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Identify the EPSG code from a .prj file

Project description

Overview

sridentify is a command-line utility and Python API for quickly identifying the EPSG Registry Code from a .prj file typically associated with ESRI Shapefiles. It ships with a SQLite database containing mappings of Well-known Text strings to EPSG codes, the bulk of which was manually sourced and cleaned from an ESRI website. It’s not complete, however, and in the event you test it against a WKT string not in the database it will search the prj2epsg.org API. If the API returns an exact match, that code is returned and saved to the SQLite database. Handling several partial matches is currently planned, but not yet implemented.

sridentify is written in Python, 2- and 3-compatible, and has no external dependencies.

Installation

pip install --user sridentify

The --user is important if installing system-wide (i.e., not in a virtualenv), because the user running sridentify must have write permissions on the SQLite database in the event that sridentify tries to save a new result fetched from the prj2epsg API to the database.

By default pip install --user will install to $HOME/.local and place the executable script in $HOME/.local/bin. You should add this to your $PATH if you want to run sridentify without having to specify the full location to the executable.

TL;DR

Command-Line usage

$ sridentify seattle_land_use.prj
2285

# Example use in conjunction with the `shp2pgsql` command-line utility
# that ships with PostGIS. Assuming you have a PostGIS-enabled database named `seattle`,
# and you have a shapefile called `seattle_land_use` that you want to import into that database
# but you're not sure what spatial projection the shapefile uses.

$ shp2pgsql -s $(sridentify seattle_land_use.prj) -g the_geom -ID seattle_land_use.shp | psql -d seattle

Python API usage

>>> from sridentify import Sridentify

>>> # Read .prj file from the filesystem
>>> ident = Sridentify()
>>> ident.from_file('/path/to/seattle_land_use.prj')
>>> ident.get_epsg()
2285

>>> # Paste in Well-Known Text string directly
>>> ident = Sridentify(prj="""PROJCS["NAD_1983_StatePlane_Washington_North_FIPS_4601_Feet",GEOGCS["GCS_North_American_1983",DATUM["D_North_American_1983",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic"],PARAMETER["False_Easting",1640416.666666667],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-120.8333333333333],PARAMETER["Standard_Parallel_1",47.5],PARAMETER["Standard_Parallel_2",48.73333333333333],PARAMETER["Latitude_Of_Origin",47.0],UNIT["Foot_US",0.3048006096012192]]""")
>>> ident.get_epsg()
2285

Background

More and more governments and organizations are making their GIS data available to the public on open data portals. Local governments typically store and use GIS data in the map projection most appropriate for their location on planet Earth. For the United States, this is typically the State Plane Coordinate System. Other common systems are Universal Transverse Mercator, or a highly localized system that is accurate only within the geographic boundaries of the entity’s jusrisdiction.

ESRI Shapefiles are a common format for publishing GIS data, although a “shapefile” with the .shp extension is really just data describing the geometry. Shapefiles are typically bundled with a dBase file ( .dbf extension ) which contains data attributes about the geometry and a small text file describing the spatial reference system of the geomtry in WKT format.

sridentify is not meant to be a full-fledged client library to the actual EPSG database, for that you’re probably looking for something like python-epsg

Rather, sridentify is for those looking to quickly identify the EPSG code of a shapefile, especially when importing into PostGIS . Of course, you could use ogr2ogr to convert everything into a web-friendly projection, like:

$ ogr2ogr -f PostgreSQL -t_srs EPSG:4326 PG:dbname=seattle seattle_land_use.shp

But transforming spatial data from one projection to another is a lossy operation and can result in coordinate drift. Ideally, you would store the original data in its original coordinate system and then transform copies as needed.

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