ease_grid¶
The Equal-Area Scalable Earth (EASE) Grid is a system of projections that is used by NASA and others for distribution of remote sensing data.
You can find some overview information at the NSIDC website. Unfortunately from the documentation it was not clear to me how the latitude, longitude values of certain EASE grid resolutions were calculated. So I wrote this package to find out.
Supported EASE Grids¶
There are two versions of EASE grid systems. This package focuses on EASE-Grid 2.0 at the moment. The data we were reading is disseminated on the global EASE-Grid projection which is why this is the one that is currently supported.
Calculation of any global EASE2 grid should work. Compability with the tiling
scheme of NASA is tested for the global 36km grid (EASE2_M36KM
) and the
global 25km grid (EASE2_M25KM
). The tiling of the 25km grid is only the same
as the NASA tiling if the map_scale
parameter is given explicitely. This
will also be the case for the subgrids of the 36km grid like EASE2_M09KM
and
EASE2_M03KM
. The map_scale
parameters used by NASA are available from
the file ease2_grid_info.pro
inside the easeconv*.tgz
file at
ftp://sidads.colorado.edu/pub/tools/easegrid/geolocation_tools/
How to use¶
To get the coordinates of a EASE2 grid:
from ease_grid import EASE2_grid
egrid = EASE2_grid(36000)
assert egrid.shape == (406, 964)
# these two attributes contain the longitude and latitude coordinate dimension
egrid.londim
egrid.latdim
Contribute¶
We are happy if you want to contribute. Please raise an issue explaining what is missing or if you find a bug. We will also gladly accept pull requests against our master branch for new features or bug fixes.
Development setup¶
For Development we recommend a conda
environment
Guidelines¶
If you want to contribute please follow these steps:
- Fork the ease_grid repository to your account
- make a new feature branch from the ease_grid master branch
- Add your feature
- Please include tests for your contributions in one of the test directories. We use py.test so a simple function called test_my_feature is enough
- submit a pull request to our master branch
Note¶
This project has been set up using PyScaffold 2.5.6. For details and usage information on PyScaffold see http://pyscaffold.readthedocs.org/.