Find Features - Find Buildings_Iquitos - Peru (1) HOT
Find Features
Active
Peru
HOT
Jun 2, 2026
Project overview
This project focuses on identifying buildings to prevent the climate and urban resilience challenges facing Iquitos, the world's largest city accessible only by air or river faces challenges due to rapid and unplanned urban growth, recurring seasonal river flooding, extreme heat conditions, and geographic isolation. All these aspects interact to increase the city's vulnerability to environmental, social, and infrastructure-related risks. By assessing these interconnected challenges, the project aims to identify strategies that strengthen urban resilience, improve adaptive capacity, and support sustainable development in one of the most unique and climate-sensitive urban environments in the Peruvian Amazon.
Mapswipe results will be used during [Annual National Anticipatory Mapathons (MANA)](https://www.hotosm.org/en/news/anticipatory-annual-mapathons-innovation-and-collaboration-to-close-mapping-gaps-in-latin-america-and-the-caribbean/), these are an innovative strategy to close mapping gaps in Latin America and the Caribbean, strengthening risk prevention and management.
You can check some of the related projects [here](https://www.hotosm.org/en/projects/participatory-mapping-for-a-sustainable-amazon/)
4445
km2
4
Contributors
Project Completion
0% completed
Last updated: Jun 3, 2026
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.)
GZIP
0.1 MB
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.)
GZIP
0.1 MB
Groups
Groups. (Note that you need to unzip this .gz file before you can use it.)
GZIP
14.7 kB
History
History
CSV
0.4 kB
Results
This gives you the unfiltered MapSwipe results. (Note that you need to unzip this .gz file before you can use it.)
GZIP
34 kB
Tasks
Tasks. (Note that you need to unzip this .gz file before you can use it.)
GZIP
5.3 MB
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.)
GZIP
0.3 kB
Area of Interest
This dataset contains information on the project region.
GEOJSON
0.7 kB
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
8.7 kB
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
12.9 kB
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.
