Wang–Müller algorithm in PostGIS

This is a work-in-progress implementation following "Line generalization based on analysis of shape characteristics" by Wang and Müller, 1998.

Structure

There will be 2 deliverables from this folder:

• wm.sql, the implementation.
• paper mj-msc-full.pdf, a MSc thesis, explaining the whole thing.

It contains a few supporting files, notably:

• tests.sql for synthetic unit tests.
• test-rivers.sql for tests with real rivers.
• Makefile to glue everything together.
• layer2img.py converts a PostGIS layer to an embeddable image.
• init.sql initializes PostGIS database for running the tests.
• rivers.sql is an OpenStreetMap snapshot of select rivers (Makefile contains code to update them).
• ... and a few more files to build the paper.

Running it

make help lists the most interesting commands for humans. As of writing:

$ make help
mj-msc-full.pdf    Thesis for publishing
test               Unit tests (fast)
test-rivers        Rivers tests (slow)
clean              Clean the current working directory
clean-tables       Remove tables created during unit or rivers tests
help               Print this help message
wc                 Character and page count
refresh-rivers     Refresh rivers.sql from Open Street Maps

To execute the algorithm, run:

• make test for tests with synthetic data.
• make test-rivers for tests with real rivers. You may adjust the rivers and data source (e.g. use a different country instead of Lithuania) by changing the Makefile and the test files. Left as an exercise for the reader.

Building the paper (pdf)

$ make -j$(nproc) mj-msc-full.pdf

mj-msc.tex results in mj-msc-full.pdf, which will be at some point published. It needs quite a few dependencies, including a functioning Docker environment, postgresql client, geopandas, and a pretty complete LaTeX installation.

License

Same as QGIS and PostGIS: GPL 2.0 or later.