Add text
Browse files- pages/00_home.py +38 -3
pages/00_home.py
CHANGED
|
@@ -9,14 +9,49 @@ def Page():
|
|
| 9 |
|
| 10 |
### Introduction
|
| 11 |
|
| 12 |
-
We have used
|
| 13 |
to generate a processed multi-band gridded GSWE dataset at 10 m spatial
|
| 14 |
-
resolution, with each band corresponding to one of the
|
| 15 |
The dataset comprises of a total of 5153 grids, each grid having a 2°×2° dimension.
|
| 16 |
|
| 17 |
### Datasets
|
| 18 |
|
| 19 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 20 |
|
| 21 |
"""
|
| 22 |
|
|
|
|
| 9 |
|
| 10 |
### Introduction
|
| 11 |
|
| 12 |
+
We have used five global datasets viz., ESA, ESRI, JRC, OSM and HydroLAKES,
|
| 13 |
to generate a processed multi-band gridded GSWE dataset at 10 m spatial
|
| 14 |
+
resolution, with each band corresponding to one of the five datasets used.
|
| 15 |
The dataset comprises of a total of 5153 grids, each grid having a 2°×2° dimension.
|
| 16 |
|
| 17 |
### Datasets
|
| 18 |
|
| 19 |
+
#### ESA
|
| 20 |
+
- **Description:** ESA Worldcover is a 10 m Sentinel-based global LULC dataset available in gridded format with 11 land cover classes
|
| 21 |
+
- **Website:** <https://esa-worldcover.org/en/data-access>
|
| 22 |
+
- **Year:** 2020
|
| 23 |
+
- **Water Classes:** Permanent water bodies [80], Herbaceous wetland [90], Mangroves [95]
|
| 24 |
+
- **Band Name:** `esa`
|
| 25 |
+
|
| 26 |
+
#### Esri
|
| 27 |
+
- **Description:** ESRI Global Land cover product is a 10 m Sentinel-based dataset available in gridded format with 10 land cover classes
|
| 28 |
+
- **Website:** <https://livingatlas.arcgis.com/landcove>
|
| 29 |
+
- **Year:** 2020
|
| 30 |
+
- **Water Classes:** Water [1], Flooded vegetation [4]
|
| 31 |
+
- **Band Name:** `esri`
|
| 32 |
+
|
| 33 |
+
#### JRC
|
| 34 |
+
- **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)
|
| 35 |
+
- **Website:** <https://esa-worldcover.org/en/data-access>
|
| 36 |
+
- **Year:** 2020
|
| 37 |
+
- **Water Classes:** Seasonal water [2], Permanent water [3]
|
| 38 |
+
- **Band Name:** `jrc`
|
| 39 |
+
|
| 40 |
+
#### OSM
|
| 41 |
+
- **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)
|
| 42 |
+
- **Website:** <https://hydro.iis.u-tokyo.ac.jp/~yamadai/OSM_water>
|
| 43 |
+
- **Year:** 2019
|
| 44 |
+
- **Water Classes:** Ocean [1], Large Lake/River [2], Major River [3], Canal [4], Small stream [5]
|
| 45 |
+
- **Band Name:** `osm`
|
| 46 |
+
|
| 47 |
+
#### HydroLakes
|
| 48 |
+
- **Description:** HydroLAKES is vector Global Lake dataset derived from merged hydrography (Messager et al., 2016)
|
| 49 |
+
- **Website:** <https://www.hydrosheds.org/>
|
| 50 |
+
- **Year:** N/A
|
| 51 |
+
- **Water Classes:** Global Lakes with size of atleast 10 ha
|
| 52 |
+
- **Band Name:** `hydrolakes`
|
| 53 |
+
|
| 54 |
+
|
| 55 |
|
| 56 |
"""
|
| 57 |
|