Status: this preprint is currently under review for the journal ESSD.
The Portuguese Large Wildfire Spread Database (PT-FireSprd)
Akli Benali1,Nuno Guiomar2,Hugo Gonçalves3,4,Bernardo Mota5,Fábio Silva3,4,Paulo M. Fernandes6,Carlos Mota3,4,Alexandre Penha4,João Santos3,4,José M. C. Pereira1,7,and Ana C. L. Sá1Akli Benali et al.Akli Benali1,Nuno Guiomar2,Hugo Gonçalves3,4,Bernardo Mota5,Fábio Silva3,4,Paulo M. Fernandes6,Carlos Mota3,4,Alexandre Penha4,João Santos3,4,José M. C. Pereira1,7,and Ana C. L. Sá1
1Centro de Estudos Florestais, Instituto Superior de Agronomia, Universidade de Lisboa, Tapada da Ajuda, 1349-017 Lisboa, Portugal
2MED - Mediterranean Institute for Agriculture, Environment and Development; CHANGE - Global Change and Sustainability; EaRSLab - Earth Remote Sensing Laboratory Institute; IIFA - Institute for Advanced Studies and Research; University of Évora, 7006-554 Évora, Portugal
3Força Especial de Proteção Civil, 2080-221 Almeirim, Portugal
4Autoridade Nacional de Emergência e Proteção Civil, 2799-51 Carnaxide, Portugal
6CITAB - Centro de Investigação e de Tecnologias Agro-Ambientais e Biológicas, Universidade de Trás-os-Montes e Alto Douro, 5001-801 Vila Real, Portugal
7Laboratório Associado TERRA, Tapada da Ajuda, 1349-017 Lisboa, Portugal
1Centro de Estudos Florestais, Instituto Superior de Agronomia, Universidade de Lisboa, Tapada da Ajuda, 1349-017 Lisboa, Portugal
2MED - Mediterranean Institute for Agriculture, Environment and Development; CHANGE - Global Change and Sustainability; EaRSLab - Earth Remote Sensing Laboratory Institute; IIFA - Institute for Advanced Studies and Research; University of Évora, 7006-554 Évora, Portugal
3Força Especial de Proteção Civil, 2080-221 Almeirim, Portugal
4Autoridade Nacional de Emergência e Proteção Civil, 2799-51 Carnaxide, Portugal
6CITAB - Centro de Investigação e de Tecnologias Agro-Ambientais e Biológicas, Universidade de Trás-os-Montes e Alto Douro, 5001-801 Vila Real, Portugal
7Laboratório Associado TERRA, Tapada da Ajuda, 1349-017 Lisboa, Portugal
Received: 31 Dec 2022 – Discussion started: 23 Jan 2023
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 a 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/products, airborne and ground data collected by fire personnel, 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 MSG-SEVIRI fire radiative power estimates. A total of 1197 observations of ROS and FGR were estimated along with 609 FRE estimates. The extreme fires of 2017 were responsible for the maximum observed values of ROS (8956 m/h) and FGR (4436 ha/h). Combining both descriptors, we defined 6 fire behaviour classes that can be easily communicated to both research and management communities and support a wide number of applications. Analysis also showed that the area burned by a wildfire is mostly determined by its FGR rather than by its forward speed. Finally, we explored a practical example to show the PT-FireSprd database can be used to study the dynamics of individual wildfires and 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. 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 (last access: 30th December 2022) and have a large potential to improve current knowledge on wildfire behaviour and support better decision-making (Benali et al. 2022).
I commend the authors for their work on developing a significant wildfire behaviour dataset. I found the work of great interest to the fire research community, and can see their methods and data being used by many in the I have few major comments (below) and a number of small comments that are in the attached pdf.
The manuscript reads well, but there are a number of sentences that seem incomplete or are somewhat incoherent. I note those in the attached pdf. Authors should also be more direct and concise in their writing. The manuscript is quite long, and I made note of content that could be left out as it is not necessary.
This is a wildfire spread database which is quite relevant. The authors should nonetheless mention clearly that no collation of data on weather, fuels, topography, etc was conducted within the context of this study. This is never mentioned. Although the authors mentioned later in the manuscript that the data can be used for better understanding of wildfire drivers, model evaluation, etc. this cannot be conducted unless other data is present. As it is, the spread data in isolation does not allow for much of an analysis.
There are important limitations of the satellite data. Some of them are mentioned, others are not. An important point that should be made is that just because the satellite or someone says the fire is at a certain location at a given time, it does not mean that the fire just arrived there at such time. The fire might have arrived hours before, and hence the average rate of spread for a burning period is a value that is diluted, combining periods of rapid spread and no spread. This is quite relevant as fire behaviour is highly nonlinear, and averaged values over larger time periods can be misleading. These aspects should be noted in the manuscript.
It is not clear how combining different methods to map a fire location are integrated. Do some methods have prevalence over others? Photographic evidence vs satellite information? Is there a process that is followed? If yes, this should be described.
I have two main technical comments.
The proposal of a fire behaviour classes based on your data is fraught with error. It is ok to explore the distribution of your data, but to propose such distribution (which you said, was biased to large fires) to derive a fire behaviour classification is wrong. The classification class threshold have no physical meaning, and you can realise that if you check into a number of fire behaviour and danger classifications developed from fire behaviour – operational implications. A proof that your proposed classification is meaningless, is the fact that if in the next two fire seasons you add 40 new wildfires all burning under moderate to high fire danger (lets say it is a mild fire season), your new fire behaviour classification classes will change drastically. What is the point then? I strongly suggest this is removed from the manuscript.
The authors use their dataset and make a ‘finding’ that area burned is mostly a function of fire growth rate rather than rate of fire spread. This result is obvious by several reasons, the simplest one being that the rate of spread is only related to the area burned for the initial stages of a fire growing from a point source. From the moment a fire is affected by topography, fuels, and burn over several burn periods and days, it is the area growth rate that is linked with the fire area, not the rate of fire spread. I do not see this a finding, whatsoever. Of course, a 2 dimensional area growth metric is going to be more related to the final burned area than a one dimensional metric of fire propagation (ROS). As with the previous point, I strongly suggest that this is removed from the manuscript.
It is not clear why the authors depart from their main focus of the study, describing how the database was assemble, to do a spurious analysis of the data and come up with these findings, that, in my view, are not really findings. If the authors want to explore those aspects of fire behaviour, then they should do so in a different piece of work, with proper basis and analysis.
Other minor comments:
What is the certainty in the intermediate perimeters (isochrones) in figure 3? I cannot imagine you were able to collect data across all the perimeter to make such a nice polygon. Were they interpolated? If so, they might provide a false sense of certainty.
The Portuguese Large Wildfire Spread Database (PT-FireSprd) (v0.08)Akli Benali, Nuno Guiomar, Hugo Gonçalves, Bernardo Mota, Fábio Silva, Paulo M. Fernandes, Carlos Mota, Alexandre Penha, João Santos, José M. C. Pereira, Ana C. L. Sá https://doi.org/10.5281/zenodo.7495506
Akli Benali et al.
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To allow for a significant progress towards better fire management, detailed good quality open data on observed wildfire behavior are crucial. We reconstructed the spread of 80 large wildfires that burned recently in Portugal, and calculated metrics that describe “how” the wildfires behaved (example: fire front speed). We used this data to build 6 easy-to-communicate fire behavior classes. The database will improve our current knowledge on wildfires and contribute to better fire management.
To allow for a significant progress towards better fire management, detailed good quality open...
