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--- |
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license: cc-by-4.0 |
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task_categories: |
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- image-segmentation |
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language: |
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- en |
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tags: |
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- geografy |
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- wildfire |
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- nature |
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- preservation |
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pretty_name: IGNIS - Intelligent Geospatial Network for Incendiary Surveillance |
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size_categories: |
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- n<1K |
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--- |
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# IGNIS - Intelligent Geospatial Network for Incendiary Surveillance |
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A dataset for **image segmentation of wildfires** in satellite/aerial imagery. The dataset contains **paired images and labels**, where each label highlights wildfire-affected regions. |
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## Dataset Summary |
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This dataset was created to support research in **wildfire detection, monitoring, and environmental risk assessment**. It can be used for training and evaluating segmentation models. |
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* **Task:** Image Segmentation |
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* **Domain:** Remote sensing / Environmental monitoring |
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* **License:** CC BY 4.0 |
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## Supported Tasks |
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* **Image Segmentation** – Identify wildfire regions pixel-by-pixel. |
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* **Potential Applications:** |
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* Early wildfire detection |
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* Environmental monitoring |
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* Risk modeling and prevention systems |
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## Dataset Structure |
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### Data Splits |
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The dataset is divided into: |
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* `train` |
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* `validation` |
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* `test` |
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## Data Fields |
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* **image** (`Image`) – RGB image |
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* **label** (`Label`) – TXT file containing coordinates for the polygons following YOLOv11 format |
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Example: |
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``` |
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{ |
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"image": "train/images/image_001.jpg", |
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"label": "train/labels/image_001.txt" |
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} |
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``` |
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## Dataset Creation |
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### Motivation |
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Wildfires are an increasing threat worldwide. This dataset was built to help researchers and engineers develop segmentation models that can detect wildfire-affected areas in aerial/satellite imagery. |
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This dataset is originally a personal project, but anyone with expert knowledge in meteorological, geographic, geophisical and related areas might feel free to reach out and help expand the dataset and increase its quality. |
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### Source Data |
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* **Collection Process:** Images were sourced from open satellite/aerial datasets. |
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* **Annotation Process:** Masks were generated using a mix between manual labelling and automatic polygon generation thanks to Roboflow's tools. |
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### Annotations |
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* **Annotation Guidelines:** Each class is labeled as: |
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* 0 → Burned Ground (burnt) |
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* 1 → Smoke Cloud (smoke_cloud) |
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* 2 → Smoke Column (smoke_column) |
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* 3 → Wildfire (wildfire) |
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## Licensing Information |
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* **Dataset License:** CC BY 4.0 |
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## Citation |
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If you use this dataset, please cite: |
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``` |
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@dataset{ignis, |
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title = {Intelligent Geospatial Network for Incendiary Surveillance}, |
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author = {Matheus J. G. Silva}, |
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year = {2025}, |
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url = {https://huggingface.co/datasets/matjs/ignis} |
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} |
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``` |
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## Acknowledgements |
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* [NASA FIRMS - Fire Information for Resource Management System](https://firms.modaps.eosdis.nasa.gov/) |
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* [NASA Earth Observatory](https://earthobservatory.nasa.gov) |
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* Inspired by the growing need for **AI-assisted wildfire monitoring**. |
