Forest fires: Evaluation of government intervention measures

The purpose of this paper is to examine the relation between government measures, volunteer participation, climate variables and forest fires. A number of studies have related forest fires to causes of ignition, to fire history in one area, to the type of vegetation and weather characteristics or to community institutions, but there is little research on the relation between fire production and government prevention and extinction measures from a policy evaluation perspective. An observational approach is first applied to select forest fires in the north east of Spain. Taking a selection of fires with a certain size, a multiple regression analysis is conducted to find significant relations between policy instruments under the control of the government and the number of hectares burn in each case, controlling at the same time the effect of weather conditions and other context variables. The paper brings evidence on the effects of simultaneity and the relevance of recurring to army soldiers in specific days with extraordinary high simultaneity. The analysis also brings light on the effectiveness of two preventive policies and of helicopters for extinction tasks.Forest fires, policy evaluation

On the use of satellite Sentinel 2 data for automatic mapping of burnt areas and burn severity

In this paper, we present and discuss the preliminary tools we devised for the automatic recognition of burnt areas and burn severity developed in the framework of the EU-funded SERV_FORFIRE project. The project is focused on the set up of operational services for fire monitoring and mitigation specifically devised for decision-makers and planning authorities. The main objectives of SERV_FORFIRE are: (i) to create a bridge between observations, model development, operational products, information translation and user uptake; and (ii) to contribute to creating an international collaborative community made up of researchers and decision-makers and planning authorities. For the purpose of this study, investigations into a fire burnt area were conducted in the south of Italy from a fire that occurred on 10 August 2017, affecting both the protected natural site of Pignola (Potenza, South of Italy) and agricultural lands. Sentinel 2 data were processed to identify and map different burnt areas and burn severity levels. Local Index for Statistical Analyses LISA were used to overcome the limits of fixed threshold values and to devise an automatic approach that is easier to re-apply to diverse ecosystems and geographic regions. The validation was assessed using 15 random plots selected from in situ analyses performed extensively in the investigated burnt area. The field survey showed a success rate of around 95%, whereas the commission and omission errors were around 3% of and 2%, respectively. Overall, our findings indicate that the use of Sentinel 2 data allows the development of standardized burn severity maps to evaluate fire effects and address post-fire management activities that support planning, decision-making, and mitigation strategies.Fil: Lasaponara, Rosa. Consiglio Nazionale delle Ricerche; ItaliaFil: Tucci, Biagio. Consiglio Nazionale delle Ricerche; ItaliaFil: Ghermandi, Luciana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina. Universidad Nacional del Comahue. Centro Regional Universitario Bariloche. Laboratorio de Ecotono; Argentin

Improving our understanding of individual wildfires by combining satellite data with fire spread modelling

Doutoramento em Engenharia Florestal e dos Recursos Naturais - Instituto Superior de AgronomiaWildfires pose real threats to life and property. In Portugal, the recent year of 2017 had the largest burnt area extent and number of casualties. A knowledge gap still exists in wildfire research related with better understanding individual wildfires, which has important implications for fire suppression, management, and policies. Wildfire spread models have been used to study individual wildfires, however, associated uncertainties and the lack of systematic evaluation methods hamper their capability for accurately predicting their spread. Understanding how fire spread predictions can be improved is a critical research task, as they will only be deemed useful if they can provide accurate and reliable information to fire managers. The present Thesis proposes to contribute to improve fire spread predictions by: i) Developing a methodology to systematically evaluate fire spread predictions ii) Thoroughly characterizing input data uncertainty and its impact on predictions; iii) Improving predictions using data-driven model calibration. The spread of large historical wildfires were studied by combining satellite data and models. The major findings of the present Thesis were: i) Satellite data accurately contributed to provide accurate fire dates and ignition information for large wildfires. ii) The evaluation metrics were very useful in identifying areas and periods of low/high spatio-temporal agreement, highlighting the strong underprediction bias and poor accuracy of the predictions. iii) Uncertainties in wind speed and direction, fuel model assignment and typology, location and timing of ignitions, had a major impact on prediction accuracy. iv) Predictions iii) Uncertainties in wind speed and direction, fuel model assignment and typology, location and timing of ignitions, had a major impact on prediction accuracy. iv) Predictions were improved by ‘learning’ from past wildfires, significantly reducing the impact of data uncertainty on the accuracy of fire spread predictions Overall, the work contributed to advance the body of knowledge regarding individual wildfires and identified future research steps towards a reliable operational fire system capable of supporting more effective and safer fire management decisions with the aim of reducing the dramatic impacts of wildfiresN/

Evaluation of a Bayesian Algorithm to Detect Burned Areas in the Canary Islands’ Dry Woodlands and Forests Ecoregion Using MODIS Data

Burned Area (BA) is deemed as a primary variable to understand the Earth’s climate system. Satellite remote sensing data have allowed for the development of various burned area detection algorithms that have been globally applied to and assessed in diverse ecosystems, ranging from tropical to boreal. In this paper, we present a Bayesian algorithm (BY-MODIS) that detects burned areas in a time series of Moderate Resolution Imaging Spectroradiometer (MODIS) images from 2002 to 2012 of the Canary Islands’ dry woodlands and forests ecoregion (Spain). Based on daily image products MODIS, MOD09GQ (250 m), and MOD11A1 (1 km), the surface spectral reflectance and the land surface temperature, respectively, 10 day composites were built using the maximum temperature criterion. Variables used in BY-MODIS were the Global Environment Monitoring Index (GEMI) and Burn Boreal Forest Index (BBFI), alongside the NIR spectral band, all of which refer to the previous year and the year the fire took place in. Reference polygons for the 14 fires exceeding 100 hectares and identified within the period under analysis were developed using both post-fire LANDSAT images and official information from the forest fires national database by the Ministry of Agriculture and Fisheries, Food and Environment of Spain (MAPAMA). The results obtained by BY-MODIS can be compared to those by official burned area products, MCD45A1 and MCD64A1. Despite that the best overall results correspond to MCD64A1, BY-MODIS proved to be an alternative for burned area mapping in the Canary Islands, a region with a great topographic complexity and diverse types of ecosystems. The total burned area detected by the BY-MODIS classifier was 64.9% of the MAPAMA reference data, and 78.6% according to data obtained from the LANDSAT images, with the lowest average commission error (11%) out of the three products and a correlation (R2) of 0.82. The Bayesian algorithm—originally developed to detect burned areas in North American boreal forests using AVHRR archival data Long-Term Data Record—can be successfully applied to a lower latitude forest ecosystem totally different from the boreal ecosystem and using daily time series of satellite images from MODIS with a 250 m spatial resolution, as long as a set of training areas adequately characterising the dynamics of the forest canopy affected by the fire is defined

Assessment of burned forest area severity and postfire regrowth in chapada Diamantina National Park (Bahia, Brazil) using dNBR and RdNBR spectral indices

Fire scar detection through orbital data can be done using specific techniques, such as the use of spectral indices like the normalized burn ratio (NBR), which are designed to help identify burnt areas as they have typical spectral responses. This paper aims to characterize burn severity and regrowth in areas hit by three fires in the Chapada Diamantina National Park (Bahia, Brazil) and its surrounding area through the differenced normalized burn ratio (dNBR) and relative differenced normalized burn ratio (RdNBR) spectral indices. The data acquired were pretreated and prepared adequately to calculate the indices. We conclude that for the study area, considering the limitations of fieldwork, the multitemporal index dNBR and the relative index RdNBR are important tools for classifying burnt areas and can be used to assess the regrowth of vegetation.This research was partially financed by FAPESB (Research Support Foundation of the State of Bahia) by granting a master’s scholarship (Nº BOL0141/2015), partially cofinanced by the Annual Land Cover and Use Mapping Project in Brazil (MapBiomas), and partially cofinanced by the European Regional Development Fund (ERDF) through the COMPETE 2020 Operational Programme Competitiveness and Internationalization (POCI) and national funds by FCT under the POCI-01-0145-FEDER-006891 project (FCT Ref: UID/GEO 04084/2019)

An integer programming approach for sensor location in a forest fire monitoring system

Forests worldwide have been devastated by fires. Forest fires cause incalculable damage to fauna and flora. In addition, a forest fire can lead to the death of people and financial damage in general, among other problems. To avoid wildfire catastrophes is fundamental to detect fire ignitions in the early stages, which can be achieved by monitoring ignitions through sensors. This work presents an integer programming approach to decide where to locate such sensors to maximize the coverage provided by them, taking into account different types of sensors, fire hazards, and technological and budget constraints. We tested the proposed approach in a real-world forest with around 7500 locations to be covered and about 1500 potential locations for sensors, showing that it allows obtaining optimal solutions in less than 20 min.This work has been supported by FCT Fundação para a Ciência e Tecnologia within the R&D Units Project Scope UIDB/00319/2020 and within project PCIF/GRF/0141/2019 “O3F - An Optimization Framework to reduce Forest Fire” and also the project UIDB/05757/2020 and Forest Alert Monitoring System (SAFe) Project through PROMOVE - Funda¸c˜ao La Caixa. Beatriz Flamia Azevedo is supported by FCT Grant Reference SFRH/BD/07427/2021, Thadeu Brito was supported by FCT PhD grant SFRH/BD/08598/2020

COSMO-SkyMed potential to detect and monitor Mediterranean maquis fires and regrowth: a pilot study in Capo Figari, Sardinia, Italy

Mediterranean maquis is a complex and widespread ecosystem in the region, intrinsically prone to fire. Many species have developed specific adaptation traits to cope with fire, ensuring resistance and resilience. Due to the recent changes in socio-economy and land uses, fires are more and more frequent in the urban-rural fringe and in the coastlines, both now densely populated. The detection of fires and the monitoring of vegetation regrowth is thus of primary interest for local management and for understanding the ecosystem dynamics and processes, also in the light of the recurrent droughts induced by climate change. Among the main objectives of the COSMO-SkyMed radar constellation mission there is the monitoring of environmental hazards; the very high revisiting time of this mission is optimal for post-hazard response activities. However, very few studies exploited such data for fire and vegetation monitoring. In this research, Cosmo-SkyMed is used in a Mediterranean protected area covered by maquis to detect the burnt area extension and to conduct a mid-term assessment of vegetation regrowth. The positive results obtained in this research highlight the importance of the very high-resolution continuous acquisitions and the multi-polarization information provided by COSMO-SkyMed for monitoring fire impacts on vegetation

Empirical Analysis of Firefighting – Large-Fire Suppression in Victoria, Australia

Large fires can cause the deaths of hundreds of people, burn thousands of homes, and cost billions of dollars in damages. Suppression is the primary means of large-fire management. Most suppression costs, billions of dollars, come from large-fire suppression. Yet, formal knowledge of large-fire suppression is limited. Fire managers make decisions that impact the lives of thousands of people. As the effectiveness of large-fire suppression is mainly unquantified, there is little beyond their tacit knowledge to guide decisions. Before we address effectiveness, we must address a fundamental question: ‘How are suppression resources used on large fires?’ This thesis uses qualitative and quantitative methods to answer that question. This thesis examines the suppression of 74 large fires that occurred between 2010 and 2015 in Victoria, Australia. The Department of Environment, Land, Water and Planning made this research possible by providing operational data. The first step to resolving suppression resource use was to develop a framework of large-fire suppression (Chapter 3). A qualitative document analysis was performed on a subset of ten large fires. Three approaches were involved: 1) daily fire reconstructions were completed, covering 156 days, 2) a five-stage classification of suppression was developed by analysing the reconstructions and comments in 674 operational documents, and 3) content analysis was performed on the comments to classify discrete suppression tasks. Large-fire suppression was framed as a progression through five discrete stages with 20 identified tasks. A striking result was that 57% of resource use was on tasks that fall outside of current suppression modelling and productivity research

ASSESSMENT OF FIREFIGHTING EFFICIENCY OF VEGETATION FIRES IN CURITIBA-PARANÁ

Vegetation fires, when not controlled, cause economic disruption, temporary loss of vegetation, and damage to soil, fauna and health. To improve the process of fire prevention and firefighting, it is necessary to evaluate the performance of the involved agents. The objective of this study was to evaluate the firefighting efficiency of vegetation fires in the municipality of Curitiba, Paraná, from 2011 to 2015, using records from the Fire Department of the Military Police of Paraná. Once the consistency of the fire records was verified, they were classified and information was gathered regarding the extent of burnt area, time of first attack, combat time, main fire-extinguishing methods used, and amount of water used. The results indicate that 88% of the records registered a burnt area inferior or equal to four hectares. In addition, the mean burnt area was of 2,399.21 m², the mean attack time was of 14.1 minutes, and the mean combat time was of 29.9 minutes, all lower than the ones presented by studies from different locations. As for the fire-extinguishing methods, it was verified that smothering equipment and water were used in 66.4 and 60.6% of the records, respectively. The mean amount of water used was of 1,186.56 liters per fire, indicating a minimum volume necessary for water storage containers for firefighting in the study area. Based on the results, we concluded that the firefighting of vegetation fires in Curitiba is efficient