Leveraging Drone GPS Data for Disaster Recovery: A Forensic Perspective on Flight Path Reconstruction

This post is an academic reflection on the paper “Drone GPS Data Analysis for Flight Path Reconstruction: A Study on DJI, Parrot & Yuneec Make Drones” by Ravin Kumar and Animesh Kumar Agrawal, exploring its relevance in the context of disaster recovery and emergency response. In recent years, the increasing integration of drones into disaster response frameworks has reshaped the way agencies manage search and rescue, damage assessment,

and emergency logistics. The capacity of drones to swiftly access hazardous or inaccessible areas, gather real-time imagery, and relay telemetry data has made them indispensable in both civilian and governmental response operations. However, their full potential is realized only when their flight data is systematically captured, analyzed, and interpreted.

Source: RemoteFlyer – How Drone GPS Navigation Works

The central aim of the study is to explore methodologies for extracting and analyzing GPS logs from three major drone families—DJI, Parrot, and Yuneec—and to reconstruct their flight paths using satellite-based visualization tools. Although originally positioned within a forensic context, this research has strong implications for disaster recovery operations where documenting aerial reconnaissance routes, assessing flight coverage areas, and correlating drone footage with geospatial data are vital for effective resource deployment and situational awareness.

The methodology involves accessing drone flight logs, which vary in format and complexity across different manufacturers. DJI drones, for instance, store encrypted .DAT files requiring decryption via tools like DatCon. Parrot drones provide plaintext .TXT or .JSON logs that, while accessible, are unstructured and difficult to process manually. To address this, the researchers developed the FlyLog Converter Tool, which automatically converts raw Parrot logs into organized .CSV format and extracts key metadata such as drone model, firmware version, flight date, and GPS coordinates. Yuneec drones, with their logs already in .CSV, present a more streamlined path to analysis.

The processed data is then mapped onto satellite imagery using Google Earth Pro, where waypoints, timestamps, altitude data, and trajectory are visually reconstructed. In disaster scenarios, such mapping enables response teams to:

• Review the spatial and temporal scope of drone coverage.

• Identify gaps in aerial reconnaissance.

• Assess terrain accessibility and infrastructure damage.

• Cross-reference GPS data with photographic or thermal imagery.

For disaster recovery personnel, this form of analysis is crucial. It ensures that every drone mission contributes meaningfully to situational awareness, mission auditing, and post-crisis evaluation. Moreover, by relying solely on open-source tools and real-world datasets provided by VTO Labs, the research presents a cost-effective and replicable workflow that can be adapted in both high-resource and resource-constrained environments.

In summary, while the original focus of the study is digital forensics, its relevance extends deeply into disaster response domains. Drone GPS data, when properly analyzed, can improve accountability, optimize operational coverage, and enhance decision-making in critical moments. As drone deployments continue to expand in emergency management, equipping teams with the ability to interpret flight data becomes not just beneficial—but essential.

The full article is accessible at:
https://doi.org/10.1016/j.fsidi.2021.301182