Unmanned Aerial Systems for Wildland and Forest Fires

Wildfires represent an important natural risk causing economic losses, human death and important environmental damage. In recent years, we witness an increase in fire intensity and frequency. Research has been conducted towards the development of dedicated solutions for wildland and forest fire assistance and fighting. Systems were proposed for the remote detection and tracking of fires. These systems have shown improvements in the area of efficient data collection and fire characterization within small scale environments. However, wildfires cover large areas making some of the proposed ground-based systems unsuitable for optimal coverage. To tackle this limitation, Unmanned Aerial Systems (UAS) were proposed. UAS have proven to be useful due to their maneuverability, allowing for the implementation of remote sensing, allocation strategies and task planning. They can provide a low-cost alternative for the prevention, detection and real-time support of firefighting. In this paper we review previous work related to the use of UAS in wildfires. Onboard sensor instruments, fire perception algorithms and coordination strategies are considered. In addition, we present some of the recent frameworks proposing the use of both aerial vehicles and Unmanned Ground Vehicles (UV) for a more efficient wildland firefighting strategy at a larger scale.Comment: A recent published version of this paper is available at: https://doi.org/10.3390/drones501001

Using a Semi-autonomous Drone Swarm to Support Wildfire Management – A Concept of Operations Development Study

This paper provides insights into a human factors-oriented Concept of Operations (ConOps), which can be applied for future semi-autonomous drone swarms to support the management of wildfires. The results provide, firstly, an overview of the current practices to manage wildfires in Finland. Secondly, some of the current challenges and future visions about drone usage in a wildfire situation are presented. Third, a description of the key elements of the developed future ConOps for operating a drone swarm to support the combat of wildfires is given. The ConOps has been formulated based on qualitative research, which included a literature review, seven subject matter expert interviews and a workshop with 40 professionals in the domain. Many elements of this ConOps may also be applied to a variety of other swarm robotics operations than only wildfire management. Finally, as the development of the ConOps is still in its first stage, several further avenues for research and development are proposed

Unmanned Aerial Vehicle (UAV) for monitoring soil erosion in Morocco

This article presents an environmental remote sensing application using a UAV that is specifically aimed at reducing the data gap between field scale and satellite scale in soil erosion monitoring in Morocco. A fixed-wing aircraft type Sirius I (MAVinci, Germany) equipped with a digital system camera (Panasonic) is employed. UAV surveys are conducted over different study sites with varying extents and flying heights in order to provide both very high resolution site-specific data and lower-resolution overviews, thus fully exploiting the large potential of the chosen UAV for multi-scale mapping purposes. Depending on the scale and area coverage, two different approaches for georeferencing are used, based on high-precision GCPs or the UAV’s log file with exterior orientation values respectively. The photogrammetric image processing enables the creation of Digital Terrain Models (DTMs) and ortho-image mosaics with very high resolution on a sub-decimetre level. The created data products were used for quantifying gully and badland erosion in 2D and 3D as well as for the analysis of the surrounding areas and landscape development for larger extents

Smokey comes of age: unmanned aerial systems for fire management

During the past century, fire management has focused on techniques both to protect human communities from catastrophic wildfire and to maintain fire-dependent ecological systems. However, despite a large and increasing allocation of resources and personnel to achieve these goals, fire management objectives at regional to global scales are not being met. Current fire management techniques are clearly inadequate for the challenges faced by fire managers, and technological innovations are needed. Advances in unmanned aerial systems (UAS) technology provide opportunities for innovation in fire management and science. In many countries, fire management organizations are beginning to explore the potential of UAS for monitoring fires. We have taken the next step and developed a prototype that can precisely ignite fires as part of wildfire suppression tactics or prescribed fires (fire intentionally ignited within predetermined conditions to reduce hazardous fuels, improve habitat, or mitigate for large wildfires). We discuss the potential for these technologies to benefit fire management activities, while acknowledging the sizeable sociopolitical barriers that prevent their immediate broad application

Monitoring and Cordoning Wildfires with an Autonomous Swarm of Unmanned Aerial Vehicles

Unmanned aerial vehicles, or drones, are already an integral part of the equipment used by firefighters to monitor wildfires. They are, however, still typically used only as remotely operated, mobile sensing platforms under direct real-time control of a human pilot. Meanwhile, a substantial body of literature exists that emphasises the potential of autonomous drone swarms in various situational awareness missions, including in the context of environmental protection. In this paper, we present the results of a systematic investigation by means of numerical methods i.e., Monte Carlo simulation. We report our insights into the influence of key parameters such as fire propagation dynamics, surface area under observation and swarm size over the performance of an autonomous drone force operating without human supervision. We limit the use of drones to perform passive sensing operations with the goal to provide real-time situational awareness to the fire fighters on the ground. Therefore, the objective is defined as being able to locate, and then establish a continuous perimeter (cordon) around, a simulated fire event to provide live data feeds such as e.g., video or infra-red. Special emphasis was put on exclusively using simple, robust and realistically implementable distributed decision functions capable of supporting the self-organisation of the swarm in the pursuit of the collective goal. Our results confirm the presence of strong nonlinear effects in the interaction between the aforementioned parameters, which can be closely approximated using an empirical law. These findings could inform the mobilisation of adequate resources on a case-by-case basis, depending on known mission characteristics and acceptable odds (chances of success)