A python library for distributed fiber optic sensing

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

Tools for distributed acoustic sensing data.

Python framework for Distributed Acoustic Sensing (DAS).

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

An Object Storage for Distributed Acoustic Sensing

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

Wavefield Reconstruction of Distributed Acoustic Sensing with Machine Learning

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

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

DAS image analysis

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

Powerful tool for geophysical data analysis and management. Also includes a simulator to handle multi-phase porous flow

Tools and notebooks for processing FORGE DAS data, including channel interpolation, seismic wave backprojection, data slicing, and pseudo-label generation for tasks like automated phase picking.

An implementation of Attention UNet based on the UNet architecture in https://arxiv.org/html/2403.02791v1; Just for fun.