Introduction: This paper describes a new technology called I4F (Instant Foam Fighting Forest Fire - EU Horizon 2020) that makes the process of aerial firefighting more effective. Aerial firefighting uses mostly water or long term retardant, sometimes short term retardants (foam) suppressing forest fires however I4F technology uses instant foam which capability is stated between traditional foam and long term retardants.
Methods: I4F technology based on previously published research results called R-20F and R-10A methods Based on these methods instant foam technology can suppress fires in such dimensions where others like water or short term retardants has objective limits: aerial firefighting can suppress fire with water up to 3,400 kW/m fire intensity however I4F technology can reach the limit of 20,000 kW/m intensity.
Results: I4F technology consists of different elements like ground refilling station, on board tank with fittings and special nozzles and the special added class A foam. Ground refilling station provides the preparing of instant foam and the quick refilling of the on board tank before taking off. The on board tank is a compartment of the pressurized instant foam. Special nozzles can provide a very straight, invariant and homogeneous footprint on the surface covering the trees with thick foam blanket. The traditional used class A foam agent get an special add which keeps foam structure longer because draining time is reduces more than up to 60 minutes. Longer foam stability gives pilot more flexibility to optimize the release distance of foam jet from the fire front.
Project made both ground and aerial tests with different configurations of valve openings, flight speed and release altitudes. Results show footprint of released foam is very straight, invariant and homogeneous reducing drastically the wasted part of carried extinguishing material. I4F technology can be optimized to different platforms both on rotary and fix wing planes.

Firefighting has become increasingly difficult and costly due to climate change. In response, new tools, including online platforms, are emerging to help prevent and promptly combat ever more destructive wildfires. While those initiatives only provide maps of fire risk based on environmental and climatic conditions, which in general have a medium predictive capability, fire propagation models, although successful in predicting fire behavior and spread, particularly at local scale, can become impractical during emergency situations, since they require lots of spatial data that must be obtained, processed and input by the user. To overcome these limitations, we have developed a fire-spread prediction system for the Brazilian Cerrado, the biome most affected by wildfires in South America. The system, named as FISC-Cerrado, automatically uploads hot pixels and satellite data to calculate maps of fuels loads, vegetation moisture, and post-probability of burning for simulating fire spread thrice a day for the entire Cerrado at 25 ha and for nine conservation units at 0.09 ha spatial resolution. Unlike the requirements to operate fire spread models, the user-friendly interface of FISC-Cerrado, alongside the automatization of the entire chain of tasks, allows its use by practitioners who do not have technical skills, such as GIS knowledge. Model results together with ancillary data, e.g., historical burned areas and annual CO2 emissions from fires, are available on an interactive web-platform (https://csr.ufmg.br/fipcerrado/en/), which is being used for daily operations by the fire brigades of the selected conservations units.

In the context of the rural fires of 2017, it was demonstrated the extreme importance of having the capacity for rapid analysis of the ongoing situation, anticipating fire behavior, and identifying suppression opportunities. These capacities were especially relevant considering the size and geographic dispersion of the fires, their simultaneity, and the involvement of a large number of resources from different entities.
In 2018, the National Emergency and Civil Protection Authority (ANEPC) implemented a decision support cell (NAD-AIR) for the analysis of rural fires, operated by fire analysts of the Special Civil Protection Force (FEPC). It was created with the objective of assisting the command structure, at the national, regional, or district level, and at the incident level, in the collection, analysis, and interpretation of important data for the prediction of wildfire behavior and making tactical proposals. More than a simple organic and operational structure, this unit incorporates tools, methodologies, processes, and knowledge with the aim of continuously monitoring and analyzing the most important wildfires, based on a logic structured in three major areas: 1. Supporting the operational decision process in a preventive scope, with a strategic analysis on the daily fire risk (before an incident); 2) Analysis of each significant ongoing wildfire; 3) Collection of the most important data to perform post-fire analysis.
This presentation aims to provide insight into the NAD-AIR concept, especially the tools, processes, and work developed in the last 5 years.

Objectives
The aim of this research is to validate previously discovered decision factors as well as identify factors that have emerged since the US federal wildfire policy was updated in 2009.
Methods
Data was gathered by selecting a representative sample of fires across the US where varying strategies were implemented. Researchers interviewed decision makers while the fire was still actively burning in order to gain time-of-fire decision factors without the presence of hindsight bias. Transcripts from interviews were coded in qualitative data analysis software to elucidate decision factors and themes.
Key results
We validated the presence of decision factors which had been identified prior to the 2009 policy update as well as 69 emergent decision factors. To contextualize decision factors within the decision-making process, we offer an updated Wildfire Decision Framework that has value for wildfire social science researchers.
Conclusions
Data shows that wildfire strategies are fluid and not easily discernible from outside appearances, and attempting to bin available strategies into strict categories does not reflect how contemporary wildfires are being managed. Instead, we suggest that researchers and managers alike should consider adopt messaging that reflects a polystrategic’ approach when managing a wildfire with any strategy other than full suppression.

This research provides insight into the complex decision-making process fire managers engage in during wildfire events. Managers may gain a better understanding of the decision environment under which they are operating and use the factors and framework as a tool to verify that needed considerations are being made.

Objectives: Since 2016, JAXA and NASA have partnered to investigate the safe and efficient integration of unmanned aircraft systems (UAS) in disaster response operations. The current research focuses on enabling the safe integration of UAS and helicopters in wildfire response operations.

Methods: A flight test using JAXA’s experimental helicopter was conducted in August 2022 to validate the use of mission planning and traffic management technologies, including onboard pilot situation awareness support, to coordinate concurrent manned aircraft and UAS operations. A scenario was developed and performed that simulated a wildfire response operation including a helicopter conducting water drops in the presence of a UAS operating area defined by a bounding box. Post-flight debrief discussions were held with the pilots to better understand their needs and assess the effectiveness of supporting situation awareness tools.

Results: The advantages of the developed technology were demonstrated. It was confirmed that real-time awareness of the UAS operation airspace helped the helicopter pilot plan and execute a safe mission and minimize the flight time loss due to the potential interference with the UAS. Post-flight interviews with the pilots indicated no sufficient increase in the pilots’ workload and provided ideas for future technology development.

Conclusions: Given the appropriate situation awareness tools, helicopter pilots can carry out wildfire missions in the vicinity of UAS without any significant impact on pilots’ workload, mission safety, and efficiency. Further research is necessary to establish the most useful situation awareness and alert functionality methods.

Introduction: Aerial firefighting is effective however very expensive solution to suppress forest fires. Drone application as a most developing branch of the aviation industry can be a complement, or perhaps even a competitive solution with the traditional aerial firefighting. Based on the input data drone swarm technology can be not just an effective but also an efficient solution suppressing forest fires.
Methods: In this study author used both practical and theoretical approach to investigate the possibility of drone usage delivering suppressant to fire front. Firstly, the required width of wetting strip and the required amount of water per unique area were investigated; practical experience shows that based on the flame length first responders can estimate both the effective width of the fire break and the amount of water required per a unique area. As a second part of the paper, the transport capability of a drone was investigated during its life cycle that is specially optimized for firefighting.
Results: In the example author took a 100 kg transport capacity that is easy to transfer to other drone design; in case of 0.3 MWm-1 fire intensity 100 kg water is enough to make 100 m long fire break, in case of 3.4 MWm-1 fire intensity 100 kg water enough to create only 2.5 m fire break. Even if this latest results can be seen a bit short experts have to take into account the swarm technology. In 10 km distance 30 drones can built a 5 m long fire brake per a minute that means 300 m per hour. This result is no worse than what large or very large air tankers can built averagely in this fire intensity. Expecting the technological development in the near future the length of the fire break will raise drastically meaning that drone swarm technology will be not a complement but a competitive solution to the traditional aerial firefighting.

Portugal is recurrently affected by severe wildfires, and some of the most severe episodes are wind driven. We describe a cellular automata (CA) model designed to simulate wind-driven wildfires. The model considers three factors (wind, terrain slope and vegetation type) when evaluating the likelihood of fire propagating from a cell to a neighboring one and incorporates a wind rule to simulate spotting.
We present results obtained when the model was applied to simulate two wind-driven wildfires that took place at Pataias-Burinhosa and Quiaios on October 15, 2017. These wildfires resulted from the combination of very strong winds steered by the passage of hurricane Ophelia, very dry vegetation because of a prolonged drought affecting the country, and very low atmospheric relative humidity.
Elevation profiles were obtained from the SRTM digital model and land cover data were obtained from CORINE maps. Hourly winds were obtained from forecast by the regional model WRF and the WindNinja software was used to account for wind interaction with topography.
The model was calibrated by comparing the simulated burned area against shapefile maps provided by EFFIS in the case of the Pataias-Burinhosa event, and against burned areas as identified by Sentinel-2, in the case of Quiaios.
Maps of probability of burning were obtained by performing an ensemble of 100 simulations. In both simulations, the patterns of probabilities present a marked decrease out of the limits of the observed scar, indicating that the model may help deciding about the locations where to allocate resources for firefighting.