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--- |
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license: cc-by-nc-4.0 |
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task_categories: |
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- image-to-image |
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tags: |
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- climate |
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pretty_name: HydroChronos |
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size_categories: |
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- 100K<n<1M |
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--- |
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# HydroChronos |
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<!-- Provide a quick summary of the dataset. --> |
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HydroChronos is designed to forecast water dynamics using multispectral satellite images, climate variables, and DEM. |
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It covers lakes and rivers of the US, Europe, and Brazil. |
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- **Repository:** [GitHub](https://github.com/DarthReca/hydro-chronos) |
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- **Paper:** [Arxiv](https://arxiv.org/abs/2506.14362) |
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## Dataset Details |
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<!-- Provide a longer summary of what this dataset is. --> |
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The dataset comprises Landsat-5 (L) TOA and Sentinel-2 (S) TOA images. There are 6 coherently aligned bands for both satellites: |
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| Landsat | Sentinel | Description | Central Wavelength (L/S) | |
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|:-------:|:--------:|:-----------:|:------------------------:| |
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| B1 | B2 | Blue | 485/492 nm | |
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| B2 | B3 | Green | 560/560 nm | |
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| B3 | B4 | Red | 660/665 nm | |
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| B4 | B8 | NIR | 830/833 nm | |
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| B5 | B11 | SWIR | 1650/1610 nm | |
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| B7 | B12 | SWIR | 2220/2190 nm | |
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They are coupled with climate variables from [TERRACLIMATE](https://www.nature.com/articles/sdata2017191) and Copernicus GLO30-DEM. |
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There is no ground truth. We directly work with Modified Normalized Difference Water Index (MNDWI) |
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- **Curated by:** Daniele Rege Cambrin |
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- **License:** Creative Commons Attribution Non Commercial 4.0 |
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## Dataset Structure |
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<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. --> |
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To load the dataset with TorchGeo, please refer to the [repository](https://github.com/DarthReca/hydro-chronos). |
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All climate data are contained in *climate.h5*. Each identifier contains the following data: |
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| Key | Shape | Data Type | Description | |
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| :-------- | :--------- | :-------- | :------------------------------------ | |
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| `climate` | `(14, T)` | `int16` | Contains the 14 TerraClimate variables. | |
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| `time` | `(T)` | `uint32` | The timestamp for each time step. | |
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The data for the two satellites and DEM are contained in the respective folders. |
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For portability, the whole dataset is divided into parts. You can easily iterate over the whole dataset using the *_main.h5* files, |
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since they contain the [external links](https://docs.h5py.org/en/stable/high/group.html#external-links) to the correct file |
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| Key | Shape | Data Type | Description | |
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| :--- | :--- | :--- | :--- | |
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| `bands` | `(6, T, 256, 256)` | `uint8/16` | Contains the 6 multispectral image bands. | |
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| `dem` | `(1, 256, 256)` | `int16` | Digital Elevation Model for the location. | |
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| `qa_mask` | `(T, 256, 256)` | `bool` | Cloud mask for each time step. | |
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| `months` | `(T,)` | `uint8` | The month (1-12) for each time step. | |
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| `years` | `(T,)` | `int64` | The year for each time step. | |
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| `x` | `(256,)` | `float32` | The x-coordinate of the location in WGS84. | |
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| `y` | `(256,)` | `float32` | The y-coordinate of the location in WGS84. | |
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## Citation |
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<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> |
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```bibtex |
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@misc{cambrin2025hydrochronosforecastingdecadessurface, |
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title={HydroChronos: Forecasting Decades of Surface Water Change}, |
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author={Daniele Rege Cambrin and Eleonora Poeta and Eliana Pastor and Isaac Corley and Tania Cerquitelli and Elena Baralis and Paolo Garza}, |
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year={2025}, |
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eprint={2506.14362}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CV}, |
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url={https://arxiv.org/abs/2506.14362}, |
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} |
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``` |
