Grid definition of the Discrete Global Grid (DGG) for ESA CCI SM and C3S SM.
Grid definition of the 0.25 degree Discrete Global Grid (DGG) used for the creation of the CCI soil moisture products and the Copernicus Climate Change Service products.
For the full documentation click here, or follow the docs-badge at the top.
The package is available on pypi and can be installed via pip:
pip install smecv_grid
Loading and using the smecv grid
The smecv_grid package contains the global quarter degree (0.25x0.25 DEG) grid definition, used for organising the ESA CCI SM and C3S SM data products. It contains masks for:
- Land Points (default)
- Dense Vegetation (AMSR-E LPRMv6 VOD>0.526),
- Rainforest Areas
- One or multiple ESA CCI LC classes (reference year 2010)
- One or multiple Koeppen-Geiger climate classes (Peel et al. 2007, DOI:10.5194/hess-11-1633-2007).
For more information on grid definitions and the usage of grids, we refer to the pygeogrids package in the background.
Loading the grid
For loading the grid, simply run the following code. Then use it as described in pygeogrids
from smecv_grid import SMECV_Grid_v052 # Load a global grid glob_grid = SMECV_Grid_v052(subset_flag=None) # Load a land grid land_grid = SMECV_Grid_v052(subset_flag='land') # Load a rainforest grid rainforest_grid = SMECV_Grid_v052(subset_flag='rainforest') # Load grid with points where VOD > 0.526 (based on AMSR-E VOD) dense_vegetation_grid = SMECV_Grid_v052(subset_flag='high_vod') # Load a grid with points over urban areas urban_grid = SMECV_Grid_v052(subset_flag='landcover_class', subset_value=190.) # Load a landcover with points over grassland areas grassland_grid = SMECV_Grid_v052(subset_flag='landcover_class', subset_value=[120., 121., 122., 130., 180.]) # Load a climate grid with points over tropical areas tropical_grid = SMECV_Grid_v052(subset_flag='climate_class', subset_value=[0., 1., 2.])
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