Official code for STARCOP: Semantic Segmentation of Methane Plumes with Hyperspectral Machine Learning models 🌈🛰️
Official code for Towards Methane Detection On Board Satellites
Official codebase for paper "Fully Automatic Trace Gas Plume Detection"
AutoMergeNet: a neural architecture search approach for automatic plume detection in TROPOMI images
Notebooks for paper "Global Solid Waste Methane Super Emitters Using Hyperspectral Satellites"
Production code for DLQ Algorithm in R
This repository contains two methods to address bias to missing pixels in methane plume detection CNNs. Our methods are transferable to other tasks.
Reproducible multi-source geospatial data pipeline and dataset for methane plume detection under incomplete satellite coverage.
MQ4 Methane (CNG) Gas Sensor Board Module
Winning Submission to 2023 Hackathon of QuantumBlack, AI by McKinsey
Notebooks for paper "HyperGas 1.0: A Python package for analyzing hyperspectral data for greenhouse gases from retrieval to emission rate quantification"
An IoT-based system for real-time monitoring of methane and environmental conditions in landfills using ESP32 and Python.
Confirmed methane plume footprints: from-scratch U-Net segmentation + accept/reject calibration
Kairos Aerospace — independent third-party profile of a public API surface, by API Evangelist. Kairos Aerospace is a methane-detection company founded in 2014 in Sunnyvale, California that provides cost-effective, high-frequency aerial methane detection for the oil and gas industry.
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