import solara @solara.component def Page(): with solara.Column(align="center"): markdown = """ ## Global Surface Water Information System (GSWIS) ### Introduction We have used five global datasets viz., ESA, ESRI, JRC, OSM and HydroLAKES, to generate a processed multi-band gridded GSWE dataset at 10 m spatial resolution, with each band corresponding to one of the five datasets used. The dataset comprises of a total of 5153 grids, each grid having a 2°×2° dimension. **Click on the GSWIS tab above to visualize the datasets interactively.** ### Datasets #### ESA - **Description:** ESA Worldcover is a 10 m Sentinel-based global LULC dataset available in gridded format with 11 land cover classes - **Website:** - **Year:** 2020 - **Water Classes:** Permanent water bodies [80], Herbaceous wetland [90], Mangroves [95] - **Band Name:** `esa` #### Esri - **Description:** ESRI Global Land cover product is a 10 m Sentinel-based dataset available in gridded format with 10 land cover classes - **Website:** - **Year:** 2020 - **Water Classes:** Water [1], Flooded vegetation [4] - **Band Name:** `esri` #### JRC - **Description:** Landsat-based JRC Yearly Water Classification History is a 30 m surface water extent dataset classified using year-by-year occurrence values from 1984-2021 (Pekel et al., 2016) - **Website:** - **Year:** 2020 - **Water Classes:** Seasonal water [2], Permanent water [3] - **Band Name:** `jrc` #### OSM - **Description:** OSM Water Layers is a 90 m gridded global surface water data generated by extracting surface water features from OpenStreetMap (Yamazaki et al., 2019) - **Website:** - **Year:** 2019 - **Water Classes:** Ocean [1], Large Lake/River [2], Major River [3], Canal [4], Small stream [5] - **Band Name:** `osm` #### HydroLakes - **Description:** HydroLAKES is vector Global Lake dataset derived from merged hydrography (Messager et al., 2016) - **Website:** - **Year:** N/A - **Water Classes:** Global Lakes with size of atleast 10 ha - **Band Name:** `hydrolakes` """ solara.Markdown(markdown)