Wildfires involve catastrophic consequences which significantly affect properties, infrastructures, and the environment. The use of remote sensing in fire management provides accurate spatial information which is necessary to improve current fire management decisions. In fact, Remote Sensing data provide the necessary tools for large-scale forest management which would be impossible to obtain by other methods. Thus, proper management of forest resources for forest fire prevention should be approached using Remote Sensing data. These technologies allow for generating current predictions about wildland fires, measuring, or monitoring fires, or can be used to fuel characterization which helps to represent and model fire risk and its effects. For example, fuel moisture maps can be used to predict wildfire danger by meteorological drought.
Nowadays, forest fires are of great importance to society because of the social and economic impacts they entail. Although the area burned on a global scale has decreased over the last decades, the hectares burned increased due to extreme fires. Among the reasons are the changes in social-ecological systems as well as in the climate, therefore, these two aspects of global changes are carriers for uncertain consequences. This special issue" Remote Sensing for fire management" aims to cover recent developments in Fire and Forest Management. Submitted papers should clearly show novel contributions and innovative applications of how remote sensing can support any of the following stages pre-fire, active fire, and post-fire periods. Furthermore, papers also can approach the fuel structure and the vegetation conditions as well as the presence of objects (houses, infrastructures…) that may be impacted by wildfires to determine the riskiest fire areas.
Remote sensing is an essential part of fire management in all the lifecycle stages of wildfires. Therefore, this Special Issue calls for papers concerning recent advances in the use of remote sensing approaches to analyze the main factors involved in a wildfire. The proposed topic should include but not be limited to:
Regarding the Pre-fire: analysis of the main parameters involved in a fire, fuel structure and composition, fuel moisture, and human infrastructure.
During the fire: monitoring of active fires, suppression management tasks, digital twins of active fire environment.
Post-fire: fire impacts, change in the vegetation stage, and the assessment of fire damage.
Therefore, areas of research may include (but are not limited to) the following:
· Active fire
· Fuel moisture
· Burned areas
· Fire regimen
· Fuel structure and composition
· Fire behavior
Keywords:
Lidar, Multispectral images, Fuels management, Machine and Deep LEarning, Fire modelling
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
Wildfires involve catastrophic consequences which significantly affect properties, infrastructures, and the environment. The use of remote sensing in fire management provides accurate spatial information which is necessary to improve current fire management decisions. In fact, Remote Sensing data provide the necessary tools for large-scale forest management which would be impossible to obtain by other methods. Thus, proper management of forest resources for forest fire prevention should be approached using Remote Sensing data. These technologies allow for generating current predictions about wildland fires, measuring, or monitoring fires, or can be used to fuel characterization which helps to represent and model fire risk and its effects. For example, fuel moisture maps can be used to predict wildfire danger by meteorological drought.
Nowadays, forest fires are of great importance to society because of the social and economic impacts they entail. Although the area burned on a global scale has decreased over the last decades, the hectares burned increased due to extreme fires. Among the reasons are the changes in social-ecological systems as well as in the climate, therefore, these two aspects of global changes are carriers for uncertain consequences. This special issue" Remote Sensing for fire management" aims to cover recent developments in Fire and Forest Management. Submitted papers should clearly show novel contributions and innovative applications of how remote sensing can support any of the following stages pre-fire, active fire, and post-fire periods. Furthermore, papers also can approach the fuel structure and the vegetation conditions as well as the presence of objects (houses, infrastructures…) that may be impacted by wildfires to determine the riskiest fire areas.
Remote sensing is an essential part of fire management in all the lifecycle stages of wildfires. Therefore, this Special Issue calls for papers concerning recent advances in the use of remote sensing approaches to analyze the main factors involved in a wildfire. The proposed topic should include but not be limited to:
Regarding the Pre-fire: analysis of the main parameters involved in a fire, fuel structure and composition, fuel moisture, and human infrastructure.
During the fire: monitoring of active fires, suppression management tasks, digital twins of active fire environment.
Post-fire: fire impacts, change in the vegetation stage, and the assessment of fire damage.
Therefore, areas of research may include (but are not limited to) the following:
· Active fire
· Fuel moisture
· Burned areas
· Fire regimen
· Fuel structure and composition
· Fire behavior
Keywords:
Lidar, Multispectral images, Fuels management, Machine and Deep LEarning, Fire modelling
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.