pages/01_datasets.py

import solara


@solara.component
def Page():
    with solara.Column(align="center"):
        markdown = """

        GSWIS currently houses five global surface water datasets used to generate a processed, 
        multi-band gridded dataset at 10-meter spatial resolution, with each band corresponding 
        to one of the five datasets used. It also hosts a 10-meter spatial resolution multi-band 
        gridded global composite of surface water occurrence, permanent and seasonal surface water 
        extent, and surface water variability, derived from Dynamic World Land Cover product. 
        **Click on the Explore tab above to visualize the datasets interactively.**

        ### Datasets

        #### European Space Agency (ESA) WorldCover
        - **Description:** ESA WC is a 10-m Sentinel-based gridded global LULC dataset 
        - **Website:** <https://esa-worldcover.org/en/data-access>
        - **Reference**: Zanaga et al 2021. <https://doi.org/10.5281/zenodo.5571936>
        - **Year used in GSWIS:** 2020
        - **Water Classes used in GSWIS:** Permanent water bodies [80], Herbaceous wetland [90], Mangroves [95] 

        #### Environmental Systems Research Institute (ESRI) Global Land Cover(GLC) product
        - **Description:** ESRI GLC is a 10-m Sentinel-based gridded global LULC dataset
        - **Website:** <https://livingatlas.arcgis.com/landcove>
        - **Reference**: Karra et al  2021. <https://doi.org/10.1109/IGARSS47720.2021.9553499>
        - **Year used in GSWIS:** 2020
        - **Water Classes used in GSWIS:** Water [1], Flooded vegetation [4] 

        #### Joint Research Centre (JRC) Global Surface Water (GSW)
        - **Description:** GSW is a 30-m Landsat-based gridded global surface water extent dataset
        - **Website:** <https://global-surface-water.appspot.com/download>
        - **Reference**: Pekel et al 2016. <https://doi.org/10.1038/nature20584>
        - **Year used in GSWIS:** 2020
        - **Water Classes used in GSWIS:** Seasonal water [2], Permanent water [3] from Yearly Water Classification History

        #### OpenStreetMap (OSM) Water Layers
        - **Description:** OSM is a 90-m gridded global surface water data generated by extracting surface water features from OpenStreetMap
        - **Website:** <https://hydro.iis.u-tokyo.ac.jp/~yamadai/OSM_water>
        - **Reference**: Yamazaki et al 2019. <https://doi.org/10.1029/2019WR024873>
        - **Year used in GSWIS:** 2019
        - **Water Classes used in GSWIS:** Ocean [1], Large Lake/River [2], Major River [3]

        #### HydroLakes
        - **Description:** HydroLAKES is vector global lake dataset derived from merged hydrography
        - **Website:** <https://www.hydrosheds.org/products/hydrolakes>
        - **Reference**: Messager et al 2016. <https://doi.org/10.1038/ncomms13603>
        - **Year used in GSWIS:** HydroLAKES is not associated with any specific time or year
        - **Water Classes used in GSWIS:** Global Lakes with size of at least 10 ha

        #### Dynamic World (DW) based global surface water (GSW) dataset
        - **Description:** DW based GSW dataset is a 10-m gridded multi-band global composite derived from Sentinel-2 based Dynamic World Land cover product ([Brown et al., 2022](https://doi.org/10.1038/s41597-022-01307-4)) 
        - **Website:** <https://dynamicworld.app>
        - **Reference**: Rajib and Khare, 2024. <https://doi.org/10.4211/hs.9d60389f55b648149a788a2ff7bc3766>
        - **Year used in GSWIS:** 2015-2023
        - **Water Classes used in GSWIS:** Surface water occurrence, Permanent and Seasonal surface water extent, Surface water variability        


        **Note: Numbers indicate the class ID in the original dataset**

        """

        solara.Markdown(markdown)