Search results

A search and rescue incident is ultimately all about the location of the missing person; hence, geotechnical tools are critical in providing assistance to search planners. One critical role of Geographic Information Systems (GISs) is to define the boundaries that define the search area. The literature mostly focuses on ring- and area-based methods but lacks a linear/network approach. The purpose of this paper is to present a novel network approach that will benefit search planners by saving time, requires less data layers and provides better results.

The paper compares two existing models (Ring Model, Travel Time Cost Surface Model (TTCSM)) against a new network model (Travel Time Network Model) by using a case study from a mountainous area in Austria. Newest data from the International Search and Rescue Incident Database are used for all three models. Advantages and disadvantages of each model are evaluated.

Network analyses offer a fruitful alternative to the Ring Model and the TTCSM for estimating search areas, especially for regions with comprehensive trail/road networks. Furthermore, only few basic data are needed for quick calculation.

The paper supports GIS network analyses for wildland search and rescue operations to raise the survival chances of missing persons due to optimizing search area estimation.

The paper demonstrates the value of the novel network approach, which requires fewer GIS layers and less time to generate a solution. Furthermore, the paper provides a comparison between all three potential models.

Mountaineering and related activities are increasingly becoming popular and are accompanied by an increase in medical incidents. Emergency operations in mountainous terrain are time-critical and often pose major logistical challenges for rescuers. Drones are expected to improve the operational performance of mountain rescuers. However, they are not yet widely used in mountain rescue missions. This paper examines the determinants that drive the behavioral intention of mountain rescuers to adopt drones in rescue missions.

This is a behavioral study that builds upon an extended model of the unified theory of acceptance and use of technology (UTAUT) and investigates the relationship between individual attitudes, perceptions, and intentions for drone adoption. Original survey data of 146 mountain rescuers were analyzed using moderated ordinary least squares (OLS) regression analysis.

Results indicate that the behavioral intention to use drones in mountain rescue missions is driven by the expected performance gains and facilitating conditions. Favorable supporting conditions and experience with drones further moderate the relationship between performance expectancy and behavioral intention. The effects for effort expectancy, social influence, and demonstrations were not significant.

Rescue organizations and stakeholders are recommended to consider the identified determinants in the implementation of drones in emergency logistics. Drone manufacturers targeting mountain rescue organizations are advised to focus on operational performance, provide sufficient support and training, and promote the gathering of practical experience.

A tailored-model that provides first empirical results on the relevance of personal and environmental factors for the acceptance of drones in emergency logistics is presented.