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. 2021 Feb 4;11:3037. doi: 10.1038/s41598-021-82404-z

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© The Author(s) 2021

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Cluster dendogram and cumulative distribution density plots for monthly humanitarian OSM building mapping between 2012/01/01 and 2020/05/20. This plot depicts the values for all countries with medium and low human development index (SHDI<0.7). The groups are defined by a hierarchical clustering approach based on a distance matrix derived from dynamic time warping time series similarity analysis. For each group the trajectory for the two countries with highest overall mapping activity are highlighted. We used alpha-3 ISO 3166 codes to refer to the countries: TZA - Tanzania, UGA - Uganda, NPL - Nepal, HTI - Haiti, LAO - Laos, KHM - Cambodia, LBR - Liberia, CAF - Central African Republic, IDN - Indonesia, NGA - Nigeria. Created using Matplotlib 3.3. in Python 3.7.5 (https://www.python.org/).