Los Angeles County building import
Switch branches/tags
Nothing to show
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Failed to load latest commit information.


The Great L.A. County Building Import

Join the chat at https://gitter.im/osmlab/labuildings

This repo focuses on the L.A. County building and address import.

Right now we're importing buildings - 1.7 million and counting

You can jump in and follow the guide and select an area to import today.

Why are we doing this?

  • To improve our map! More data will allow more users to create projects and do analysis on a variety of things. How many units are located within 1,000 feet of a freeway? What's the average building age in a neighborhood? What's the tallest building on Sunset Boulevard? This data will tell you.
  • To catch up with other cities. New York has buildings. Seattle has buildings. San Francisco. Portland. Even Bakersfield has buildings. L.A. County should too!
  • Because a big earthquake is coming. Free and open data will assist first responders. And later it will allow folks to update the buildings with tags showing whether they have been destroyed, are dangerous or have been red-tagged.
  • To improve the Los Angeles Times maps Seriously! The Times has been using and contributing to OpenStreetmap for the last four years. A large portion of their interactive web maps are based on the Quiet LA tiles. And the Times has used OSM data to do a lot of maps, including about 700 maps printed in the newspaper (with an OSM credit, of course).
  • Buildings data will encourage more map edits. Once buildings are in the map, people will be able to orient themselves to the shapes, making it easier to add more data, like names or businesses.

More on this project

These scripts generate an OSM file of buildings with addresses per census block groups, ready to be used in JOSM for a manual review and upload to OpenStreetMap. This repository is based heavily on the NYC building import

This README is about data conversion. See also the page on the OSM wiki.

HOW YOU CAN GET INVOLVED: You may want to browse the issues and/or "watch" this repo (see button at the top of this page) to follow along with the discussion. Also join the chat room on Gitter!

Phase Task Contact
Attributes to be Imported Select which fields will be imported and prepend (associate) with an OSM tag Google Spreadsheet, list is displayed below as well Request access to spreadsheet from @cityhubla or discuss in Issue [#3] (https://github.com/osmlab/labuildings/issues/3)
Python Scripting Process datasets to OSM files Questions? Discuss in Issue #9
Import Guidelines Prepare guidelines for import Discuss in Issue #10

LA buildings screenshot

Sample .osm files (not ready for import yet) are in this zip file.

Browse a slippy map of the data here


Python 2.7.x

Installing prerequisites on Mac OSX

# install brew http://brew.sh

brew install libxml2
brew install libxslt
brew install spatialindex
brew install gdal

Installing prerequisites on Ubuntu

apt-get install python-pip
apt-get install python-virtualenv
apt-get install gdal-bin
apt-get install libgdal-dev
apt-get install libxml2-dev
apt-get install libxslt-dev
apt-get install python-lxml
apt-get install python-dev
apt-get install libspatialindex-dev
apt-get install unzip

Set up Python virtualenv and get dependencies

# may need to easy_install pip and pip install virtualenv
virtualenv ~/venvs/labuildings
source ~/venvs/labuildings/bin/activate
pip install -r requirements.txt


Run all stages:

# Download all files and process them into a building
# and an address .osm file per district.

You can run stages separately, like so:

# Download and expand all files, reproject
make download

# Chunk address and building files by census block group
# (this will take a long time)
make chunks

# Generate importable .osm files.
# This will populate the osm/ directory with one .osm file per
# census block group.
make osm

# Clean up all intermediary files:
make clean

# For testing it's useful to convert just a single district.
# For instance, convert block group 060372735024:
make chunks # will take a while
python merge.py 060372735024 # Should be fast
python convert.py merged/buildings-addresses-060372735024.geojson # Fast


  • Cleans address names
  • Exports one OSM XML building and address file per LA county block group
  • Conflates buildings and addresses (only when there is one address point inside a building polygon)
  • Exports remaining addresses as points (for buildings with more than one address, or addresses not on a building)
  • Handles multipolygons
  • Simplifies building shapes

Attribute mapping

See the convert.py script to see the implementation of these transformations.

Address attributes

Attribute OSM Equivalent Dataset used Description Add/Ignore? Notes
AIN LA County Address Points Parcel this address falls inside Ignore
Numprefix addr:housenumber LA County Address Points Number prefix Add These are extremely rare (only 33 of them), mainly showing up for addresses in Lakewood Center Mall, Lakewood CA. Handling these would require treating addr:housenumber as a string, not an integer. However, the OSM wiki says this is permitted.
Number addr:housenumber LA County Address Points House Number Add
NumSuffix addr:housenumber LA County Address Points House Number Suffix (1/2, 3/4 etc) Add
PreMod addr:street LA County Address Points Prefix Modifier Add Examples: OLD RANCH ROAD, LOWER ASUZA ROAD
PreDir addr:street LA County Address Points Prefix Direction (E, S, W, N) Add Examples: SOUTH RANCH ROAD
PreType addr:street LA County Address Points Prefix Type (Ave, Avenida, etc) Add Examples: NORTH VIA SORRENTO, RUE DE LA PIERRE
STArticle addr:street LA County Address Points Street Article (de la, les, etc) Add Examples: RUE DE LA PIERRE. Change to titlecase
StreetName addr:street LA County Address Points Street Name Add Change to titlecase (but full lowercase on numeral suffixes "st", "nd", "rd", "th")
PostType addr:street LA County Address Points Post Type (Ave, St, Dr, Blvd, etc) Add Change to titlecase
PostDir addr:street LA County Address Points Post Direction (N, S, E, W) Add Examples: MARINA DRIVE SOUTH. Note: the data is already expanded into "NORTH", "SOUTH", etc. We do not condense into "N", "S". Change to Titlecase
PostMod addr:street LA County Address Points Post Modifier (OLD, etc) Add Note: this is always null in the current data. Treat like PreMod for consistency. Change to titlecase
UnitType LA County Address Points Unit Type (#, Apt, etc) - where these are known Ignore???
UnitName addr:unit LA County Address Points Unit Name (A, 1, 100, etc) Add
Zipcode addr:postcode LA County Address Points Zipcode Add
Zip4 LA County Address Points Not currently filled out Ignore
LegalComm is_in:city LA County Address Points Legal City or primary postal city in Unincorporated Areas Add Fall back to this if PCITY1 is null. Potentially could map this to is_in:city, but given that OSM already has good city boundaries this seems unnecessary.
PostComm1 addr:city LA County Address Points Primary Postal Community Ignore
PostComm2 LA County Address Points Secondary Postal Community Ignore
PostComm3 LA County Address Points Third Postal Community Ignore
Source LA County Address Points source of the address point, one of: Assessor, LACity, Regional Planning, other Ignore this generally corresponds to whichever city the address falls within
SourceID LA County Address Points ID of the Address in the source system Ignore
MADrank LA County Address Points Method Accuracy Description (MAD) provides a number between 1 and 100 detailing the accuracy of the location. Ignore
PCITY1 addr:city 1st postal city (from the USPS) add this is null for 1469 records. When null, fall back to LegalComm. Change to titlecase
PCITY2 2nd postal city (from the USPS) ignore mostly null or same as LegalComm. Always null when PCITY1 is null.
PCITY3 3rd postal city (from the USPS) ignore mostly null. Always null when PCITY1 is null.

Building attributes

Attribute OSM Equivalent Dataset used Description Add/Ignore? Notes
CODE Ignore Note: only CODE=Building is used for this import. We ignore CODE='Courtyard'. This filtering step happens in the Makefile
BLD_ID lacounty:bld_id Building Outlines Unique Building ID Add Special OSM Tag
HEIGHT height Building Outlines The height of the highest major feature of the building (not including roof objects like antennas and chimneys) Add map to tag, only if height >0
ELEV ele Building Outlines The elevation of the building Add map to elevation, only if elevation > 0
AREA Building Outlines Roof Area Ignore Mostly null
SOURCE Building Outlines The data source (either LARIAC2, Pasadena, Palmdale, or Glendale) Ignore
AIN Building Outlines The parcel ID number Ignore Used to map stray addresses to buildings and link datasets
Shape_Leng Building Outlines Ignore
Shape_Area area Building Outlines Ignore
GeneralUseType building Assessor 2015 General use type of the property Add
SpecificUseType building:use Assessor 2015 More specific use type of the property Add
YearBuilt start_date Assessor 2015 Year property was originally built Add
EffectiveYearBuilt Assessor 2015 Effective year built taking into account subsequent construction, remodeling, building maintenance, etc. what is this?
SpecificUseDetail1 amenity Assessor 2015 More specific use type of the property Add
SpecificUseDetail2 Assessor 2015 Additional property usage detail
SQFTmain Assessor 2015 Total square footage of the main structure(s), Ignore
Bedrooms Assessor 2015 Total number of bedrooms.
Bathrooms Assessor 2015 Total number of bathrooms.
Units building:units Assessor 2015 Total number of living units. Add