Update README.md

README.md

@@ -1,3 +1,44 @@
 ---
 license: cc-by-nc-4.0
+pipeline_tag: image-segmentation
+tags:
+- remote sensing
+- sentinel2
+- landsat
+- floods
 ---
+
+# STARCOP pre-trained models
+
+This repository contains the trained models of the publication:
+
+>  V. Růžička, G. Mateo-Garcia, L. Gómez-Chova, A. Vaughan, L. Guanter, and A. Markham. [Semantic segmentation of methane plumes with hyperspectral machine learning models](https://www.nature.com/articles/s41598-023-44918-6). _Scientific Reports 13, 19999_ (2023). DOI: 10.1038/s41598-023-44918-6.
+
+We include the trained models:
+* **HyperSTARCOP, only mag1c** in folder `models/hyperstarcop_mag1c_only`
+* **HyperSTARCOP, mag1c + rgb**  in folder `models/hyperstarcop_mag1c_rgb`
+
+The following table shows the performance of the models in the AVIRIS test dataset and in the EMIT test dataset:
+![metrics_ml4floods](metrics_ml4floods.png)
+
+In order to run any of these models:
+
+* In a EMIT scene see the tutorial [*Run STARCOP models on raw EMIT data*](https://github.com/spaceml-org/STARCOP/blob/main/notebooks/emit_processing.ipynb).
+
+If you find this work useful please cite:
+
+```
+@article{ruzicka_starcop_2023,
+	title = {Semantic segmentation of methane plumes with hyperspectral machine learning models},
+	volume = {13},
+	issn = {2045-2322},
+	url = {https://www.nature.com/articles/s41598-023-44918-6},
+	doi = {10.1038/s41598-023-44918-6},
+	number = {1},
+	journal = {Scientific Reports},
+	author = {Růžička, Vít and Mateo-Garcia, Gonzalo and Gómez-Chova, Luis and Vaughan, Anna, and Guanter, Luis and Markham, Andrew},
+	month = nov,
+	year = {2023},
+	pages = {19999}
+}
+```