Parse and normalize a GeoJSON area of interest, using using PostGIS.
📖 Documentation: https://hotosm.github.io/geojson-aoi-parser/
🖥️ Source Code: https://github.com/hotosm/geojson-aoi-parser
- We generally need an Area of Interest (AOI) specified for software to run on a geospatial area.
- GeoJSON is a simple exchange format to communicate this AOI.
- We only care about Polygon data types, but GeoJSON data can be quite variable, with many options for presenting data.
- The goal of this package is to receive GeoJSON data in various forms, then produce a normalised output that can be used for further processing.
- Flexible data input: file bytes, dict, string JSON.
- Flexible geometry input:
- Polygon
- MultiPolygons
- GeometryCollection
- Feature
- FeatureCollection
- Handle multigeometries with an optional merge to single polygon, or split into featcol of individual polygons.
- Handle geometries nested inside GeometryCollection.
- Remove any z-dimension coordinates.
- Warn user if CRS is provided, in a coordinate system other than EPSG:4326.
- Normalised output: FeatureCollection containing Polygon geoms.
If the GeoJSON has an invalid CRS, or coordinates seem off, a warning will be raised.
To halt execution when a warning is raised and act on it:
try:
featcol = parse_aoi(raw_geojson)
except UserWarning as warning:
log.error(warning.message)
msg = "Using a valid CRS is mandatory!"
log.error(msg)
raise HTTPException(HTTPStatus.BAD_REQUEST, detail=msg)
To record warnings, but allow execution to continue:
import warnings
with warnings.catch_warnings(record=True) as recorded_warnings:
featcol = parse_aoi(raw_geojson)
if recorded_warnings:
for warning in recorded_warnings:
if isinstance(warning.message, UserWarning)
# do stuff with warning
logger.warning(f"A warning was encountered: {warning.message}")
- Initially I tried to write a pure-Python implementation of this, no dependencies.
- I underestimated the amount of work that is! It could be possible to reverse engineer C++ Geos or georust/geos, but it's more hassle than it's worth.
- As all of the target install candidates for this package use a db driver anyway, I thought it wisest (and most time efficient) to use the PostGIS Geos implementation (specifically for the unary_union and convex_hull algorithms).
- An additional advantage is the potential to port this to PGLite when the PostGIS extension is available, meaning AOI processing easily in the browser.