https://orcid.org/0000-0002-5553-4152
![Sample our Geography journals, sign in here to start your FREE access for 14 days]({"type":"image" , "src" : "/sda/5937/TOC-Subject-Sample-2021-Geography.jpg"})
Abstract
In the past decade, the number of refugees and internally displaced people (IDP) has doubled. This prompted the construction of more refugee camps and the proliferation of existing camps with diverse structural morphologies. Satellite imagery and machine learning (ML) are increasingly utilized to map these camps. However, there exists no standardized inventory that systemizes the built-up structures of these camps. In this study, we conceptualize the settlement morphology of refugee and IDP camps from satellite images and create a structure catalogue. Using visual image interpretation (VII) of very-high-resolution and multitemporal imagery, we compile a global database of settlement structures from 285 camps across 1,053 observations. This catalogue is subsequently used to synthesize patterns in camp structures and temporal dynamics. The results show stark variations in settlement structures across camps. Despite some similar regional patterns, stark differences in morphologies are a testament to the global heterogeneous landscape of refugee and IDP camp structures. These findings highlight the importance of considering morphological differences in image analyses across camps in future designs of ML-based automated detection and monitoring efforts. Therein, the Structure Catalogue serves as an important foundation for future earth observation for humanitarian applications.
Notes
Acknowledgements
The authors thank Ricardo Göhler and Ebru Koç for their assistance. The authors acknowledge the data provided by the OpenStreetMap project and its contributors under the terms of the Open Data Commons Open Database License (ODbL).
Disclosure statement
No potential conflict of interest was reported by the author(s). The funders had no role in the design of the study; in the collection, analyses, or interpretation of the data; in the writing of the manuscript, or the decision to publish the results.
Data and codes availability statement
The data and code that support the findings of this study are available for further research at https://doi.org/10.6084/m9.figshare.c.6207238. The collection includes
the Structure Catalogue featuring the following attributes: an object ID, camp name, date of observation (accurate to months), the collected structure parameters AREA, DIST, DENS, ORI, HOM, STR, and PATH per observation in numeric values 1 = low/small, 2 = medium, 3 = high/large, a rough description of the prevalent (most common) building materials (BUILD_MATERIAL), the aggregated compactness and arrangement measures as well as geographic coordinates (geogr. WGS 84, EPSG 4326),
R code supporting the methodology of this study,
supplementary geographic data required for running the code.
Notes
Additional information
Funding
Notes on contributors
Matthias Weigand
Matthias Weigand studied Geography (BSc) with a focus on remote sensing at the Julius-Maximilians-Universität Würzburg, Germany (JMU) and Geoinformatics (MSc) at the University of Augsburg, Germany. Currently, he is a research assistant and PhD student at the Earth Observation Center (EOC) of the German Aerospace Center (DLR). His research focuses on combining large scale geographic data, machine learning, and geostatistics for analysing and monitoring the human habitat.
Matthias Weigand developed the methodology of the study, wrote software for the spatial and statistical analyses, drafted and edited the article, contributed graphical designs and acts as corresponding author.
Simon Worbis
Simon Worbis studied Applied Geodesy and Geoinformatics (BEng) at the Munich University of Applied Sciences where he is currently studying for a master’s degree in Geomatics (MEng). His research interests focus on remote sensing, machine learning techniques and geostatistics.
Simon Worbis contributed by collecting the data, developing software for spatial and statistical analyses, and reviewing the manuscript.
Marta Sapena
Marta Sapena, engineer in Geodesy and Cartography completed her Ph.D. in Geomatics Engineering at the Polytechnic University of Valencia, Spain. Currently, she is a postdoctoral researcher at the Earth Observation Center (EOC) of the German Aerospace Center (DLR). Her research interests include the development of methodologies that allow relating the spatial structure of urban areas and their evolution to geographic, demographic, and socio-economic variables, assessing exposure and vulnerability to natural hazards, and mapping and monitoring urbanisation through remote sensing.
Marta Sapena contributed to the study through consulting formal analyses and critical review of the manuscript.
Hannes Taubenböck
Hannes Taubenböck is affiliated with the German Aerospace Center (DLR) and the Julius-Maximilians-Universität Würzburg (JMU). At DLR he is heading the department “Georisks and Civil Security” within the German Remote Sensing Data Center (DFD) and at JMU he is professor holding the chair “Global Urbanization and Remote Sensing”.
Hannes Taubenböck contributed the research idea, the conceptual approach, the acquisition of funding, the supervision of the formal analysis, and reviewing of the manuscript.