converted RLIS data loaded in the JOSM editor
The majority of Oregon Metro's Regional Land Information System (RLIS) dataset, including the street, trail and bicycle centerline data that is used in this project, is now under the same license as OpenStreetMap (OSM): the Open Database License (ODbL). This means that edits to OSM that are derived from RLIS are fully compliant with OpenStreetMap's contribution terms. Significant resources go into keeping RLIS accurate and up-to-date for the Portland metro region which makes it great resources for the improvement of OSM.
However, RLIS and OSM use a significantly different methodologies to classify attributes and RLIS is released in shapefile format which is not ideal for comparison to existing OSM data in an editing environment. The code here converts the attributes, segmentation (splitting connected lines only when attributes differ, not at each intersection), and file format (.shp --> .osm) of RLIS into a state that mirrors OSM as closely as possible.
Because RLIS is updated quarterly this conversion needs to be executed often to keep pace with those improvements, but once the project dependencies are in place this tool reduces that task to launching a console script and waiting a few minutes for it to run.
As noted above the conversion itself should be a simple task, however if you're inexperienced in setting up a development environment you my have some difficulty in getting the dependencies in place. If you're not interested in deploying the code, but would like to use the data to improve OSM, skip to the Using the Data section below.
The principal dependency of this project is Python 2.7, the code has not been tested with any other version of python. Beyond that the only other requirements are several python packages, most of which are automatically fetched by a tool called buildout. However there are a couple of packages that buildout usually can't retrieve and those libraries, listed below, must be installed manually:
There are number of of ways to get the above tools on Windows, but if you don't already have them installed I recommend using the wheel files found here (links: gdal, fiona, shapely). Several variants of these files are offered so be sure to match the version and bit level of your python instance to the file that you select. For instance to install gdal to 64-bit python 2.7 you would download the .whl file below and use the following command:
pip install GDAL-2.0.3-cp27-cp27m-win_amd64.whl
Install the gdal and geos libraries using your favorite package manager like homebrew or apt-get and buildout should be able to fetch the python bindings that you'll need automatically. On Mac, installing gdal with homebrew would look like this:
brew install gdal
With the dependencies in place follow the steps below to create the file rlis.osm which can be used in OSM editors:
-
if you don't yet have buildout installed do so with the following command:
pip install zc.buildout -
from the home directory of this repo enter the text below, it may take a few minutes for buildout to fetch all of the packages that the project requires:
buildout -
the previous step generates the console script that performs the conversion, to launch it from the home directory enter:
./bin/rlis2osmto obtain information on script usage and options use:
./bin/rlis2osm --help
The execution should take 10 minutes or so and the converted OSM file will be written to: ./data/rlis.osm within the directory structure of your cloned repo (unless you specify a different write location).
Note!!! Upon successfully transforming the data do not add the geometry and/or tags that appear in the output to OpenStreetMap without first considering if they are a good fit for what is being mapped. Much effort has been put into making this conversion as accurate as possible (with reliance on the OSM Wiki), but streets, trails and bicycle infrastructure that have common attributes in RLIS may not always map to the same tags in OSM. Use aerial imagery, the wiki, and any other license compliant resources that you have at your disposal to ensure that the features being added or modified are accurate and in line with OSM convention before uploading them.
I'm presently looking for hosting options for this data so that it can simply be downloaded without having to deal with the code. If you have a hosting solution drop me a line by opening a ticket in the issues section of this repo. In the meantime if you would like a copy of the data and are unable to generate one, email me and I will send it your way.
The Java OpenStreetMap Editor (JOSM) has the ability to load multiple .osm files at once, and bringing rlis.osm into JOSM is a great way to use it as an editing aid. Because the generated file is fairly large at 100+ MB, you may need to allocate more than the default amount of memory to JOSM in order to load rlis.osm without crashing the application. To do so launch JOSM from the terminal or create a shortcut that executes a launch command. To run a josm .jar file from the terminal use:
java -Xmx1G -jar /path/to/your/josm/jar/file/josm-tested.jar
the 1G in the snippet above is the amount of memory being allotted to JOSM (1 gigabyte in this case), you can adjust this, but it should be at least 200 MB to accommodate the file and the app's other data and functionality. If using JOSM webstart (which automatically updates the app each time you open it) you may need to modify its auto-created shortcut. At last check webstart worked out of the box for me on Mac, but on Windows I had to change the shortcut command to something like the code below. If you're unable to get things running you can read more about this here.
"P:\ath\to\java\webstart\javaws.exe" ^
-J-d64 ^
-Xmx=2048m ^
-localfile ^
-J-Djnlp.application.href=https://josm.openstreetmap.de/download/josm.jnlp ^
"P:\ath\to\cached\josm\app"If there are features or functionality that you would like to see added or if something looks off with the data feel free to open a ticket here.