Datasets:
Tasks:
Image Segmentation
Modalities:
Image
Languages:
English
Size:
1K<n<10K
Tags:
methane-detection
thermal-infrared
agriculture
semantic-segmentation
optical-gas-imaging
environmental-monitoring
License:
File size: 5,102 Bytes
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---
license: cc-by-4.0
task_categories:
- image-segmentation
tags:
- methane-detection
- thermal-infrared
- agriculture
- semantic-segmentation
- optical-gas-imaging
- environmental-monitoring
- FLIR-GF77
- enteric-methane
- rumen-fermentation
size_categories:
- 1K<n<10K
language:
- en
pretty_name: Controlled Diet Dataset for Methane Plume Detection
dataset_info:
features:
- name: image
dtype: image
- name: mask
dtype: image
config_name: default
splits:
- name: train
num_bytes: 0
num_examples: 3905
- name: validation
num_bytes: 0
num_examples: 496
- name: test
num_bytes: 0
num_examples: 484
download_size: 0
dataset_size: 0
configs:
- config_name: default
data_files:
- split: train
path:
- "data/train/images/*.png"
- "data/train/masks/*.png"
- split: validation
path:
- "data/validation/images/*.png"
- "data/validation/masks/*.png"
- split: test
path:
- "data/test/images/*.png"
- "data/test/masks/*.png"
class_info:
class_mapping:
0: "background"
1: "control_diet" # 166-171 ppm, 50:50 F:C ratio
2: "low_forage_diet" # 300-334 ppm, 20:80 F:C ratio
3: "high_forage_diet" # 457-510 ppm, 80:20 F:C ratio
pixel_to_class_mapping:
# Note: Dataset has discrepancy between pixel values and class IDs
0: 0 # background
1: 1 # control_diet
2: 3 # pixel value 2 → class 3 (high forage)
3: 2 # pixel value 3 → class 2 (low forage)
gc_concentration_ranges:
1: "166-171 ppm" # Control diet
2: "300-334 ppm" # Low forage diet
3: "457-510 ppm" # High forage diet
diet_descriptions:
1: "Control (50:50 F:C ratio)"
2: "Low Forage (20:80 F:C ratio)"
3: "High Forage (80:20 F:C ratio)"
---
# Controlled Diet Dataset for Methane Plume Detection
[](https://doi.org/10.1049/ipr2.13327)
[](https://creativecommons.org/licenses/by/4.0/)
[](https://www.nifa.usda.gov/)
## 📊 Dataset Overview
This repository contains the CD dataset for methane plume detection, presented in the paper "Optical gas imaging and deep learning for quantifying enteric methane emissions from rumen fermentation in vitro". This dataset contains **4,885 thermal infrared images** of methane plumes captured using FLIR GF77 optical gas imaging technology for semantic segmentation applications in agricultural emissions monitoring.
The images document methane emissions from controlled rumen fermentation experiments under three dietary conditions: Control diet (166-171 ppm), Low forage diet (300-334 ppm), and High forage diet (457-510 ppm).
## 📄 Associated Publication
**"Optical gas imaging and deep learning for quantifying enteric methane emissions from rumen fermentation in vitro"**
*Mohamed G. Embaby, Toqi Tahamid Sarker, Amer AbuGhazaleh, Khaled R. Ahmed*
*IET Image Processing*, January 19, 2025
DOI: [10.1049/ipr2.13327](https://doi.org/10.1049/ipr2.13327)
## 📊 Dataset Details
### Dataset Statistics
| Class | GC Range (ppm) | Diet Description | Train | Val | Test | Total |
|-------|----------------|------------------|-------|-----|------|-------|
| Control | 166-171 | 50:50 F:C ratio | 1,079 | 138 | 133 | 1,350 |
| Low Forage | 300-334 | 20:80 F:C ratio | 1,268 | 162 | 157 | 1,587 |
| High Forage | 457-510 | 80:20 F:C ratio | 1,558 | 196 | 194 | 1,948 |
### Class Mapping
- **Class 0**: Background
- **Class 1**: Control diet methane plumes (166-171 ppm, 50:50 F:C ratio)
- **Class 2**: Low forage diet methane plumes (300-334 ppm, 20:80 F:C ratio)
- **Class 3**: High forage diet methane plumes (457-510 ppm, 80:20 F:C ratio)
**Mask Pixel Values:**
> ⚠️ **Important**: There is a discrepancy between pixel values and class IDs in the mask files:
- Pixel value 0: Background (Class 0)
- Pixel value 1: Control diet (Class 1)
- Pixel value 2: **High forage diet (Class 3)** ⚠️
- Pixel value 3: **Low forage diet (Class 2)** ⚠️
## 📋 License
This dataset is released under the [Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/) license.
## 📚 Additional Resources
For preprocessing methods and code examples, please refer to the [GitHub repository](https://github.com/toqitahamid/controlled-diet-methane-dataset-tools).
## 🙏 Acknowledgments
This work was supported by the USDA National Institute of Food and Agriculture (NIFA) under Grant No. 2022-70001-37404.
## 📜 Citation
This work is published in IET Image Processing (2025, DOI: 10.1049/ipr2.13327).
```bibtex
@article{embaby2025optical,
title={Optical gas imaging and deep learning for quantifying enteric methane emissions from rumen fermentation in vitro},
author={Embaby, Mohamed G and Sarker, Toqi Tahamid and AbuGhazaleh, Amer and Ahmed, Khaled R},
journal={IET Image Processing},
year={2025},
doi={10.1049/ipr2.13327}
}
``` |