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Novel technological advances in mobile devices and applications can be exploited in wildfire confrontation, enabling end-users to easily conduct several everyday tasks, such as access to data and information, sharing of intelligence and coordination of personnel and vehicles. This work describes an innovative mobile application for wildfire information management that operates on Windows Phone devices and acts as a complementary tool to the web-based version of the AEGIS platform for wildfiredoi:10.1016/j.procs.2015.07.249 fatcat:p366uaqu3nb5leon5ggwnpo7xy
more »... evention and management. Several tasks can be accomplished from the AEGIS App, such as routing, spatial search for closest facilities and firefighting support infrastructures, access to weather data and visualization of fire management data (water sources, gas refill stations, evacuation sites etc.). An innovative feature of AEGIS App is the support of these tasks by a digital assistant for artificial intelligence named Cortana (developed by Microsoft for Windows Phone devices), that allows information utilization through voice commands. The application is to be used by firefighting personnel in Greece and is potentially expected to contribute towards a more sophisticated transferring of information and knowledge between wildfire confrontation operation centers and firefighting units in the field.
Large-scale wildfires have become more frequent in Greece and coupled with the country's limited economic resources, investments in both pre-fire planning and post-fire rehabilitation for most affected areas are not feasible. From the perspective of forest and fire management agencies, the severity and importance of fire effects are evaluated based only on total area burned, while from a societal standpoint, by the number of fatalities and destroyed houses. A holistic approach to rank wildfiresdoi:10.3390/fire3040063 fatcat:w3sb4xojrrexxigqa23lwifcmm
more »... with an inclusive assessment of all their effects is missing. We developed a new evaluation and ranking index based on expert judgment, the study of 50 large-scale fire events in Greece and a detailed review of the literature, to develop a set of categories and criteria to assess ecological and socioeconomic effects of wildfires. The Fire Inventory and Ranking of Effects (FIRE) Index provides a comprehensive and easy-to-use semi-numeric framework that combines scores from seven fire effects categories and 56 criteria through a user-friendly web-platform. The seven categories include fire effects on landscape and vegetation, general environmental impacts, regeneration potential and vegetation recovery, casualties and fatalities, destruction and damages to infrastructure, economic losses, and firefighting and wildfire suppression. Each of the 56 criteria within these categories describes a different anticipated fire effect. The magnitude of each fire effect criterion is estimated by predefined ranked choices by one or more persons/assessors in a multi-level evaluation procedure. We apply the FIRE Index assessment to a significant 5900-ha wildfire that occurred in 2011 in northern Greece, including a sensitivity analysis of how different category weights impact the final index score. More diverse metrics to assess wildfire effects will help address the complex social and biophysical dimensions of the wildfire governance challenge and help guide pre- and post-fire management actions.
Adapting to the growing frequency of catastrophic wildfires in Greece and mitigating their effects is a complex socio-ecological problem. We used an online survey to query more than 100 engaged stakeholders who can potentially influence possible legislation and fire management organizational reform, emphasizing civil protection agencies and research entities. We focused the questionnaire on the importance of different wildfire effects to understand which were considered negative ordoi:10.3390/fire4020018 fatcat:4w32k5vsnzgchisml6uqypsyfa
more »... indifferent, or positive. For fire prevention, we examined the range of acceptance and views on fuel management and fire use activities that are limited in extent or not allowed in Greece. We also examined the beliefs regarding ignition causes and responsibility, in addition to how different policies might reduce wildfire-related problems. The results revealed an emphasis on reforming wildfire management policies to deal with the way society and agencies function and interact, and mitigate the influence of climate change in wildfire frequency and behavior. In addition, respondents had a negative stance towards allowing wildfires to burn for resource objectives and a strong belief that arsonists are behind most ignitions. They also believe the lack of a national cadaster system is a major source of wildfire-related problems. The results indicate little support for fuel treatments, but increased acceptance for the legalization of fire use during firefighting (backfires). This study summarizes current wildfire perceptions in Greece and identifies opportunities and barriers to changes in wildfire governance to improve risk management programs and guide post-fire management and mitigation.
A solution to the growing problem of catastrophic wildfires in Greece will require a more holistic fuel management strategy that focuses more broadly on landscape fire behavior and risk in relation to suppression tactics and ignition prevention. Current fire protection planning is either non-existent or narrowly focused on reducing fuels in proximity to roads and communities where ignitions are most likely. A more effective strategy would expand the treatment footprint to landscape scales todoi:10.3390/f11080789 fatcat:lcwcwmnqnrakfpl6n722v7v6rm
more »... uce fire intensity and increase the likelihood of safe and efficient suppression activities. However, expanding fuels treatment programs on Greek landscapes that are highly fragmented in terms of land use and vegetation requires: (1) a better understanding of how diverse land cover types contribute to fire spread and intensity; and (2) case studies, both simulated and empirical, that demonstrate how landscape fuel management strategies can achieve desired outcomes in terms of fire behavior. In this study, we used Lesvos Island, Greece as a study area to characterize how different land cover types and land uses contribute to fire exposure and used wildfire simulation methods to understand how fire spreads among parcels of forests, developed areas, and other land cover types (shrublands, agricultural areas, and grasslands) as a way to identify fire source–sink relationships. We then simulated a spatially coordinated fuel management program that targeted the fire prone conifer forests that generally burn under the highest intensity. The treatment effects were measured in terms of post-treatment fire behavior and transmission. The results demonstrated an optimized method for fuel management planning that accounts for the connectivity of wildfire among different land types. The results also identified the scale of risk and the limitations of relying on small scattered fuel treatment units to manage long-term wildfire risk.
We assessed transboundary wildfire exposure among federal, state, and private lands and 447 communities in the state of Arizona, southwestern United States. The study quantified the relative magnitude of transboundary (incoming, outgoing) versus nontransboundary (i.e., self-burning) wildfire exposure based on land tenure or community of the simulated ignition and the resulting fire perimeter. We developed and described several new metrics to quantify and map transboundary exposure. We founddoi:10.1111/risa.12999 pmid:29694686 fatcat:ezpfbtrjdranvhpk34odeaaucu
more »... incoming transboundary fire accounted for 37% of the total area burned on large parcels of federal and state lands, whereas 63% of the area burned was burned by ignitions within the parcel. However, substantial parcel to parcel variation was observed for all land tenures for all metrics. We found that incoming transboundary fire accounted for 66% of the total area burned within communities versus 34% of the area burned by self-burning ignitions. Of the total area burned within communities, private lands contributed the largest proportion (36.7%), followed by national forests (19.5%), and state lands (15.4%). On average seven land tenures contributed wildfire to individual communities. Annual wildfire exposure to structures was highest for wildfires ignited on state and national forest land, followed by tribal, private, and BLM. We mapped community firesheds, that is, the area where ignitions can spawn fires that can burn into communities, and estimated that they covered 7.7 million ha, or 26% of the state of Arizona. Our methods address gaps in existing wildfire risk assessments, and their implementation can help reduce fragmentation in governance systems and inefficiencies in risk planning.
In this study, we share an approach to locate and map forest management units with high accuracy and with relatively rapid turnaround. Our study area consists of private, state, and federal land holdings that cover four counties in North-Central Washington, USA (Kittitas, Okanogan, Chelan and Douglas). This area has a rich history of landscape change caused by frequent wildfires, insect attacks, disease outbreaks, and forest management practices, which is only partially documented acrossdoi:10.3390/s20092454 pmid:32357414 pmcid:PMC7249656 fatcat:2ra72x5xx5etvjr7sciobr6rdi
more »... ips in an inconsistent fashion. To consistently quantify forest management activities for the entire study area, we leveraged Sentinel-2 satellite imagery, LANDFIRE existing vegetation types and disturbances, monitoring trends in burn severity fire perimeters, and Landsat 8 Burned Area products. Within our methodology, Sentinel-2 images were collected and transformed to orthogonal land cover change difference and ratio metrics using principal component analyses. In addition, the Normalized Difference Vegetation Index and the Relativized Burn Ratio index were estimated. These variables were used as predictors in Random Forests machine learning classification models. Known locations of forest treatment units were used to create samples to train the Random Forests models to estimate where changes in forest structure occurred between the years of 2016 and 2019. We visually inspected each derived polygon to manually assign one treatment class, either clearcut or thinning. Landsat 8 Burned Area products were used to derive prescribed fire units for the same period. The bulk of analyses were performed using the RMRS Raster Utility toolbar that facilitated spatial, statistical, and machine learning tools, while significantly reducing the required processing time and storage space associated with analyzing these large datasets. The results were combined with existing LANDFIRE vegetation disturbance and forest treatment data to create a 21-year dataset (1999–2019) for the study area.
Palaiologou, et al. ... Palaiologou, et al. Landscape and Urban Planning 189 (2019) 99-116 social vulnerability characterization. ...doi:10.1016/j.landurbplan.2019.04.006 fatcat:rnh6s3hfwzb3pahsxwcawivcni
Charnley, 2018; Schoennagel, Nelson, Theobald, Carnwath, & Chapman, 2009 ), high fire hazard locations (Vaillant & Reinhardt, 2017) , and demography of affected populations (Adams & Charnley, 2018; Palaiologou ... al., 2010; Modugno et al., 2016; van Wilgen, Forsyth, & Prins, 2012) Theobald & Romme, 2007) underscores the need for expanding and improving existing planning systems and wildfire risk governance (Palaiologou ...doi:10.1016/j.apgeog.2019.102059 fatcat:bflh6y3b2bef7ask53kysja5vq
Managing forests has been demonstrated to be an efficient strategy for fragmenting fuels and for reducing fire spread rates and severity. However, large-scale analyses to examine operational aspects of implementing different forest management scenarios to meet fire governance objectives are nonexistent for many Mediterranean countries. In this study we described an optimization framework to build forest management scenarios that leverages fire simulation, forest management, and tradeoffdoi:10.3390/f12060697 fatcat:n52ulqmpunas3ifzsomkx2bluy
more »... for forest areas in Macedonia, Greece. We demonstrated the framework to evaluate five forest management priorities aimed at (1) protection of developed areas, (2) optimized commercial timber harvests, (3) protection of ecosystem services, (4) fire resilience, and (5) reducing suppression difficulty. Results revealed that by managing approximately 33,000 ha across all lands in different allocations of 100 projects, the area that accounted for 16% of the wildfire exposure to developed areas was treated while harvesting 2.5% of total wood volume. The treatments also reduced fuels on the area that are responsible for 3% of the potential fire impacts to sites with important ecosystem services, while suppression difficulty and wildfire transmission to protected areas attainment was 4.5% and 16%, respectively. We also tested the performance of multiple forest district management priorities when applying a proposed four-year fuel treatment plan that targeted achieving high levels of attainment by treating less area but strategically selected lands. Sharp management tradeoffs were observed among all management priorities, especially for harvest production compared with suppression difficulty, the protection of developed areas, and wildfire exposure to protected areas.
<p><strong>Abstract.</strong> We describe a Web-GIS wildfire prevention and management platform (AEGIS) developed as an integrated and easy-to-use decision support tool to manage wildland fire hazards in Greece (<a href="http://aegis.aegean.gr" target="_blank">http://aegis.aegean.gr</a>). The AEGIS platform assists with early fire warning, fire planning, fire control and coordination of firefighting forces by providing online access to information that is essential for wildfire management. Thedoi:10.5194/nhess-16-643-2016 fatcat:znhnn67xhvcbdboebxnmoas4b4
more »... ystem uses a number of spatial and non-spatial data sources to support key system functionalities. Land use/land cover maps were produced by combining field inventory data with high-resolution multispectral satellite images (RapidEye). These data support wildfire simulation tools that allow the users to examine potential fire behavior and hazard with the Minimum Travel Time fire spread algorithm. End-users provide a minimum number of inputs such as fire duration, ignition point and weather information to conduct a fire simulation. AEGIS offers three types of simulations, i.e., single-fire propagation, point-scale calculation of potential fire behavior, and burn probability analysis, similar to the FlamMap fire behavior modeling software. Artificial neural networks (ANNs) were utilized for wildfire ignition risk assessment based on various parameters, training methods, activation functions, pre-processing methods and network structures. The combination of ANNs and expected burned area maps are used to generate integrated output map of fire hazard prediction. The system also incorporates weather information obtained from remote automatic weather stations and weather forecast maps. The system and associated computation algorithms leverage parallel processing techniques (i.e., High Performance Computing and Cloud Computing) that ensure computational power required for real-time application. All AEGIS functionalities are accessible to authorized end-users through a web-based graphical user interface. An innovative smartphone application, AEGIS App, also provides mobile access to the web-based version of the system.</p>
A B S T R A C T Risk management typologies and their resulting archetypes can structure the many social and biophysical drivers of community wildfire risk into a set number of strategies to build community resilience. Existing typologies omit key factors that determine the scale and mechanism by which exposure from large wildfires occur. These factors are particularly important for land managing agencies like the US Forest Service, which must weigh community wildfire exposure against otherdoi:10.1016/j.landurbplan.2018.10.004 fatcat:r6yote5dbfgjfpxx75zqsoeilm
more »... ement priorities. We analyze community wildfire exposure from national forests by associating conditions that affect exposure in the areas where wildfires ignite to conditions where exposure likely occurs. Linking source and exposure areas defines the scale at which crossboundary exposure from large wildfires occurs and the scale at which mitigation actions need to be planned. We find that the vast majority of wildfire exposure from national forests is concentrated among a fraction of communities that are geographically clustered in discrete pockets. Among these communities, exposure varies primarily based on development patterns and vegetation gradients and secondarily based on social and ecological management constraints. We describe five community exposure archetypes along with their associated risk mitigation strategies. Only some archetypes have conditions that support hazardous fuels programs. Others have conditions where managing community exposure through vegetation management is unlikely to suffice. These archetypes reflect the diversity of development patterns, vegetation types, associated fuels, and management constraints that exist in the western US and provide a framework to guide public investments that improve management of wildfire risk within threatened communities and on the public lands that transmit fires to them. (WUI), the area where development and infrastructure are located within or adjacent to wildland vegetation (e.g., forests, shrublands, grasslands). Combined with longer fire seasons, altered ignition patterns, and accumulation of fuels, growth of the WUI has accelerated suppression costs and wildfire-related losses (Schoennagel et al., 2017) . The exact definition of the WUI varies by country and statute. In the US, the two classes of WUI most commonly described are the intermix WUI, where development is scattered within wildlands, and the interface WUI, where development abuts wildlands (USDA and USDI, 2001). Maps depicting the extent of WUI in the US now span more than two https://doi.
., 2018; Palaiologou et al., 2018) , but they are not yet considered in the official 15 wildfire risk assessments at the pan-European level (San-Miguel-Ayanz et al., 2018) . ... ( Evers et al., 2019;Hamilton et al., In press;Palaiologou et al., Under revision; Bodin and Tengö, 2012) .Establishing cross-boundary fuel management projects with other major landowners has become ...doi:10.5194/nhess-2019-56 fatcat:5neitjfjvzfqfke2wmtidbznfm
Advances in forest fire research
A navegação consulta e descarregamento dos títulos inseridos nas Bibliotecas Digitais UC Digitalis, UC Pombalina e UC Impactum, pressupõem a aceitação plena e sem reservas dos Termos e Condições de Uso destas Bibliotecas Digitais, disponíveis em https://digitalis.uc.pt/pt-pt/termos. Conforme exposto nos referidos Termos e Condições de Uso, o descarregamento de títulos de acesso restrito requer uma licença válida de autorização devendo o utilizador aceder ao(s) documento(s) a partir de umdoi:10.14195/978-989-26-0884-6_95 fatcat:j7wa56w36nbejmv5l6qazas7f4
more »... o de IP da instituição detentora da supramencionada licença. Ao utilizador é apenas permitido o descarregamento para uso pessoal, pelo que o emprego do(s) título(s) descarregado(s) para outro fim, designadamente comercial, carece de autorização do respetivo autor ou editor da obra. Na medida em que todas as obras da UC Digitalis se encontram protegidas pelo Código do Direito de Autor e Direitos Conexos e demais legislação aplicável, toda a cópia, parcial ou total, deste documento, nos casos em que é legalmente admitida, deverá conter ou fazer-se acompanhar por este aviso. Minimum travel time algorithm for fire behavior and burn probability in a parallel computing environment Autor(es): Abstract Fire management systems materialize the integration of fire science models and decision support planning modules. Their operational usage often requires the concurrent execution of a large number of fire growth simulations by multiple users. Intensive computations such as the creation of burn probability maps demand not only high expertise but also high computing power and data storage capacity. The purpose of this paper is to present some of the initial results of the AEGIS platform, which is a Web-GIS wildfire prevention and management information system currently under development. More specifically, the paper focuses on the utilization of the Minimum Travel Time (MTT) algorithm as a powerful fire behavior prediction system. MTT in AEGIS will be applied in a transparent way through its graphical user interface. Several end users will be able to conduct on-demand fire behavior simulations. To achieve this, end users must provide a minimum amount of inputs, such as fire duration, ignition point and weather information. Weather inputs can be either inserted directly or derived from selected remote automatic weather stations or forecasted weather data maps based on the SKIRON system (Eta/NCEP model). Seasonal burn probability maps will be also prepared and provided to the end users. Socioeconomic data, weather predictions, topographic and vegetation data will be combined with artificial neural networks to produce an ignition probability map. Based on the ignition probability map, thousands of potential ignition points located in areas of anticipated high risk will be generated. These ignitions will be further used as inputs on MTT simulations, running FConstMTT as a command line-based executable. FConstMTT calculations will be conducted on a parallel mode in Microsoft Azure infrastructure using a different subset of ignition points in each simulation. The current deployment of the AEGIS platform consists of a number of machines resided on premises and a scalable Cloud Computing environment based on the Microsoft Azure infrastructure. This parallel computing environment ensures high processing power availability and high data storage capacity. During a fire emergency, the scalability of the Cloud can also provide extra processing power and storage, if needed. It is anticipated that by integrating MTT into the AEGIS platform, the firefighting and civil protection agencies will gain great assistance to organize better and more reliable plans for fire confrontation.
The time-series analysis of multi-temporal satellite data is widely used for vegetation regrowth after a wildfire event. Comparisons between pre- and post-fire conditions are the main method used to monitor ecosystem recovery. In the present study, we estimated wildfire disturbance by comparing actual post-fire time series of Moderate Resolution Imaging Spectroradiometer (MODIS) enhanced vegetation index (EVI) and simulated MODIS EVI based on an artificial neural network assuming no wildfiredoi:10.3390/ijgi7110420 fatcat:dzy4um72bfddfkwtiunnla7zqi
more »... urrence. Then, we calculated the similarity of these responses for all sampling sites by applying a dynamic time warping technique. Finally, we applied multidimensional scaling to the warping distances and an optimal fuzzy clustering to identify unique patterns in vegetation recovery. According to the results, artificial neural networks performed adequately, while dynamic time warping and the proposed multidimensional scaling along with the optimal fuzzy clustering provided consistent results regarding vegetation response. For the first two years after the wildfire, medium-high- to high-severity burnt sites were dominated by oaks at elevations greater than 200 m, and presented a clustered (predominant) response of revegetation compared to other sites.
et al. 2013  Pinus halepensis FM02 211 Yes Palaiologou et al. 2013  Non-burnable areas NB 91-99 - Scott and Burgan  © 2015 by the authors; licensee MDPI, Basel, Switzerland ... chestnuts TL2 182 Yes Scott and Burgan  Mixed oak with Quercus ilex TL6 186 Yes Scott and Burgan  Broadleaf forest TL9 189 Yes Scott and Burgan  Pinus nigra FM03 212 Yes Palaiologou ...doi:10.3390/f6062214 fatcat:uzhh6cev5vhz7agh7qq5aaqs2u
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