Fire Science Models, Remote Sensing, and Data
A section of Fire (ISSN 2571-6255).
Section Fire Science Models, Remote Sensing, and Data was the first section in MDPI’s journal Fire. The main aim of the Section Fire Science Models, Remote Sensing, and Data is to introduce and describe datasets, models, equipment, and analytical methods used in fire science. This Section publishes all the article types supported by Fire, with particular interest on Technical Notes, Data Descriptions, and articles describing data, models, and equipment, and analytical methods used in fire science.
This Section publishes Data Descriptors connected to prior and concurrent Fire submissions as well as for manuscripts published elsewhere. Data Descriptors can include papers that describe metadata, data collection, data archival and access, and data management. Data papers are also welcome that provide an analysis or description of fire science models, remote sensing, and data contained in repositories.
- Technical descriptions of fire science data, sensor, equipment, approaches, and models.
- Meta data descriptions.
- Big data including remote sensing and modeling.
- Fire science data collection and data acquisition.
- Fire science data processing and algorithm development.
- Fire science data management, integrity, archival, access, compression, and curation.
- Fire science data of physical quantities and standards.
- Fire science models, including conceptual descriptions, simulations, and validation.
- Datasets of physical quantities related to fire science such as thermal conductivity, diffusivity, bulk density, radiative fraction, fuel loadings, etc.
- Datasets related to the effects of fire on organisms such as mortality, growth, damage, etc.
- Datasets related to the impacts of fires on structural elements.
- Validation, sensitivity analyses, and verification of models or simulations.
- Calibration of sensors and equipment.
- Scaling from laboratory experiments to large-scale fires.
- Remote sensing and geographical information system data related to fire science
- Advances in scientific visualization of fire science data.
- Technical Notes describing the correct application of any fire science methods, equipment, and models
- Descriptions of fire science modeling and simulation runs.
Data Descriptors should follow the general layout in this template: Fire-data.
Topical Advisory Panel
Following special issues within this section are currently open for submissions:
- Understanding and Managing Extreme Wildland Fires (Deadline: 31 December 2023)
- The Use of Remote Sensing Technology for Forest Fire (Deadline: 6 January 2024)
- Cable and Electrical Fires (Deadline: 29 February 2024)
- Drone Applications Supporting Fire Management (Deadline: 31 March 2024)
- Understanding the Dissociation and Combustion of Gas Hydrates (Deadline: 31 March 2024)
- Dynamics of Wind-Fire Interaction: Fundamentals and Applications (Deadline: 8 May 2024)
- Machine Learning (ML) and Deep Learning (DL) Applications in Wildfire Science: Principles, Progress and Prospects (Deadline: 31 May 2024)
- Understanding, Monitoring, and Responses to Wildfires with New Sensors (Deadline: 25 September 2024)
Following topical collection within this section is currently open for submissions: