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An Exploratory Application of Low-Cost Drone Imagery and an Image Analysis Model to Evaluate Post-Disaster Recovery Progress for Planning Equitable Housing Recoveries Through Dynamic Funding Allocation
Journal article   Open access   Peer reviewed

An Exploratory Application of Low-Cost Drone Imagery and an Image Analysis Model to Evaluate Post-Disaster Recovery Progress for Planning Equitable Housing Recoveries Through Dynamic Funding Allocation

Daniel V. Perrucci, German C. Buitrago, Brady McKay, Kathleen Short and Christopher Santos
Urban science, v 10(4), 199
01 Apr 2026
url
https://doi.org/10.3390/urbansci10040199View
Published, Version of Record (VoR) Open CC BY V4.0

Abstract

Environmental Sciences Environmental Sciences & Ecology Life Sciences & Biomedicine Regional & Urban Planning Science & Technology Environmental Studies Geography Public Administration Social Sciences Urban Studies
After major disruptive events, particularly natural and human-made disasters, community leaders face the challenge of rebuilding societal infrastructure and managing the allocation of funds, which can affect the duration of recovery periods. Decision-makers must quickly determine how to allocate financial resources while minimizing population distress. Conventional methods of assessing damage and evaluating relief requirements fall short of meeting the urgent recovery needs after a disaster, potentially leading to negative effects on communities, such as involuntary relocation and neighborhood gentrification. The study evaluates current methods and technologies to propose a new approach that leverages low-cost consumer drones and modern image analysis techniques to support initial damage assessments and track recovery progress, thereby promoting the dynamic allocation of limited resources. Using low-cost drone imagery enables rapid, cost-effective data collection and dynamic analysis through iterative reviews during the disaster response and recovery phases that can adjust baseline disaster funding allocations. The study investigates the potential of temporary blue tarp roofs ("blue roofs") as a metric for recovery progress during the 2020 tornado in Middle Tennessee and conducts an R-squared and error analysis. The goal of this research is to evaluate an affordable and efficient data analysis method (e.g., modern image analysis; artificial intelligence; low-cost drones) that can improve post-disaster resource allocation and inform decision-making for governmental and planning officials.

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#11 Sustainable Cities and Communities

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Collaboration types
Domestic collaboration
Web of Science research areas
Environmental Sciences
Environmental Studies
Geography
Regional & Urban Planning
Urban Studies
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