I love location data – it tells so many stories, and shows so many scenarios of our past, present and future. You must learn how to manipulate geographic information if you want to stay relevant in urban planning.
Check the Find GIS data page if you want to find and download about a place and to use in these tools.
GIS and mapping
- Quantum GIS (QGIS) – Free, open source software that works on Mac, Linux, and Windows. QGIS is especially helpful to convert geodata between formats, like KML to shapefile and vice versa. Read all posts about QGIS.
- GRASS – This has very powerful conversion tools, based on OGR, and is essentially a GUI for OGR. I’ve used this to convert shapefiles to DXF files for use in AutoCAD.
- MapWindow – While I continued to figure out the best, fastest and least error prone method to convert shapefiles to KML files, I came across the free and open source MapWindow software.
- uDig – Another GIS application.
- Geocoding sources: This is the most complete list of free and paid geocoding services I’ve seen (all have developer APIs).
- Texas A&M University has a free geocoding and reverse geocoding service.
- GeoGinger – Visualize changes in your geodata. It’s like “git” that thinks geographically (it’s using GeoGit).
- GPS Visualizer – This multi-address geocoder does provide the latitude/longitude coordinates. Read all posts about geocoding.
- Map Stack by Stamen – Quickly and easily design your own map styles.
- GEOLocate – Geocode a place when you don’t know the address.
- DropChop – in-browser GIS; this website can manipulate geodata in many ways that ArcGIS and QGIS can, but do it faster and without download software. However, it’s limited and won’t be able to process large geodatasets.
- OpenRefine – Clean up and get to know your data a little better. Also helpful at creating new data based on existing fields, or fetching data from APIs using your data as parameters. For example, using the Sunlight Labs Congress API, I fetched the U.S. congressional districts for street addresses based on their latitude/longitude coordinates.
- Google Fusion Tables – Quickly share your tabular data, starting from CSV, KML, XLS, or Google Docs formats. Map your data instantaneously. Read all posts about Google Fusion Tables.
- Dedupe – Remove duplicate records from variably-formatted datasets.
Tutorials & instruction
- Web Map Academy – Tutorials on a wide range on publishing online maps with various tools and data sources.
Quality assurance (QA)
- KeepRight – Data consistency checks; for example, is there an intersection node where two highways cross? because there should be one.
- OpenStreetMap Analytics – Visualizes the density/coverage of objects – currently only buildings, rivers, and roads – in an area
- How did you contribute?
- Map Compare
- Nameless roads – Highlights areas of the map that have roads without names; editors can click on the roads and edit them to add the names.
- Hospitals that need areas – Highlights areas of the map that have hospitals that are represented only by points and not areas (buildings).
- Schools that need areas – Like the hospitals map, highlights schools that are represented only by points and not areas (buildings).
- Fixing Sidewalks
- Who’s mapping around me?
- OSM Changeset Analyzer (Osmcha)
- OSM Inspector
- Pelias/Mapzen Search (former)/Geocode.earth geocoder coverage
- Building classification – one of many maps from ITO that visualize data coverage in any part of the world (building classification is one type)
- HOT Export Tool – Select an area of the world to extract download; you can customize the tags that are included in the extract.
- OnOSM – encourage business owners to use this so they can get their locations added to OpenStreetMap without having to edit the map themselves (it works by having them fill out a form, which adds a “note” to the map that OSM editors will see)
- CAD Mapper – Export data as CAD files for architects
- Overpass Turbo
- BigMap 2 – export a large static map image of an area (very difficult to use but it stitches together large areas into a single high-resolution PNG image file)
- Node density map of 2017 edits