Forest fires represent a significant menace to both the ecological equilibrium of forests and the safety of human life and property. Upon ignition, fires frequently generate billowing smoke. The prompt identification and management of fire sources an...
Forest fires are a major natural calamity that inflict substantial harm on forest resources and the socio-economic landscape. The eastern region of China is particularly susceptible to frequent forest fires, characterized by high population density a...
Forest fires are important factors that influence and restrict the development of forest ecosystems. In this paper, forest-fire-risk prediction was studied based on random forest (RF) and backpropagation neural network (BPNN) algorithms. The Heihe ar...
Forest fires can lead to a decline in ecosystem functions, such as biodiversity, soil quality, and carbon cycling, causing economic losses and health threats to human societies. Therefore, it is imperative to map forest-fire risk to mitigate the like...
Forest fires are among the biggest threats to forest ecosystems and forest resources, and can lead to ecological disasters and social crises. Therefore, it is imperative to detect and extinguish forest fires in time to reduce their negative impacts....
The Random Domino Automaton—a stochastic cellular automaton forest-fire model—is formulated for the Bethe lattice geometry. The equations describing the stationary state of the system are derived using combinatorial analysis. The special...
This paper presents a novel system for automatic forest-fire measurement using cameras distributed at ground stations and mounted on Unmanned Aerial Systems (UAS). It can obtain geometrical measurements of forest fires in real-time such as the locati...
In the present research, the open-source WRF-SFIRE model has been used to carry out surface forest fire spread forecasting in the North Sikkim region of the Indian Himalayas. Global forecast system (GFS)-based hourly forecasted weather model data obt...
Forest fires are disasters that are common around the world. They pose an ongoing challenge in scientific and forest management. Predicting forest fires improves the levels of forest-fire prevention and risk avoidance. This study aimed to construct a...
The spread of contemporary artificial intelligence technologies, particularly machine learning, has significantly enhanced the capacity to predict asymmetrical natural disasters. Wildfires constitute a prominent example, as machine learning can be em...
The Mediterranean basin is an area particularly exposed to fire risk due to its climate and fire-prone vegetation. In recent decades, the frequency and intensity of wildfires increased, leading to negative effects on forests, such as a decrease in tr...
LoRaWAN is widely used for IoT environmental monitoring, but its lightweight security mechanisms leave the physical layer vulnerable to availability attacks such as jamming and battery-depletion. These risks are particularly critical in mission-criti...
In recent years, forest-fire monitoring methods represented by deep learning have been developed rapidly. The use of drone technology and optimization of existing models to improve forest-fire recognition accuracy and segmentation quality are of grea...
A prediction model was developed for the wildfire fuel load of Korean red pine (Pinus densiflora) stands with susceptibility to forest fire based on the forest-growth model. Furthermore, a time-series analysis was performed on the variation in forest...
The Himachal Pradesh district’s biggest natural disaster is the forest fire. Forest fire threat evaluation, model construction, and forest management using geographic information system techniques will be important in this proposed report. A simulati...
Forest fires are an important disturbance in forest ecosystems and can affect the structure and function of forests. These must be mitigated, to eliminate the associated harmful impacts on forests and the environment as well as to have a healthy and...
Forest fires are among the most critical natural tragedies threatening forest lands and resources. The accurate and early detection of forest fires is essential to reduce losses and improve firefighting. Conventional firefighting techniques, based on...
Forest-fire rates have increased in Southern European landscapes. These fires damage forest ecosystems and alter their development. During the last few decades, an increase in fast-growing and highly fuel-bearing plant species such as bush, Eucalyptu...
Estimating the damaged area after a forest fire is important for responding to this natural catastrophe. With the support of aerial remote sensing, typically with unmanned aerial vehicles (UAVs), the aerial imagery of forest-fire areas can be easily...
Forest fires are one of the world’s deadliest natural disasters. Early detection of forest fires can help minimize the damage to ecosystems and forest life. In this paper, we propose an improved fire detection method YOLOv5-IFFDM for YOLOv5. Fi...
Historical forest management practices in the southwestern US have left forests prone to high-severity, stand-replacement fires. Reducing the cost of forest-fire management and reintroducing fire to the landscape without negative impact depends on de...
Pinus koraiensis is one of the important tree species in Northeast China. Due to its high pine-needle-oil content and the density of human activities in its habitat, the forest-fire prevention situation is severe in the context of climate change. The...
Canopy base height (CBH) is a key parameter used in forest-fire modeling, particularly crown fires. However, estimating CBH is a challenging task, because normally, it is difficult to measure it in the field. This has led to the use of simple estimat...
Forest fire monitoring in remote sensing imagery has long relied on traditional perception models that primarily focus on detection or segmentation. However, such approaches fall short in understanding complex fire dynamics, including contextual reas...
Infrared small-target detection remains a critical challenge in military reconnaissance, environmental monitoring, forest-fire prevention, and search-and-rescue operations, owing to the targets’ extremely small size, sparse texture, low signal-...