| | --- |
| | license: openrail |
| | datasets: |
| | - DarthReca/hydro-chronos |
| | pipeline_tag: image-segmentation |
| | tags: |
| | - climate |
| | - geospatial |
| | - remote-sensing |
| | - spatiotemporal |
| | - multi-modal |
| | - earth-observation |
| | - time-series |
| | - hydrology |
| | library_name: transformers |
| | --- |
| | |
| | # ACTU for Magnitude Regression |
| |
|
| | <!-- Provide a quick summary of what the model is/does. --> |
| | This is ACTU for direction classification of MNDWI difference. |
| |
|
| | ## Model Details |
| |
|
| | <!-- Provide a longer summary of what this model is. --> |
| | This architecture is a temporal UNet (with ConvLSTMs), featuring an LSTM branch to process climate timeseries and a gating mechanism. |
| | It is designed to receive a timeseries of Sentinel-2 images, DEM, and timeseries of climate variables and output a tri-class mask of future MNDWI direction of change. |
| |
|
| | - **Developed by:** Daniele Rege Cambrin |
| | - **Model type:** ACTU |
| | - **License:** OpenRAIL |
| | - **Repository:** [Github](https://github.com/DarthReca/hydro-chronos) |
| | - **Paper:** [Arxiv](https://arxiv.org/abs/2506.14362) |
| |
|
| |
|
| | ## How to Get Started with the Model |
| | The model is integrated into Transformers, so you can easily load it with the following code: |
| |
|
| | ```python |
| | AutoModel.from_pretrained("DarthReca/actu-direction-classification", trust_remote_code=True, revision=<model_type>) |
| | ``` |
| |
|
| | Load the model with the desired configuration with the *revision* parameter (the branches of this repo). These configurations are available: |
| |
|
| | | Revision | Backbone | DEM | Climate | |
| | |-------------|-----------------|:---:|:-------:| |
| | | main | ConvNeXtV2 Base | No | No | |
| | | dem-climate | ConvNeXtV2 Base | Yes | Yes | |
| |
|
| | ## Training Details |
| | The model is pre-trained on Landsat-5 images and fine-tuned on Sentinel-2 of HydroChronos. |
| |
|
| | ## Citation |
| |
|
| | ```bibtex |
| | @misc{cambrin2025hydrochronosforecastingdecadessurface, |
| | title={HydroChronos: Forecasting Decades of Surface Water Change}, |
| | author={Daniele Rege Cambrin and Eleonora Poeta and Eliana Pastor and Isaac Corley and Tania Cerquitelli and Elena Baralis and Paolo Garza}, |
| | year={2025}, |
| | eprint={2506.14362}, |
| | archivePrefix={arXiv}, |
| | primaryClass={cs.CV}, |
| | url={https://arxiv.org/abs/2506.14362}, |
| | } |
| | ``` |
| |
|
| | ## Licensing |
| | The project uses third-party software. For detailed information on the licensing of each component, please see the [**NOTICE.md**](NOTICE.md) file. |
| |
|
