6. Remapping¶
Remapping is the process of mapping satellite data to a uniform grid. Mapping data to a uniform grid makes it easier to view, manipulate, and store the data. Some instrument data is provided to the user already gridded (ex. VIIRS EDR Flood, ABI L1B data) and others are not (ex. VIIRS SDR or older GOES satellites).
In Geo2Grid it is possible to perform the gridding (reprojecting) process for ungridded data or to re-project already gridded data. Mapping input data in order to create a high quality image can be a complicated process. There are different techniques that can be used to create an output image based on what grid (projection) is chosen and what algorithm is used to map input pixel to output pixel. Geo2Grid offers various options that are described below. Defaults are also configured to provide a good result without any customization necessary.
6.1. Native Resampling¶
Native resampling is a special type of resampling that keeps input data in its
original projection, but replicates or averages data when necessary to make
other processing in Geo2Grid easier. Native resampling is the default for all
data that is already gridded (ABI, AHI, etc) or when a native grid is specified
by the user on the command line (-g MIN
). It can also be specified on the
command line by using --method native
. See the Command Line Arguments
section below for more details and the options available.
6.2. Elliptical Weighted Averaging Resampling¶
Elliptical Weighted Averaging (EWA) resampling is the default resampling method
for a lot of scan-based polar-orbiting instrument data. This method uses the
size of each instrument scan to determine a weight for each pixel. All input
pixels that map to output pixels are weighted and averaged. This helps
produce an image that is typically higher quality than those produced by
nearest neighbor. It fits an ellipse to the data in the two
axes based upon the --weight-delta-max
and the --weight-distance-max
options and then filters the texture with a Gaussian filter function.
It can be specified on the command line by using --method ewa
.
6.3. Nearest Neighbor Resampling¶
Nearest neighbor resampling is the most basic form of resampling when gridding
data to another grid. This type of resampling will find the nearest valid input
pixel for each pixel in the output image. If a valid pixel can’t be found near
a location then an invalid (transparent) pixel is put in its place. Controlling
this search distance and other options are described below in the Command Line
Arguments section. Nearest neighbor resampling can be specified on the command line
with --method nearest
and is the default when non-native grids are specified
to the command line (-g my_grid
) for gridded data or if polar-orbiting
instrument data is not scan-based (required for EWA).
Note that nearest neighbor resampling can cache intermediate calculations to files
on disk when the same grid is used. For example, the calculations required to
resample ABI L1B data to the same output grid for each time step are the same.
If a directory is specified with the --cache-dir
command line flag, this can
greatly improve performance. This has no benefit for polar-orbiting swath-based
data.
6.4. Grids¶
Geo2Grid uses the idea of “grids” to define the output geographic location that images will be remapped to. Grids are also known as “areas” in the SatPy library. These terms may be used interchangeably through this documentation, especially in low-level parts.
Geo2Grid uses grids defined by a PROJ.4 projection specification. Other parameters that define a grid like its width and height can be determined dynamically during this step. A grid is defined by the following parameters:
Grid Name
PROJ.4 String (either lat/lon or metered projection space)
Width (number of pixels in the X direction)
Height (number of pixels in the Y direction)
Cell Width (pixel size in the X direction in grid units)
Cell Height (pixel size in the Y direction in grid units)
X Origin (upper-left X coordinate in grid units)
Y Origin (upper-left Y coordinate in grid units)
Geo2Grid supports static and dynamic grids. Grids are static if they have all of the above attributes defined. Grids are dynamic if some of the attributes are not defined. These attributes are then computed at run time based on the data being remapped. Only width/height and x/y origin can be unspecified in dynamic grids. SatPy areas are also supported by Geo2Grid, but must be specified in SatPy’s typical “areas.yaml” file.
For information on defining your own custom grids see the Custom Grid documentation.
6.5. Remapping and Grid Command Line Arguments¶
usage: polar2grid.sh -r <reader> -w <writer> [-h] [--method {native,nearest}] [-g [GRIDS ...]] [--grid-coverage GRID_COVERAGE] [--cache-dir CACHE_DIR] [--grid-configs GRID_CONFIGS [GRID_CONFIGS ...]]
[--ll-bbox lon_min lat_min lon_max lat_max] [--antimeridian-mode {modify_extents,modify_crs,global_extents}] [--radius-of-influence RADIUS_OF_INFLUENCE]
6.5.1. Resampling¶
- --method
Possible choices: native, nearest
resampling algorithm to use (default: native)
- -g, --grids
Area definition to resample to. Empty means no resampling (default: “MAX”)
- --grid-coverage
Fraction of target grid that must contain data to continue processing product.
Default: 0.1
- --cache-dir
Directory to store resampling intermediate results between executions. Not used with native resampling or resampling of ungridded or swath data.
- --grid-configs
Specify additional grid configuration files. (.conf for legacy CSV grids, .yaml for SatPy-style areas)
Default: ()
- --ll-bbox
Crop data to region specified by lon/lat bounds (lon_min lat_min lon_max lat_max). Coordinates must be valid in the source data projection. Can only be used with gridded input data.
- --antimeridian-mode
Possible choices: modify_extents, modify_crs, global_extents
Behavior when dynamic grids are converted to ‘frozen’ grids and data crosses the anti-meridian. Defaults to ‘modify_crs’ where the prime meridian is shifted 180 degrees to make the result one contiguous coordinate space. ‘modify_extents’ will attempt to surround the data but will often cause artifacts over the antimeridian. ‘global_extents’ will force the X extents to -180 and 180 to create one large grid. This currently only affects lon/lat projections.
Default: “modify_crs”
- --radius-of-influence
Specify radius to search for valid input pixels for nearest neighbor resampling (–method “nearest”). Value is in geocentric meters regardless of input or output projection. By default this will be estimated based on input and output projection and pixel size.