check the paper from here
- Create a virtual environment and activate it
# via python note: safebridge requires at least version 3.11
python -m venv safebridge_env
# activate the environment
source safebridge_env/bin/activate # for unix
safebridge_env\Scripts\activate.bat # for windows
# or conda
conda create --name safebridge_env python=3.11
# activate environment
conda activate safebridge_env- Clone the reposity to your current directory
git clone https://github.com/SafeStruct/SafeBridge.git- Install the library from directory using pip
pip install -e ./SafeBridge- Testing the installation using tutorial
# before testing one extension needs to be installed
python -c "import duckdb; duckdb.install_extension('spatial')"
# change the directory to examples and run the tutorial
cd SafeBridge/examples
python tutorial.pyIf everything works correctly, you should see a folder called SafeBridgeDB inside the example folder. Inside that folder, you will find the generated PDF report for the entire dataset provided.
The toy MT-InSAR data presented in the repository and used for the tutorial is a synthetic one and has no relation to real data. It was generated with the intent to present how the SafeBridge is working.
This work is supported by Vidi project InStruct, project number 18912, financed by the Dutch Research Council (NWO).