Tanga Building Footprints Import

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This is a plan for the addition of building footprint data for Tanga City, Tanzania. The import is currently going through the Import Guidelines steps, and it should be soon an ongoing crowdsourced task.

Goals

The goal is to import building footprint data developed by Ardhi University (ARU) in Collaboration with Tanzania Communication Regulatory Authority (TCRA) in 2021, using 2019 satellite images.

Schedule

  1. Data has already been cleaned and checked for any errors
  2. Existing data on OSM on Tanga city has already been checked and verified it they tally with the generated data
  3. Parties have agreed to share upload data

Data

Data description

These data (building footprints) have been generated by the Ardhi University from a request raised by Tanzania Communication Regulatory Authority. The data were developed between January 2021 and March 2021 by ARU students under supervision of the School of Spatial Planning and Social Science. These building footprints have been developed based on 2019 satellite image. The purpose of these data was to be used in a street code naming and house numbering system.

The data contain the building footprint of all Tanga City, with streets but without names and other attributes

The raw data was in shapefile format compressed to geojson files that can be found here click here to download .

Background

ODbL Compliance verified: YES

The Tanzania Communication Authority and Ardhi University has given full consent of their data to be used in an open street map.

Import Type

The best approach to import this data is manually by the community, with data split in a number of files, that will correspond to an equal number of projects in the HOT Tasking Manager.

Advantages:

  • Any volunteers may join the import effort, at any time (although only skilled mappers should join).
  • We can check, at any time, the mapping progress of the import.
  • We can easily validate each task too, and check the validation progress.
  • Easy to set up.

We will provide a link for each Tasking Manager project showing:

  1. info about the total size (number of buildings)
  2. and expected time of work for each one.

We will open the different projects progressively, when the previous jobs are being finished

The existing data will be checked and overlaid to see any similarities and differences and decide whether to merge or remove data. Attention will be taken to avoid data duplicates during the process. Every required process will be followed to accomplish this task.

Note: Every single cluster and block formed by these building footprints is a foundation of street address system and place and facilities naming. Ardhi University and Tanzania Data Lab are designing micro works which aim at enriching this valuable data set with more attributes which will be shared in the near future

Data Preparation

Data Reduction & Simplification

The building outlines in the source shapefiles will be compared with existing OpenStreetMap data. Buildings already present will not be imported.

Tagging Plans

Some of the tags of the original dataset aren't relevant, so we ignore them. Here we list all the original tags with their corresponding translation into the OSM tagging schema.

Tanga Buildings Key Value Meaning OSM Tags Comments
_Council_ Tanga City Council
_District_ Districts within Tanga region addr:district=*
_Hamlet_ Hamlet within Tanga region addr:hamlet=*
_Subward_ Subward within Tanga region addr:subward=*
_Ward_ Ward within Tanga region addr:ward=*
_building_ Building tag building = yes Original tagging is maintained for existing buildings

Data Transformation

  1. The original file (in shapefile format) was opened with JOSM + Open Data plugin, and saved in osm format.
  2. We deleted all non-relevant tags and translated the info of the rest to produce the proposed tags.
  3. The resulting file will be divided in pieces, one for each Tasking Manager project, again with the JOSM editor.
  4. Any errors detected by JOSM Validator (empty relations, duplicated nodes or ways...) are fixed in the files before publishing Tasking Manager projects.

Changeset tags

Here are the changeset tag we plan to use:

Optional hashtags:

  • #ARU #TANGA #dLab

Data Merge Workflow

This import (data integration) will be done through the HOT Tasking Manager, so the number of people importing the data is unknown. We expect users to be experienced mappers. Among the skills required:

  • Good experience with JOSM.
    • skilled working with buildings. It's needed to know well how to orthogonalize buildings (Q), round buildings (O), combine ways (C) and ungluing (G).
  • Experience with previous imports through the Tasking Manager is not necessary, but a plus.
  • knows how to use JOSM filters.
  • knows how to use the Replace Geometry tool of the UtilsPlugin 2 JOSM plugin (Ctrl+Shift+G), and why it is so interesting.
  • knows how to use the ToDo JOSM plugin.
  • knows how to create and deal with building relations.
  • knows how to deal with conflicts.

References

This import is referenced in the Import Catalogue. Local OSM community will be contacted and notified of import plans. And as the import is related to humanitarian issues, the HOT community will be contacted as an additional measure.

Workflow

  • Choose a task and load the OSM data and the ARU-TCRA Data into JOSM.
  • If the selected tile contains at least one existing building in the OSM layer, configure the Conflation plugin. Then generate matches between the existing OSM data and the ARU-TCRA Data data.
  • If there is no existing building in OSM, simply merge the ARU-TCRA Data layer with the OSM one. Then, using filters, select all buildings in the data layer and add them to the Todo list, so we don't leave any building behind.
  • When finished, upload the data with the specific import OSM user account and the specific changeset tags:
  • If appropriate, manually trace missing buildings. If you are doing this simultaneously, consider using a separate layer for the buildings which you are manually tracing.

Conflation

  • Conflation is explained in the import workflow in the section 5.1 as well as in subsection 5.1.1 and 5.1.2
  • We will make sure that buildings and highways don’t cross each other.
  • The import workflow will basically keep the tagging. All existing tags will be preserved.
  • If an existing building in OSM is no longer visible on the most recent imagery, it will be removed unless it contains any valuable tags but a fixme tag could be added to it.

Acknowledgements

  • OSM Uganda Community from their previous import experience.

QA

Validation of the import will be done by a second user in the Tasking Manager.