Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/anisotropi4/woodpecker

A way to overlay and combine two linear geographic network models
https://github.com/anisotropi4/woodpecker

Last synced: about 2 months ago
JSON representation

A way to overlay and combine two linear geographic network models

Awesome Lists containing this project

README 

        
# Woodpecker

This is a way to overlay and combine two linear geographic network models using the rail centre-line track model and OpenStreetMap rail data as examples. The resulting network model is segmented using a rail waymark point layer and assigns approximate operation reporting points (STANOX) and planning timing point (TIPLOC) locations snapped to the network model segments



## Overview

The centre-line track-model is a dataset published via an Environmental Information Regulations (EIR) [request](https://www.whatdotheyknow.com/request/geospatial_data) by [Network Rail](https://www.networkrail.co.uk/who-we-are/transparency-and-ethics/freedom-of-information-foi) under the Open Government Licence:



Open Street Map contains current and historic mainland Britain railway data [here](https://www.openstreetmap.org/) published under the [Open Database License](https://opendatacommons.org/licenses/odbl/1-0/).



Run the following script:



    $ ./run.sh



This will downloads dependencies, centre-line and OSM data, creates the network overlay and combines this in a [outputx.gpkg](https://github.com/anisotropi4/woodpecker/blob/main/outputx.gpkg) GeoPKG repository. This combined network is then segmented using the waymark point layer and switch, end-point and locations in [segmentx.gpkg](https://github.com/anisotropi4/woodpecker/blob/main/segmentx.gpkg) and assign approximate operation reporting points (STANOX) and planning timing point (TIPLOC) locations snapped to OpenStreetMap and network model segments in [tiploc-location.gpkg](https://github.com/anisotropi4/woodpecker/blob/main/tiploc-location.gpkg)



### Overlay and combine approach

The approach used to overlay and combine data is:



1. create a cropped OSM and centre-line track-model LineString segments within scaled hexagons

2. create line-extended centre-line track-model rectangular polygons within a given hexagon

3. test if the OSM LineStrings are within these rectangular polygons

4. any OSM LineString segments that fall within a centre-line track-model rectangular polygon are discarded.

5. hexagons are classified as to whether they contain no rail, only OSM, only centre-line or a mixture of elements.

6. OSM data in hexagons only containing OSM elements are retained.

7. hexagons with mixed OSM and centre-line data are reassessed but at the next granular hexagon level.

8. the combined OSM only data and centre-line model then seems to give the required result.



### Segmentation approach

The approach used to segment the combined network is:



1. identify waymarks within a rectangle 12 track centre-to-centre separation of the network

2. split linear network features at the near nearest point the the waymark



The centre-to-centre track separation on the rail network is 3.26m



### Rail operation and planning location approach

The approach used to identify rail operation STANOX and planning TIPLOC locations is:



1. snap approximate STANOX locations to nearest OSM linear feature (`ox` layer in [tiploc-location.gpkg](https://github.com/anisotropi4/woodpecker/blob/main/tiploc-location.gpkg) 

2. snap approximate STANOX to combined network-model segement (`sx` layer in [tiploc-location.gpkg](https://github.com/anisotropi4/woodpecker/blob/main/tiploc-location.gpkg)

3. use the Network Rail [CORPUS](https://wiki.openraildata.com/index.php/Reference_Data#Downloading_CORPUS_Data) open rail reference data to link TIPLOC to STANOX locatation 



## Notes



All code is licensed under Apache 2.0 [license](https://github.com/anisotropi4/woodpecker/blob/main/LICENSE), data is licensed under [Creative Commons by Share Alike (CC-SA-4.0)](https://creativecommons.org/licenses/by-sa/4.0/deed.en)