Missing Millions Settlement Detection (1)

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Finished
Uganda
HOT
Jul 28, 2021
Missing Millions Settlement Detection (1)

Project overview

This special MapSwipe project involves looking at before and after imagery to check for the development of settlements - it uses low resolution imagery (20 times less sharp than the imagery we typically use on MapSwipe). We are not looking for individual buildings here, in fact it will not be possible to see these, instead we're looking for new clusters of buildings. Millions of individuals living in informal refugee and IDP settlements are estimated to be missing from national surveys, yet they are the world’s most vulnerable populations - displaced and resettled due to disaster, development and/or conflict and violence. The Missing Millions research project in collaboration with Oregon State University and funded by NASA is looking to identify new and expanding informal settlements. The use of low resolution but high-frequency open Sentinel imagery in this project allows for monitoring and identification of settlements quickly on a large scale.

75755
km2
562
Contributors
Project Completion
100% completed
020406080100Jul 28, 21Aug 09, 21Aug 21, 21Sep 03, 21Sep 15, 21Sep 28, 21
Last updated: May 25, 2024, 11:55:01 PM

Download the data

Below you'll find the data downloads for this MapSwipe project, including a GeoJSON file that can be imported into the HOT Tasking Manager for more detailed mapping of the area. If you need more information or if you have a special request related to MapSwipe data get in contact with the team at the Heidelberg Institute for Geoinformation Technology
Aggregated Results
Aggregated Results. This gives you the unfiltered MapSwipe results aggregated on the task level. This is most suited if you want to apply some custom data processing with the MapSwipe data, e.g. select only specific tasks. Check our documentation for more details. (Note that you need to unzip this .gz file before you can use it.)
csv
0.3 MB
Download
Aggregated Results (with Geometry)
Aggregated Results. This gives you the unfiltered MapSwipe results aggregated on the task level. This is most suited if you want to apply some custom data processing with the MapSwipe data, e.g. select only specific tasks. Check our documentation for more details. (Note that you need to unzip this .gz file before you can use it.)
geojson
0.3 MB
Download
HOT Tasking Manager Geometries
This dataset contains shapes that are ready to use in the HOT Tasking Manager. Currently, the geometries consist of maximum 15 MapSwipe Tasks, where at least 35% of all users indicated the presence of a building by classifying as "yes" or "maybe"
geojson
0.2 MB
Download
Moderate to High Agreement Yes Maybe Geometries
This dataset contains all results where at least 35% of users submitted a "yes" or "maybe" classification. The output dataset depicts the union of all selected results.
geojson
0.3 MB
Download
Groups
Groups. (Note that you need to unzip this .gz file before you can use it.)
csv
3.3 kB
Download
History
History
geojson
6.3 kB
Download
Results
This gives you the unfiltered MapSwipe results. (Note that you need to unzip this .gz file before you can use it.)
csv
0.3 MB
Download
Tasks
Tasks. (Note that you need to unzip this .gz file before you can use it.)
csv
0.2 MB
Download
Users
This dataset contains information on the individual contributions per user. This tells you for instance the most active users of this project. (Note that you need to unzip this .gz file before you can use it.)
csv
18.9 kB
Download
Area of Interest
This dataset contains information on the project region.
geojson
0.2 MB
Download

Our license

This project is part of the OpenStreetMap community. The goal is high-quality geographical data, freely accessible and available to everyone. OSM’s reciprocal license protects the data from being appropriated by services that do not share back to OSM.

MapSwipe is released under a "liberal" non-reciprocal license (Creative Commons Attribution). Whenever you want to use the data, just make sure to credit the MapSwipe contributors.