Advanced map techniques November 9 2015 

The Great Subway Map War of 1978 

Arriving in Berlin 

Types of maps Go from A to B Visualise information 

Types of maps “Ten years ago, maps were all about a navigation-use case. We looked at streets, addresses, POIs, maybe a little traffic. That's not true today. Today, it's about imagery, social media, real-time content, and much more. And three years from now, there will be only more data”—especially as location-based sensors increasingly populate the built environment. Marc Prioleau 

Getting Data 

Evaluating datasets 

ParisData: http://opendata.paris.fr/ 

ParisData datasets ● Museums 59 elements, 39 kB ● Theaters 88 elements, 38 kB ● Schools 670 elements, 285 kB ● Green spaces 942 elements, 5.9 MB ● Addresses 145459 elements, 88.2 MB ● ... 

Yelp & Foursquare 

OpenStreetMap 

Buildings 

Buildings 

Navitia.io: transportation data 

General Transit Feed Specification (GTFS) Standard format for public transportation data. Zip archive of CSV files: ● agency.txt ● stops.txt ● routes.txt ● trips.txt ● stop_times.txt ● calendar.txt Optional: fares, transfers, shapes (map) 

Be careful about the licenses Open Database License (ODbL): Constraints: attribute, share-alike (copyleft), keep open Used by: OpenStreetMap, ParisData, Stif Etalab / License ouverte: Constraints: attribute Used by: ParisData License NIO: Constraints: ? Used by: Navitia 

Putting data on the map 

AirMapView AirMapView Google Maps Google Maps Web MapBox 

Data representation: markers 

Data representation: clusters Good : Bad : 

Data representation: clusters ClusterManager clusterManager = new ClusterManager(this, getMap()); getMap().setOnCameraChangeListener(mClusterManager); InputStream inputStream = getResources().openRawResource(R.raw.radar_search); List items = new MyItemReader().read(inputStream); mClusterManager.addItems(items); 

Data representation: areas Standards: ● GeoJSON (ParisData) ● ● ● ● WKT (Navitia : Stif) ● KML (Google Earth) 

Data representation: GeoJSON try { GeoJsonLayer layer = new GeoJsonLayer(map, new JSONObject("...")); layer.addLayerToMap(); } catch (JSONException e) { e.printStackTrace(); } 

Point inside polygon 

Data representation: Heatmaps 

List coordinates = getCoordinatesList(); HeatmapTileProvider provider = new HeatmapTileProvider.Builder() .data(coordinates) .build(); TileOverlayOptions overlayOptions = new TileOverlayOptions().tileProvider(provider); getMap().addTileOverlay(overlayOptions); 

No content

Heatmap: Isochrone 

Representation for the amount of data A few Way too much Data points Markers Clusters Heatmaps 

Further reading AirMapView: https://github.com/airbnb/AirMapView Android map utils: https://github.com/googlemaps/android-maps-utils Sample: https://github.com/acq/AndroidMapSample Slides: http://speakerdeck.com/acq/advanced-map-techniques 

Thank you! @AdrienCouque 

The Great Subway Map War of 1978: http://www.theverge.com/2015/10/29/9630862/new-york-city- subway-maps-mta-google-gps Arriving in Berlin: http://umap.openstreetmap.fr/en/map/arriving-in-berlin-a-map-made-by-refugees- english-_42855 “Vrai plan du métro”: http://carto.metro.free.fr/documents/CartoMetroParis.v3.9.png Transport heatmap: http://vernier.frederic.free.fr/Infovis/horizonMaps/ Isochrone: http://www.atelier01.net/metro/paris/isochrone OpenStreetMap: http://wiki.openstreetmap.org/wiki/ RESOURCES