Hi,
I was investigating the possibility of comparing a random
WKT file found along with a shapefile or grid coverage
against the EPSG database to find out the equivalent
EPSG code.
Consider the following random wkt file contents:
GEOGCS["GCS_North_American_1983",DATUM["North_American_Datum_1983",SPHEROID["GRS_1980",6378137,298.257222101]],PRIMEM["Greenwich",0],UNIT["Degree",0.017453292519943295]]
which gets interpreted by parse and then toWkt into:
GEOGCS["GCS_North_American_1983",
DATUM["North_American_Datum_1983",
SPHEROID["GRS_1980", 6378137.0, 298.257222101]],
PRIMEM["Greenwich", 0.0],
UNIT["degree", 0.017453292519943295],
AXIS["Lon", EAST],
AXIS["Lat", NORTH]]
and the equivalent EPSG definition, EPSG:4296:
GEOGCS["NAD83",
DATUM["North American Datum 1983",
SPHEROID["GRS 1980", 6378137.0, 298.257222101,
AUTHORITY["EPSG","7019"]],
TOWGS84[1.0, 1.0, -1.0, 0.0, 0.0, 0.0, 0.0],
AUTHORITY["EPSG","6269"]],
PRIMEM["Greenwich", 0.0, AUTHORITY["EPSG","8901"]],
UNIT["degree", 0.017453292519943295],
AXIS["Geodetic latitude", NORTH],
AXIS["Geodetic longitude", EAST],
AUTHORITY["EPSG","4269"]]
Now, there are a couple of issues here. The first one
is that CRS.parseWkt has create a lat/lon CRS, whilst
the EPSG one one has swapped axis.
I hope that forcing lon/lat axis would get me a lon/lat
one out of the epsg database, but a modified original wkt that forces
the same axis order as wkt won't match anyways:
GEOGCS["GCS_North_American_1983",DATUM["North_American_Datum_1983",SPHEROID["GRS_1980",6378137,298.257222101]],PRIMEM["Greenwich",0],UNIT["Degree",0.017453292519943295],AXIS["Lat",NORTH],AXIS["Lon",EAST]]
because even using AbstractIdentifiableObject.equals(xxx, false) to
avoid metadata comparison, axis names and such are considered to be
relevant, and this makes it impossible to compare them.
I would like a more lenient way to do the comparison, that uses
only the spheroid parameters, the projection parameters, primem, and
unit. Is there any way to get it?
I could code a special comparator for each kind of CRS (projected,
geographic and the like) but was wondering if there is a better way,
and if I'm making some mistake in assuming the more lenient method
is a good one.
Cheers
Andrea
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