OSM Tools MATLAB Implementation

This is a MATLAB implementation to read OpenStreetMap (OSM) files and extract building and road data from them as data tables. It consists of several functions that parse the OSM file and create a MATLAB data structure of the file contents.

Table of content

• Functions
• Example Usage
• License

Functions

osm_to_struct

This function loads an OSM XML data file and returns a MATLAB data structure of the parsed file.

Input

filename: String of the OSM XML Data file name. The file extension could be .osm or .xml.

Output

struc: MATLAB data structure of the parsed OpenStreetMap file.

get_nodes

This function extracts the nodes data from the struct created by osm_to_struct and returns a MATLAB data table of the nodes in the OpenStreetMap file containing the following columns: id, lat, and lon.

Input

struc: MATLAB data structure of the parsed OpenStreetMap file.

Output

nodes: MATLAB data table of the nodes in the OpenStreetMap file containing the following columns: id, lat, and lon.

id	lat	lon
29052337	55.033	82.973

get_ways

This function extracts the ways data from the struct created by osm_to_struct and returns a MATLAB data table of the ways in the OpenStreetMap file containing the following columns: id, timestamp, node_ids, and tags.

Input

struc: MATLAB data structure of the parsed OpenStreetMap file.

Output

ways: MATLAB data table of the ways in the OpenStreetMap file containing the following columns: id, timestamp, node_ids, and tags.

id	timestamp	node_ids	tags
29052337	03-May-2013	struct array	struct array

get_bounds

This function extracts the bounding box from the struct created by osm_to_struct and returns a MATLAB polyshape structure that defines the boundary of the map.

Input

struc: MATLAB data structure of the parsed OpenStreetMap file.

Output

bounding_box: MATLAB polyshape structure that defines the boundary of the map.

clean_ways

This function removes ways that do not have associated tags from the ways data table returned by get_ways.

Input

ways: MATLAB data table of ways from the parsed OpenStreetMap file containing the following columns: id, timestamp, node_ids, and tags.

Output

cleaned_ways: MATLAB data table of the ways in the OpenStreetMap file containing the following columns: id, timestamp, node_ids, and tags.

classify_ways

This function classifies the ways by adding primary and secondary categories such as building or highway.

Input

ways: MATLAB data table of ways from the parsed OpenStreetMap file containing the following columns: id, timestamp, node_ids, and tags.

id	timestamp	node_ids	tags	primary_category	secondary_category
29052337	03-May-2013	struct array	struct array	"highway"	"tertiary"

Output

classified_ways: MATLAB data table of ways from the parsed OpenStreetMap file containing the following columns: id, timestamp, node_ids, tags, primary_category, and secondary_category.

build_geo_shapes

This function builds the geographical shapes from the ways table based on the primary category.

Input

classified_ways: MATLAB data table of ways from the parsed OpenStreetMap file containing the following columns: id, timestamp, node_ids, tags, primary_category, and secondary_category.
nodes: MATLAB data table of the nodes in the OpenStreetMap file containing the following columns: id, lat, and lon.

Output

shaped_ways: classified_ways table with an additional column that contains the geo shape.

id	timestamp	node_ids	tags	primary_category	secondary_category	shapes
29052337	03-May-2013	struct array	struct array	"building"	"school"	geopolyshape

filter_by_category

This function filters the ways table based on the primary category.

Input

classified_ways: MATLAB data table of ways from the parsed OpenStreetMap file containing the following columns: id, timestamp, node_ids, tags, primary_category, and secondary_category.
category: The category to filter such as building or highway.

Output

category_table: Filtered classified_ways table.

Examples Usage

Here is a basic example that demonstrates how to plot buildings using the osm_to_struct, get_ways, clean_ways, classify_ways, build_geo_shapes, and filter_by_category functions:

```matlab
% Load OSM file
osm_file = 'example.osm';
struc = osm_to_struct(osm_file);

% Extract ways and filter by building category
ways = get_ways(struc);
ways = clean_ways(ways);
classified_ways = classify_ways(ways);
buildings = filter_by_category(classified_ways, 'building');

% Get nodes and build geo shapes
nodes = get_nodes(struc);
shaped_buildings = build_geo_shapes(buildings, nodes);

% Plot buildings
geoplot(shaped_buildings.shapes);
```

We can change the example above to shows the buildings with different colors based on their heights

```matlab
% Load OSM file
osm_file = 'example.osm';
struc = osm_to_struct(osm_file);

% Extract ways and filter by building category
ways = get_ways(struc);
ways = clean_ways(ways);
classified_ways = classify_ways(ways);
buildings = filter_by_category(classified_ways, 'building');

% Get nodes and build geo shapes
nodes = get_nodes(struc);
shaped_buildings = build_geo_shapes(buildings, nodes);

% Get building heights
heights = zeros(1, height(buildings));
for i = 1:(height(buildings))
    building = buildings(i,:);
    tags = building.tags{1};
    tags_table = struct2table(tags);
    tmp = tags_table(tags_table.kAttribute == 'height', :);
    if height(tmp) == 1
        heights(i) = str2double(tmp.vAttribute{1});
    else
        tmp = tags_table(tags_table.kAttribute == "building:levels", :);
        if height(tmp) == 1
            heights(i) = str2double(tmp.vAttribute{1})*3;
        else
            heights(i) = 1;
        end
    end
end

% Plot buildings in different colors based on their heights
geoplot(shaped_buildings.shapes, ColorData=heights);
colorbar;
```

License

The code is released under the MIT License.