Remote Sensing of Environment

 

 

 

Advancing Drone-Based Remote Sensing for Disaster Management: A Critical Review of Trends, Biases, and Future Directions

In recent years, small aerial drones (weighing less than 25 kg) have emerged as transformative tools in the field of disaster management, particularly in remote sensing applications.

Their capacity for rapid deployment, high-resolution data acquisition, and cost-effectiveness has expanded the possibilities for monitoring, assessing, and responding to natural hazards. This technological evolution warrants a critical appraisal of how drone-based remote sensing is currently employed in disaster contexts and where strategic improvements could be made to optimize its utility.

A recent systematic review employing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology identified 635 scholarly articles relevant to drone applications in natural hazard-related disaster management. These studies were analyzed across multiple parameters including geographic distribution, drone hardware, type of disaster, data acquisition techniques, and the specific disaster management phases addressed. This comprehensive analysis offers valuable insights into prevailing research patterns, existing biases, and underexplored areas that hold significant potential for future research and operational integration.

The review revealed a pronounced bias in the types of hazards studied, with mass movement events (e.g., landslides and avalanches) accounting for approximately 38% of the research focus. While such hazards are indeed significant, they do not typically result in the highest human or economic losses compared to earthquakes, floods, and windstorms. This disparity highlights the need for a strategic reorientation of research priorities to encompass more frequent and devastating hazards that disproportionately affect vulnerable populations, particularly in low- and middle-income countries.

Spatially, the majority of studies have concentrated on small (<1 km²) and rural sites, with 76% and 79% of the literature respectively falling into these categories. Furthermore, 64% of studies were conducted in high-income countries or territories. This geographic skew underscores an urgent need to redirect research efforts toward urban environments in low, lower-middle, and upper-middle income nations, where the human impact of disasters tends to be more severe and complex. Drones offer a unique opportunity to bridge data gaps in such settings, where conventional data collection may be hindered by infrastructural, logistical, or economic constraints.

In terms of observational focus, 77% of studies relied on image-based data to monitor features from the natural environment, with relatively fewer efforts aimed at documenting built features in urban areas. However, for drones to be truly effective across all stages of disaster management—particularly in response and early recovery phases—it is imperative to develop methodologies that also capture the dynamics of urban infrastructure, population movements, and service accessibility. Response-focused research remains markedly underrepresented in the current literature, despite its critical importance during and immediately after disaster events.

Regarding the functional application of drone data, a majority of studies (54%) contributed to mitigation efforts, such as vulnerability assessments and risk modeling, while 23% supported environmental recovery. Although these applications are foundational to long-term resilience building, immediate response and short-term recovery operations demand equally robust remote sensing capabilities. The current gap suggests an opportunity for greater innovation in real-time data integration, situational awareness platforms, and inter-agency coordination using drone-derived inputs.

To address these limitations and realize the full potential of drone-based remote sensing in disaster contexts, several recommendations emerge. First, research should pivot toward high-impact hazard types—especially earthquakes, floods, and windstorms. Second, the geographic and socio-economic scope of drone studies should be broadened to include more diverse and vulnerable settings, particularly urban areas in the Global South. Third, expanding the focus to include response and recovery activities can significantly enhance the timeliness and effectiveness of disaster management operations. Finally, the establishment of standardized protocols and data formats is crucial for integrating drone data with international disaster response frameworks, enabling more coordinated and scalable interventions.

In conclusion, while drones have already demonstrated substantial value in disaster management, a recalibration of research agendas is necessary to ensure that their benefits are equitably distributed and fully realized. Through targeted innovation and inclusive practices, drone-based remote sensing can become a cornerstone of global disaster resilience.

 References

Tucker, C.J. (1979). Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 8(2), 127–150

Congalton, R.G. (1991). A review of assessing the accuracy of classifications of remotely sensed data. Remote Sensing of Environment, 37(1), 35–46

Holben, B.N., et al. (1998). AERONET—a federated instrument network and data archive for aerosol characterization. Remote Sensing of Environment, 66(1), 1–16