A python library for distributed fiber optic sensing

DASPy: A Python Toolbox for DAS (Distributed Acoustic Sensing) data processing.

Python framework for Distributed Acoustic Sensing (DAS).

Tools for distributed acoustic sensing data.

A curated list of DAS tools and resources.

Tools for standardizing Distributed Acoustic Sensing (DAS) metadata

Microseismic event detection on fiber-optic data using machine learning

A Python package for anomaly detection in distributed acoustic sensing (DAS) datasets.

An Object Storage for Distributed Acoustic Sensing

Official reproducible material for Noise attenuation in distributed acoustic sensing data using a guided unsupervised deep learning network

Wavefield Reconstruction of Distributed Acoustic Sensing with Machine Learning

Characterizing Vehicle-Induced Distributed Acoustic Sensing Signals for Accurate Urban Near-Surface Imaging

TelecomTM: A Fine-Grained and Ubiquitous Traffic Monitoring System Using Pre-Existing Telecommunication Fiber-Optic Cables as Sensors

This is a temporary package for low-frequency processing on a spool of distributed acoustic sensing (DAS) data.

Urban sensing using existing fiber-optic networks

Distributed Acoustic Sensing Denoising Using a Self-supervised Conditional Diffusion Model

A Python toolkit for applying Refraction Microtremor analysis to Distributed Acoustic Sensing data

Bridge Monitoring Using Existing Telecommunication Fiber-Optic Networks

DAS image analysis

VTX - Vehicle Tracking Xcorr is a Python-based framework to apply Multichannel Analysis of Surface Waves (MASW) to surface waves generated by vehicles (cars or trains) recorded with Distributed Acoustic Sensing (DAS) systems along roads or railways.