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Turning Data into Action: Leveraging Unmanned Aerial Systems (UAS) for Flood-Related Disaster Management in Sub-Saharan Africa

Lal, Amrita LU (2025) In IIIEE Master Thesis IMEM02 20251
The International Institute for Industrial Environmental Economics
Abstract
Floods are among the most frequent and destructive natural disasters in Sub-Saharan Africa, exacerbated by climate change, rapid urbanisation, and inadequate infrastructure. In this context, drones, or Unmanned Aerial Systems (UAS), are increasingly recognised for their potential to enhance disaster management. Yet, adoption across the region remains fragmented, inconsistently integrated into workflows, and poorly documented. This thesis examines how drones have been adopted for flood disaster management between 2014 and 2024 in six countries, Kenya, Nigeria, Senegal, South Africa, Ghana, and Mozambique, by focusing on non-state actors and their stakeholders. The study employs a qualitative design grounded in Rogers’ Diffusion of... (More)
Floods are among the most frequent and destructive natural disasters in Sub-Saharan Africa, exacerbated by climate change, rapid urbanisation, and inadequate infrastructure. In this context, drones, or Unmanned Aerial Systems (UAS), are increasingly recognised for their potential to enhance disaster management. Yet, adoption across the region remains fragmented, inconsistently integrated into workflows, and poorly documented. This thesis examines how drones have been adopted for flood disaster management between 2014 and 2024 in six countries, Kenya, Nigeria, Senegal, South Africa, Ghana, and Mozambique, by focusing on non-state actors and their stakeholders. The study employs a qualitative design grounded in Rogers’ Diffusion of Innovation (DOI) theory and the Technology-Organisation-Environment (TOE) framework. Fifteen semi-structured interviews with practitioners from academia, NGOs, the private sector, and one government stakeholder were conducted, complemented by secondary sources such as reports, blogs, and grey literature. Findings show that drone applications are most prominent in the response phase, where real-time, high-resolution data supports rapid impact assessment, damage mapping, and logistical planning. Use in mitigation, preparedness, and recovery remains largely confined to academic and pilot projects. Adoption patterns vary: NGOs with established reputations leverage influence to bypass regulatory and funding barriers, while private sector and academic actors face significant obstacles. Real-time and accurate data were universally valued, but cost savings and ease of use were contested. Hardware preferences centered on multirotor drones, while software choices reflected sectoral priorities: NGOs and firms favoured commercial platforms, while academics used open-source tools. Across all contexts, community perception and engagement were critical for building trust and enabling adoption. The study concludes that while drones and local practitioners have proven effective, sustained integration depends on consistent institutional frameworks, regulatory clarity, and collaborative knowledge-sharing. Without these, adoption will remain fragmented and ad hoc, limiting drones’ transformative potential for flood resilience in Sub-Saharan Africa. (Less)
Please use this url to cite or link to this publication:
author
Lal, Amrita LU
supervisor
organization
course
IMEM02 20251
year
type
H2 - Master's Degree (Two Years)
subject
keywords
drones, disaster management, stakeholders, practitioners, Sub-Saharan Africa
publication/series
IIIEE Master Thesis
report number
2025:33
ISSN
1401-9191
language
English
id
9211270
date added to LUP
2025-11-13 12:55:05
date last changed
2025-11-13 12:55:05
@misc{9211270,
  abstract     = {{Floods are among the most frequent and destructive natural disasters in Sub-Saharan Africa, exacerbated by climate change, rapid urbanisation, and inadequate infrastructure. In this context, drones, or Unmanned Aerial Systems (UAS), are increasingly recognised for their potential to enhance disaster management. Yet, adoption across the region remains fragmented, inconsistently integrated into workflows, and poorly documented. This thesis examines how drones have been adopted for flood disaster management between 2014 and 2024 in six countries, Kenya, Nigeria, Senegal, South Africa, Ghana, and Mozambique, by focusing on non-state actors and their stakeholders. The study employs a qualitative design grounded in Rogers’ Diffusion of Innovation (DOI) theory and the Technology-Organisation-Environment (TOE) framework. Fifteen semi-structured interviews with practitioners from academia, NGOs, the private sector, and one government stakeholder were conducted, complemented by secondary sources such as reports, blogs, and grey literature. Findings show that drone applications are most prominent in the response phase, where real-time, high-resolution data supports rapid impact assessment, damage mapping, and logistical planning. Use in mitigation, preparedness, and recovery remains largely confined to academic and pilot projects. Adoption patterns vary: NGOs with established reputations leverage influence to bypass regulatory and funding barriers, while private sector and academic actors face significant obstacles. Real-time and accurate data were universally valued, but cost savings and ease of use were contested. Hardware preferences centered on multirotor drones, while software choices reflected sectoral priorities: NGOs and firms favoured commercial platforms, while academics used open-source tools. Across all contexts, community perception and engagement were critical for building trust and enabling adoption. The study concludes that while drones and local practitioners have proven effective, sustained integration depends on consistent institutional frameworks, regulatory clarity, and collaborative knowledge-sharing. Without these, adoption will remain fragmented and ad hoc, limiting drones’ transformative potential for flood resilience in Sub-Saharan Africa.}},
  author       = {{Lal, Amrita}},
  issn         = {{1401-9191}},
  language     = {{eng}},
  note         = {{Student Paper}},
  series       = {{IIIEE Master Thesis}},
  title        = {{Turning Data into Action: Leveraging Unmanned Aerial Systems (UAS) for Flood-Related Disaster Management in Sub-Saharan Africa}},
  year         = {{2025}},
}