The drivers of human displacement are becoming more and more complex, ranging from conflict and persecution to the increasingly pertinent variables of heightened mobility and social media influences. Of rapidly but appropriately escalating concern is the impact of climate change. While the intensity and severity of climate-induced disasters and climate-related migration will be unevenly distributed across space and time, the World Bank estimates that approximately 140 million people will be displaced globally due to climate-related reasons by 2050. The effects of climate change are expected to be particularly pronounced in Africa, where rising temperatures, unpredictable anomalous rainfall and high vulnerability to extreme natural hazards will continue to exacerbate conflict and harm local and regional human, economic, and environmental security.
In the East and Horn of Africa (EHoA) in particular, the dependence on rain-fed agriculture and pastoralism means that livelihoods and food security are inextricably linked and affected by long-term or sudden environmental changes and natural hazards. The extreme natural hazards that have struck EHoA in recent years have caused widespread hunger, displacement, loss of critical infrastructure and livelihoods, and death
In an effort to understand the complex variables that influence migration, the International Organization for Migration (IOM) developed the Displacement Tracking Matrix (DTM) to track and gather information about populations on the move. The Flow Monitoring Registry (FMR) captures a wealth of data about the migratory routes, the demographics and nationality of migrants, reasons for migration, modes of transportation used to facilitate movement, and vulnerabilities experienced by these populations. While the descriptive data provides a wealth of information, more can be done to analyze the complexities of and interactions between migration, conflict, environmental changes, and climate-related events. Climate projections further suggest that environmental changes will likely further lead to decreased water availability, lowered agricultural productivity, and increased disease transmission in the region, producing complex ramifications regarding local and regional conflicts, economics, politics, and migration.
The porous borders in EHoA have contributed to some of the highest volumes of cross border movement in the world. In 2020 alone, EHoA hosted 6.5 million internally displaced persons (IDPs) and 3.5 million refugees and asylum seekers.6 In the same year, the Horn of Africa experienced unusually high levels of precipitation leading to disastrous floods and landslides and creating ideal conditions for an detrimental locust plague towards the end of 2019 that devastated crops and disrupted livelihoods. The extreme precipitation experienced across much of the Horn in 2019 was preceded by anomalous rainfall the previous year. 2018 was particularly hot and dry in the Horn of Africa, with positive temperature anomalies of around 2°C and below-average precipitation contributing to drought-like conditions in Somalia, Eritrea, and Djibouti while Kenya and Sudan experienced above-average precipitation.8 The drought-like conditions in Somalia, Eritrea, and Djibouti contributed to widespread food insecurity that affected approximately 12 million people. These extreme weather conditions are increasingly exacerbating the already complex and interconnected factors driving migration in the Horn of Africa, and are only expected to escalate in the future.
For this study, the IOM RDH in Nairobi partnered with the Humanitarian Geoanalytics Program at the Harvard Humanitarian Initiative to leverage spatial analytics to investigate migration flows in the East and Horn of Africa and Yemen. Geospatial analytics hold tremendous potential to introduce new ways of thinking, build research capacity, study impacts, and facilitate costeffective programming. The adoption of geospatial methods into research oriented towards populations on the move, gives us the capacity to accurately characterize the spatial heterogeneity of migrating populations. Furthermore, by incorporating environmental variables into this spatial analysis, we begin to reveal relationships previously undiscovered that could contribute to a richer understanding regarding migration in the region.
This guide outlines the tools and techniques to establish a foundation for visual analysis and discusses how these techniques can assist in identifying notable landscape features pertaining to agriculture, settlements, water catchment, and livestock in northern Somalia. To the knowledge of the Signal Program analysts, there is no systematic open-source remote sensing documentation of frequently occurring natural and man-made features in Somalia. This guide helps users to identify and analyze these features, particularly humanitarian practitioners supporting activities in the Horn of Africa. This project, titled “Children on the Move: Using Satellite Data Analysis in Conflict/Famine-Affected Areas,” was carried out in collaboration with UNICEF, the GovLab at NYU, and the Signal Program on Human Security and Technology at Harvard Humanitarian Initiative.
This study explores how pastoralists respond to changing environments in Somaliland . An agent-based model is used to simulate the movement of nomadic pastoralists based on typologically diverse, historical data of environmental, interpersonal, and transactional variables in Somaliland and Puntland between 2008 and 2018. Through subsequent application of spatial analysis such as choropleth maps, kernel density mapping, and standard deviational ellipses, we characterize the resultant pastoralist population distribution in response to these variables.
This study is the first geospatial-based history of a conflict created primarily through a fusion of remote sensing and previously public event data. The researchers of the Signal Program spent many months cross-referencing and analyzing over 40,000 square kilometers of archival satellite imagery of Sudan with more than 2,000 published reports of incidents occurring between January 2011 and mid-2012.
Key findings of the study include evidence of the apparent intentional destruction of more than 2,000 civilian dwellings and other structures; the intentional targeting and destruction of four humanitarian facilities; identification of specific armed actors, units, and chains-of-command allegedly involved in specific attacks in Sudan; and evidence of the mass displacement of civilian populations.
This article documents the development and initial use case of the GRID (Ground Reporting through Imagery Delivery) methodology by the Harvard Humanitarian Initiative (HHI). GRID was created to support corroboration of witness testimony of mass atrocity related-events using satellite imagery analysis. A repeating analytic limitation of employing imagery for this purpose is that differences in the geographic knowledge of a witness and an imagery analyst can limit or impede corroboration.
The aim of this article is to highlight potential methods applicable to a standard forensic approach for the analysis of high-resolution satellite imagery that may contain evidence of alleged mass atrocities. The primary method employed is the retrospective analysis of a case study involving the use of high-resolution satellite imagery analysis to document alleged mass atrocities. The case study utilized herein is the Satellite Sentinel Project’s reporting on the May 2011 sacking of Abyei Town by Government of Sudan-aligned armed actors. In the brief case study, categories of objects, patterns of activities, and types of alleged mass atrocity events are applied the Abyei Town incident.
At the evolving frontier of modern humanitarianism, non-governmental organizations are using satellite technology to monitor mass atrocities. As a documentation tool, satellites have the potential to collect important real-time evidence for alleged war crimes and crimes against humanity. However, the field remains experimental and ill-defined, while useful court evidence cannot be produced without a standard methodology and code of ethics. In this paper, members of the groundbreaking Satellite Sentinel Project review the historical development of satellite documentation and some of its landmark projects, and propose necessary measures to advance the field forward.
The Georgetown Journal of International Affairs published an article authored by Signal Program staff in which they detail the technology, perceived impact and lessons learned from running operations for the Satellite Sentinel Project. This inside assessment of the Satellite Sentinel Project has been offered open source by the journal in order to inform humanitarian practitioners, scholars and the public.
Remote sensing can provide unique, sometimes otherwise unavailable, information about human rights violations occurring in non-permissive environments, over large geographic areas, and across long and multiple timeframes. The evidentiary potential of RS analysis currently appears not to be fully exploited by international criminal justice mechanisms. The purpose of this paper is (A) to illustrate the nature of RS analysis and its evidentiary potential and limitations, (B) to identify the key, repeating factors across regional and cultural contexts and types of crimes that influence its limited use in court, and (C) to explore steps and strategies for overcoming the challenges.
During armed conflict in East and Central Africa civilian dwellings are intentionally targeted and razed. These traditional civilian dwellings are known as tukuls which are primarily mud and thatch huts.
The intentional destruction of these dwellings, given their prevalence in these regions, is often one of the only available indicators of the intentional targeting of civilians observable in satellite imagery.
This field has lacked accepted methodologies for performing this type of analysis. This guide is the first to focus on tukuls because they are a uniquely valuable metric for both documenting attacks on civilians during armed conflicts and assessing potential mass displacement that can result from these incidents.
This guide is the second in a series of Satellite Imagery Interpretation Guides. Future satellite imagery interpretation guides from the Signal Program may focus on other, related phenomena and structures present in similar operational contexts.
Satellite Imagery Interpretation Guide: Displaced Population Camps is intended to help address the absence of public and standardized training resources for those seeking to use high resolution satellite imagery in support of refugee/IDP assistance operations. Students, general audiences, and volunteers studying and analyzing satellite imagery of displaced population camps may find this training resource beneficial.
The guide provides case studies of displaced population camps in East Africa and the Middle East. Dimensions, colors, shapes, and, when possible, unique identifying features of objects, including civilian shelters and humanitarian agency infrastructure, visible in high resolution imagery of the camps are identified. Objects are organized according to the United Nations Office for the Coordination of Humanitarian Affairs humanitarian cluster system and three other categories unique to this guide. Imagery provided by Google's Skybox Imaging for the creation of this guide can be explored online by following the directions included inside the report.
At present, accepted methodologies for wind disaster damage assessments rely almost exclusively on responders having ground access to the affected area to document damage to housing structures. This approach can prove both time consuming and inefficient, and does not support the use of drones and satellites.
Geospatially-based damage assessments offer potential improvements to this process in terms of providing responding agencies with previously unavailable information about hard to reach, often non-permissive environments, at a scale and speed not possible through ground-based counts of damaged structures.
This guide provides the first standard method for conducting these types of damage assessments through the analysis of drone and satellite imagery. The “BAR Methodology” has been developed by the Signal Program on Human Security and Technology at HHI to address this critical gap in this evolving area humanitarian practice.
Building data responsibility into humanitarian action is the first UN Office for Coordination of Humanitarian Affairs think brief to explore what constitutes the responsible use of data in humanitarian response. It was co written by the Signal Program, NYU Gov Lab and the Center for Innovation at Leiden University.
This paper identifies the critical issues humanitarians face as they strive to responsibly use data in operations. It also proposes an initial framework for data responsibility.