Methane-detection-from-hyperspectral-imagery

Deep Learning based Remote Sensing Methods for Methane Detection in Airborne Hyperspectral Imagery.
https://github.com/satish1901/Methane-detection-from-hyperspectral-imagery

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Sub Category: Emission Observation and Modeling

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Deep Learning based Remote Sensing Methods for Methane Detection in Airborne Hyperspectral Imagery

Host: GitHub
URL: https://github.com/satish1901/Methane-detection-from-hyperspectral-imagery
Owner: satish1901
License: mit
Created: 2020-06-01T22:19:06.000Z (almost 5 years ago)
Default Branch: master
Last Pushed: 2023-02-02T06:46:09.000Z (about 2 years ago)
Last Synced: 2025-04-17T20:38:15.814Z (11 days ago)
Language: Python
Size: 6.35 MB
Stars: 60
Watchers: 3
Forks: 14
Open Issues: 14
Releases: 0
Metadata Files:
- Readme: README.md
- License: LICENSE

Methane-detection-from-hyperspectral-imagery

H-MRCNN introduces fast algorithms to analyze large-area hyper-spectral information and methods to autonomously represent and detect CH4 plumes. This repo contains 2 methods for processing different type of data, Single detector works on 4-channels data and Ensemble detectors works on 432-channels raw hyperspectral data recorded from AVIRIS-NG instrument.

Deep Remote Sensing Methods for Methane Detection in Overhead Hyperspectral Imagery

Satish Kumar*, Carlos Torres*, Oytun Ulutan, Alana Ayasse, Dar Roberts, B S Manjunath.

Official repository of our WACV 2020 paper.

This repository includes:

Source code of single-detector and ensemble detectors(H-MRCNN) built on Mask-RCNN.
Training code for single-detector and ensemble detectors(H-MRCNN)
Pre-trained ms-coco weights of Mask-RCNN
Annotation generator to read-convert mask annotation into json.
Modified spectral library of python
Example of training on your own dataset

GitHub license

The whole repo folder structure follows the same style as written in the paper for easy reproducibility and easy to extend. If you use it in your research, please consider citing our paper (bibtex below)

Citing

If this work is useful to you, please consider citing our paper:

@inproceedings{kumar2020deep,
  title={Deep Remote Sensing Methods for Methane Detection in Overhead Hyperspectral Imagery},
  author={Kumar, Satish and Torres, Carlos and Ulutan, Oytun and Ayasse, Alana and Roberts, Dar and Manjunath, BS},
  booktitle={2020 IEEE Winter Conference on Applications of Computer Vision (WACV)},
  pages={1765--1774},
  year={2020},
  organization={IEEE}
}

Requirements

Linux or macOS with Python ≥ 3.6
Tensorflow <= 1.8
CUDA 9.0
cudNN (compatible to CUDA)

Installation

Clone this repository
Install dependencies

pip install -r requirements.txt

Single-detector

Running single-detector is quite simple. Follow the README.md in single_detector folder

single_detector/README.md

Ensemble-detector

For Running ensemble-detector we need some pre-processing. Follow the README.md in emsemble_detector folder

ensemble_detector/README.md

Owner metadata

Name: Satish Kumar
Login: satish1901
Email:
Kind: user
Description: PhD Candidate, University of California Santa Barbara, Previously at Samsung Research Institute
Website: bisque.ece.ucsb.edu
Location: University of California, Santa Barbara
Twitter:
Company: Vision Research Lab, ECE
Icon url: https://avatars.githubusercontent.com/u/14195838?u=f32551912d2878b6090cb0792de357a8b69f36bd&v=4
Repositories: 29
Last ynced at: 2024-06-11T15:58:37.515Z
Profile URL: https://github.com/satish1901

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Last synced: 7 days ago

Total Commits: 104
Total Committers: 1
Avg Commits per committer: 104.0
Development Distribution Score (DDS): 0.0

Commits in past year: 0
Committers in past year: 0
Avg Commits per committer in past year: 0.0
Development Distribution Score (DDS) in past year: 0.0

Name	Email	Commits
Satish Kumar	y**1@g**m	104

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dependencies (24)

Dependencies

ensemble_detectors/src/Algorithm_1_matchfilter/spectral_lib/setup.py pypi

numpy *

ensemble_detectors/src/Algorithm_1_matchfilter/spectral_lib/spectral.egg-info/requires.txt pypi

numpy *

ensemble_detectors/src/Algorithm_3_mrcnn/mask_rcnn/requirements.txt pypi

IPython *
Pillow *
cython *
h5py *
imgaug *
keras >=2.0.8
matplotlib *
numpy *
scikit-image *
scipy *
tensorflow >=1.3.0

requirements.txt pypi

Keras ==2.2.4
Keras-Applications ==1.0.8
Keras-Preprocessing ==1.1.0
Markdown ==3.1.1
Pillow *
PyWavelets ==1.0.3
PyYAML ==5.1.1
Pygments ==2.4.2
Werkzeug ==0.15.4
absl-py ==0.7.1
astor ==0.8.0
backcall ==0.1.0
bleach ==1.5.0
coloredlogs ==10.0
cycler ==0.10.0
decorator ==4.4.0
gast ==0.2.2
grpcio ==1.22.0
h5py ==2.9.0
html5lib ==0.9999999
humanfriendly ==4.18
imageio ==2.5.0
imutils ==0.5.2
ipython ==7.6.1
ipython-genutils ==0.2.0
jedi ==0.14.0
joblib ==0.13.2
kiwisolver ==1.1.0
mask-rcnn ==2.1
matplotlib ==3.1.1
networkx ==2.3
numpy ==1.16.4
opencv-python ==3.4.3.18
parso ==0.5.0
pexpect ==4.7.0
pickleshare ==0.7.5
prompt-toolkit ==2.0.9
protobuf ==3.9.0
ptyprocess ==0.6.0
pyparsing ==2.4.0
python-dateutil ==2.8.0
scikit-image ==0.15.0
scikit-learn ==0.21.3
scipy ==1.3.0
six ==1.12.0
spectral ==0.19
tensorboard ==1.7.0
tensorflow-gpu ==1.7.0
termcolor ==1.1.0
traitlets ==4.3.2
wcwidth ==0.1.7

single_detector/src/custom-mask-rcnn-detector/mask_rcnn/requirements.txt pypi

IPython *
Pillow *
cython *
h5py *
imgaug *
keras >=2.0.8
matplotlib *
numpy *
scikit-image *
scipy *
tensorflow >=1.3.0

ensemble_detectors/src/Algorithm_3_mrcnn/mask_rcnn/setup.py pypi

single_detector/src/custom-mask-rcnn-detector/mask_rcnn/setup.py pypi

Score: 4.30406509320417

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Methane-detection-from-hyperspectral-imagery

Repository metadata

README.md

Methane-detection-from-hyperspectral-imagery

Deep Remote Sensing Methods for Methane Detection in Overhead Hyperspectral Imagery

Citing

Requirements

Installation

Single-detector

Ensemble-detector

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