The Portuguese Large Wildfire Spread Database (PT-FireSprd)

Benali, Akli; Guiomar, Nuno; Gonçalves, Hugo; Mota, Bernardo; Silva, Fábio; Fernandes, Paulo; Mota, Carlos Bolli; Penha, Alexandre; Santos, João A.; Pereira, José M. C.; Sá, Ana C. L.

doi:10.5194/essd-2022-475

Cited by 3 publications

(3 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The generic metadata are connected to L1 data through the fire name field and to L2 and L3 through the fire ID field. The data are freely available at https://doi.org/10.5281/zenodo.7495506 (Benali et al, 2022). We intend to update the database annually with wildfires from the current fire season and implement continuous improvements to the procedure.…”

Section: Data Availabilitymentioning

confidence: 99%

The Portuguese Large Wildfire Spread database (PT-FireSprd)

Benali,

Guiomar,

Gonçalves

et al. 2023

Earth Syst. Sci. Data

Self Cite

View full text Add to dashboard Cite

Abstract. Wildfire behaviour depends on complex interactions between fuels, topography, and weather over a wide range of scales, being important for fire research and management applications. To allow for significant progress towards better fire management, the operational and research communities require detailed open data on observed wildfire behaviour. Here, we present the Portuguese Large Wildfire Spread database (PT-FireSprd) that includes the reconstruction of the spread of 80 large wildfires that occurred in Portugal between 2015 and 2021. It includes a detailed set of fire behaviour descriptors, such as rate of spread (ROS), fire growth rate (FGR), and fire radiative energy (FRE). The wildfires were reconstructed by converging evidence from complementary data sources, such as satellite imagery and products, airborne and ground data collected by fire personnel, and official fire data and information in external reports. We then implemented a digraph-based algorithm to estimate the fire behaviour descriptors and combined it with the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI) fire radiative power estimates. A total of 1197 ROS and FGR estimates were calculated along with 609 FRE estimates. The extreme fires of 2017 were responsible for the maximum observed values of ROS (8900 m h−1) and FGR (4400 ha h−1). Combining both descriptors, we describe the fire behaviour distribution using six percentile intervals that can be easily communicated to both research and management communities. Analysis of the database showed that burned extent is mostly determined by FGR rather than by ROS. Finally, we explored a practical example to show how the PT-FireSprd database can be used to study the dynamics of individual wildfires and to build robust case studies for training and capacity building. The PT-FireSprd is the first open-access fire progression and behaviour database in Mediterranean Europe, dramatically expanding the extant information. Updating the PT-FireSprd database will require a continuous joint effort by researchers and fire personnel. PT-FireSprd data are publicly available through https://doi.org/10.5281/zenodo.7495506 (Benali et al., 2022) and have large potential to improve current knowledge on wildfire behaviour and to support better decision making.

show abstract

Section: Data Availabilitymentioning

confidence: 99%

The Portuguese Large Wildfire Spread database (PT-FireSprd)

Benali,

Guiomar,

Gonçalves

et al. 2023

Earth Syst. Sci. Data

Self Cite

View full text Add to dashboard Cite

show abstract

“…To quantify the apparent horizontal expansion of the fire perimeter, we define the fire spread rate, in kilometers per hour, in two ways, as either the maximum axis of expansion (fspread MAE ) or the area-weighted expansion (fspread AWE ), between two hourly time steps. Similar to the approach in Benali et al (2023), fspread MAE represents the partial fire spread along the longest axis of expansion, whereas fspread AWE represents the overall fire spread. While the fire perimeter and active-fire line describe the state of the fire at the end of the hour (t = 1, 2, 3. .…”

Section: Fire Spread Ratementioning

confidence: 99%

Systematically tracking the hourly progression of large wildfires using GOES satellite observations

Liu,

Randerson,

Chen

et al. 2023

Preprint

View full text Add to dashboard Cite

Abstract. In the western United States, prolonged drought, warming climate, and historical fuel build-up have contributed to larger and more intense wildfires, as well as longer fire seasons. As these costly wildfires become more common, new tools and methods are essential for improving our understanding of the evolution of fires and how extreme weather conditions, including heatwaves, windstorms, droughts, and varying levels of active fire suppression, influence fire spread. Here we develop the GOES-Observed Fire Event Representation (GOFER) algorithm to derive the hourly fire progression of large wildfires and create a dataset of hourly fire perimeters, active fire lines, and fire spread rates. Using GOES-East and GOES-West geostationary satellite detections of active fires, we test the GOFER algorithm on 28 large wildfires in California from 2019–2021. The GOFER algorithm includes parameter optimizations for defining the burned-to-unburned boundary and correcting for the parallax effect from elevated terrain. We evaluate GOFER perimeters with using 12-hourly data from the VIIRS-derived Fire Event Data Suite (FEDS) and final fire perimeters from California’s Fire and Resource Assessment Program (FRAP). Although the GOES imagery used to derive GOFER has coarser resolution (2 km at the equator), the final fire perimeters from GOFER correspond reasonably well with those obtained from FRAP, with a mean Intersection-over-Union (IoU) of 0.77, in comparison to 0.83 between FEDS and FRAP. GOFER fills a key temporal gap present in other fire tracking products that rely on low-earth-orbit imagery, where perimeters are available at 12-hour intervals or longer, or at ad hoc intervals from aircraft overflights. This is particularly relevant when a fire spreads rapidly, such as at maximum hourly spread rates of over 5 km/h. Our GOFER algorithm for deriving the hourly fire progression using GOES can be applied to large wildfires across North and South America and reveals considerable variability in rates of fire spread on diurnal time scales. The resulting GOFER dataset has a broad set of applications, including the development of predictive models for fire spread and improvement of atmospheric transport models for surface smoke estimates.

show abstract

“…One key feature in calibrating and validating fire behavior model outputs is its comparison against observed fire metrics, such as rate of spread and fireline intensity [58], as the current calibration process solely focuses on reproducing historical fire size and frequency. Although comprehensive open-access fire behavior data is difficult to obtain, new fire behavior datasets are being published [59,60], which can foster the use of fire behavior metrics in the calibration of MTT models.…”

Section: Future Workmentioning

confidence: 99%

MTTfireCAL Package for R—An Innovative, Comprehensive, and Fast Procedure to Calibrate the MTT Fire Spread Modelling System

Aparício

Benali

Pereira

et al. 2023

Fire

Self Cite

View full text Add to dashboard Cite

Fire spread behavior models are used to estimate fire behavior metrics, fire hazard, exposure, and risk across the landscape. One of the most widely used fire spread models is the minimum travel time (MTT), which requires a very time-consuming, interactive, trial-and-error calibration process to reproduce observed fire regimens. This study presents the MTTfireCAL package for R, a tool that enables fast calibration of the MTT fire spread models by testing and combining multiple settings and then ranking them based on the model’s capacity to reproduce historical fire patterns, such as fire size distribution and fire frequency. Here, we explain the main methodological steps and validate the package by comparing it against the typical calibration procedures in two study areas. In addition, we estimate the minimum number of fire runs required to ensure a reliable calibration. Overall, the use of MTTfireCAL R package and the optimization of the number of ignitions used allowed for a faster calibration of the MTT modeling system than the typical trial-and-error calibration. The MTT modeling system calibrated using MTTfireCAL was also able to better reproduce the historical fire patterns. This tool has the potential to support the academic and operational community working with MTT.

show abstract

The Portuguese Large Wildfire Spread Database (PT-FireSprd)

Cited by 3 publications

References 24 publications

The Portuguese Large Wildfire Spread database (PT-FireSprd)

The Portuguese Large Wildfire Spread database (PT-FireSprd)

Systematically tracking the hourly progression of large wildfires using GOES satellite observations

MTTfireCAL Package for R—An Innovative, Comprehensive, and Fast Procedure to Calibrate the MTT Fire Spread Modelling System

Contact Info

Product

Resources

About