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risk.</title> <meta name="description" content="Search results for: wildfire risk."> <meta name="keywords" content="wildfire risk."> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none navbar-toggler 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id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="wildfire risk."> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 6034</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: wildfire risk.</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6034</span> Evaluating the Social Learning Processes Involved in Developing Community-Informed Wildfire Risk Reduction Strategies in the Prince Albert Forest Management Area </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Carly%20Madge">Carly Madge</a>, <a href="https://publications.waset.org/abstracts/search?q=Melanie%20Zurba"> Melanie Zurba</a>, <a href="https://publications.waset.org/abstracts/search?q=Ryan%20%20Bullock"> Ryan Bullock</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Boreal Forest has experienced some of the most drastic climate change-induced temperature rises in Canada, with average winter temperatures increasing by 3°C since 1948. One of the main concerns of the province of Saskatchewan, and particularly wildfire managers, is the increased risk of wildfires due to climate change. With these concerns in mind Sakaw Askiy Management Inc., a forestry corporation located in Prince Albert, Saskatchewan with operations in the Boreal Forest biome, is developing wildfire risk reduction strategies that are supported by the shareholders of the corporation as well as the stakeholders of the Prince Albert Forest Management Area (which includes citizens, hunters, trappers, cottage owners, and outfitters). In the past, wildfire management strategies implemented through harvesting have been received with skepticism by some community members of Prince Albert. Engagement of the stakeholders of the Prince Albert Management Area through the development of the wildfire risk reduction strategies aims to reduce this skepticism and rebuild some of the trust that has been lost between industry and community. This research project works with the framework of social learning, which is defined as the learning that occurs when individuals come together to form a group with the purpose of understanding environmental challenges and determining appropriate responses to them. The project evaluates the social learning processes that occur through the development of the risk reduction strategies and how the learning has allowed Sakaw to work towards implementing the strategies into their forest harvesting plans. The incorporation of wildfire risk reduction strategies works to increase the adaptive capacity of Sakaw, which in this case refers to the ability to adjust to climate change, moderate potential damages, take advantage of opportunities, and cope with consequences. Using semi-structured interviews and wildfire workshop meetings shareholders and stakeholders shared their knowledge of wildfire, their main wildfire concerns, and changes they would like to see made in the Prince Albert Forest Management Area. Interviews and topics discussed in the workshops were inductively coded for themes related to learning, adaptive capacity, areas of concern, and preferred methods of wildfire risk reduction strategies. Analysis determined that some of the learning that has occurred has resulted through social interactions and the development of networks oriented towards wildfire and wildfire risk reduction strategies. Participants have learned new knowledge and skills regarding wildfire risk reduction. The formation of wildfire networks increases access to information on wildfire and the social capital (trust and strengthened relations) of wildfire personnel. Both factors can be attributed to increases in adaptive capacity. Interview results were shared with the General Manager of Sakaw, where the areas of concern and preferred strategies of wildfire risk reduction will be considered and accounted for in the implementation of new harvesting plans. This research also augments the growing conceptual and empirical evidence of the important role of learning and networks in regional wildfire risk management efforts. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20capacity" title="adaptive capacity">adaptive capacity</a>, <a href="https://publications.waset.org/abstracts/search?q=community-engagement" title=" community-engagement"> community-engagement</a>, <a href="https://publications.waset.org/abstracts/search?q=social%20learning" title=" social learning"> social learning</a>, <a href="https://publications.waset.org/abstracts/search?q=wildfire%20risk%20reduction" title=" wildfire risk reduction "> wildfire risk reduction </a> </p> <a href="https://publications.waset.org/abstracts/132044/evaluating-the-social-learning-processes-involved-in-developing-community-informed-wildfire-risk-reduction-strategies-in-the-prince-albert-forest-management-area" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/132044.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">147</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6033</span> Wildfire Risk and Biodiversity Management: Understanding Perceptions and Preparedness</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Emily%20Moskwa">Emily Moskwa</a>, <a href="https://publications.waset.org/abstracts/search?q=Delene%20Weber"> Delene Weber</a>, <a href="https://publications.waset.org/abstracts/search?q=Jacob%20Arnold"> Jacob Arnold</a>, <a href="https://publications.waset.org/abstracts/search?q=Guy%20M.%20Robinson"> Guy M. Robinson</a>, <a href="https://publications.waset.org/abstracts/search?q=Douglas%20K.%20Bardsley"> Douglas K. Bardsley</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Management strategies to reduce the risks to human life and property from wildfire are key contemporary concerns, with a growing literature exploring these issues from a social research perspective. Efforts range from narrowly focused examinations, such as comparing the level of community support for vegetation clearance with that of controlled burning, to broader considerations of what constitutes effective fire management policy and education campaigns. However, little analysis is available that integrates the social component of risk mitigation and the influence of educational materials with the biodiversity conservation strategies so often needed in fire-prone ecosystems found on the periphery of urban areas. Indeed many communities living on the fringe of Australian cities face major issues relating to an increased risk of wildfire events and a decline in local biodiversity. Inadequate policy and planning, and a lack of awareness or information, exacerbate this risk. This has brought forward an emerging governance challenge that requires the mitigation of wildfire risk while simultaneously supporting improved conservation practices in these urban-fringe areas. Focusing on the perceptions and experiences of residents of the Lower Eyre Peninsula in South Australia, this study analyses data collected from a series of semi-structured interviews with landholders (n=20) living in rural and urban-fringe areas surrounding the city of Port Lincoln, a city with a growing population and one that has faced a number of very large fires in recent years. In South Australia, new policies have assigned increased responsibility on individual landholders to manage their land and prepare themselves for a wildfire event, potentially to the detriment of the surrounding native vegetation. Our findings indicate the value of gaining a more nuanced understanding of the perceptions and behaviours of landholders living in areas of high fire risk, who often choose to live there in order to be close to the natural environment. Many interviewees demonstrated a high awareness of wildfire risk as a result of their past experience with fire, and the majority considered themselves to be well-prepared in the event of a future fire. Community interactions and educational programs were found to be effective in raising awareness of risk; however, negative trust relationships with government authorities and low exposure to information concerning biodiversity resulted in an overall misunderstanding of the relationship between risk mitigation and biodiversity protection. The study offers insights into how catastrophic fires are reframing perceptions of what constitutes effective vegetation management. It provides recommendations to assist with the development of education strategies that concurrently address wildfire management and biodiversity conservation, and contribute towards environmentally-informed and risk conscious governance. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=biodiversity%20conservation" title="biodiversity conservation">biodiversity conservation</a>, <a href="https://publications.waset.org/abstracts/search?q=risk" title=" risk"> risk</a>, <a href="https://publications.waset.org/abstracts/search?q=peri-urban%20planning" title=" peri-urban planning"> peri-urban planning</a>, <a href="https://publications.waset.org/abstracts/search?q=wildfire%20management" title=" wildfire management"> wildfire management</a> </p> <a href="https://publications.waset.org/abstracts/42317/wildfire-risk-and-biodiversity-management-understanding-perceptions-and-preparedness" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/42317.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">250</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6032</span> Generating Individualized Wildfire Risk Assessments Utilizing Multispectral Imagery and Geospatial Artificial Intelligence</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Gus%20Calderon">Gus Calderon</a>, <a href="https://publications.waset.org/abstracts/search?q=Richard%20McCreight"> Richard McCreight</a>, <a href="https://publications.waset.org/abstracts/search?q=Tammy%20Schwartz"> Tammy Schwartz</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Forensic analysis of community wildfire destruction in California has shown that reducing or removing flammable vegetation in proximity to buildings and structures is one of the most important wildfire defenses available to homeowners. State laws specify the requirements for homeowners to create and maintain defensible space around all structures. Unfortunately, this decades-long effort had limited success due to noncompliance and minimal enforcement. As a result, vulnerable communities continue to experience escalating human and economic costs along the wildland-urban interface (WUI). Quantifying vegetative fuels at both the community and parcel scale requires detailed imaging from an aircraft with remote sensing technology to reduce uncertainty. FireWatch has been delivering high spatial resolution (5” ground sample distance) wildfire hazard maps annually to the community of Rancho Santa Fe, CA, since 2019. FireWatch uses a multispectral imaging system mounted onboard an aircraft to create georeferenced orthomosaics and spectral vegetation index maps. Using proprietary algorithms, the vegetation type, condition, and proximity to structures are determined for 1,851 properties in the community. Secondary data processing combines object-based classification of vegetative fuels, assisted by machine learning, to prioritize mitigation strategies within the community. The remote sensing data for the 10 sq. mi. community is divided into parcels and sent to all homeowners in the form of defensible space maps and reports. Follow-up aerial surveys are performed annually using repeat station imaging of fixed GPS locations to address changes in defensible space, vegetation fuel cover, and condition over time. These maps and reports have increased wildfire awareness and mitigation efforts from 40% to over 85% among homeowners in Rancho Santa Fe. To assist homeowners fighting increasing insurance premiums and non-renewals, FireWatch has partnered with Black Swan Analytics, LLC, to leverage the multispectral imagery and increase homeowners’ understanding of wildfire risk drivers. For this study, a subsample of 100 parcels was selected to gain a comprehensive understanding of wildfire risk and the elements which can be mitigated. Geospatial data from FireWatch’s defensible space maps was combined with Black Swan’s patented approach using 39 other risk characteristics into a 4score Report. The 4score Report helps property owners understand risk sources and potential mitigation opportunities by assessing four categories of risk: Fuel sources, ignition sources, susceptibility to loss, and hazards to fire protection efforts (FISH). This study has shown that susceptibility to loss is the category residents and property owners must focus their efforts. The 4score Report also provides a tool to measure the impact of homeowner actions on risk levels over time. Resiliency is the only solution to breaking the cycle of community wildfire destruction and it starts with high-quality data and education. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=defensible%20space" title="defensible space">defensible space</a>, <a href="https://publications.waset.org/abstracts/search?q=geospatial%20data" title=" geospatial data"> geospatial data</a>, <a href="https://publications.waset.org/abstracts/search?q=multispectral%20imaging" title=" multispectral imaging"> multispectral imaging</a>, <a href="https://publications.waset.org/abstracts/search?q=Rancho%20Santa%20Fe" title=" Rancho Santa Fe"> Rancho Santa Fe</a>, <a href="https://publications.waset.org/abstracts/search?q=susceptibility%20to%20loss" title=" susceptibility to loss"> susceptibility to loss</a>, <a href="https://publications.waset.org/abstracts/search?q=wildfire%20risk." title=" wildfire risk."> wildfire risk.</a> </p> <a href="https://publications.waset.org/abstracts/155085/generating-individualized-wildfire-risk-assessments-utilizing-multispectral-imagery-and-geospatial-artificial-intelligence" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/155085.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">108</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6031</span> Exploring the Influence of Wind on Wildfire Behavior in China: A Data-Driven Study Using Machine Learning and Remote Sensing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rida%20Kanwal">Rida Kanwal</a>, <a href="https://publications.waset.org/abstracts/search?q=Wang%20Yuhui"> Wang Yuhui</a>, <a href="https://publications.waset.org/abstracts/search?q=Song%20Weiguo"> Song Weiguo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Wildfires are one of the most prominent threats to ecosystems, human health, and economic activities, with wind acting as a critical driving factor. This study combines machine learning (ML) and remote sensing (RS) to assess the effects of wind on wildfires in Chongqing Province from August 16-23, 2022. Landsat 8 satellite images were used to estimate the difference normalized burn ratio (dNBR), representing prefire and postfire vegetation conditions. Wind data was analyzed through geographic information system (GIS) mapping. Correlation analysis between wind speed and fire radiative power (FRP) revealed a significant relationship. An autoregressive integrated moving average (ARIMA) model was developed for wind forecasting, and linear regression was applied to determine the effect of wind speed on FRP. The results identified high wind speed as a key factor contributing to the surge in FRP. Wind-rose plots showed winds blowing to the northwest (NW), aligning with the wildfire spread. This model was further validated with data from other provinces across China. This study integrated ML, RS, and GIS to analyze wildfire behavior, providing effective strategies for prediction and management. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=wildfires" title="wildfires">wildfires</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=remote%20sensing" title=" remote sensing"> remote sensing</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20speed" title=" wind speed"> wind speed</a>, <a href="https://publications.waset.org/abstracts/search?q=GIS" title=" GIS"> GIS</a>, <a href="https://publications.waset.org/abstracts/search?q=wildfire%20behavior" title=" wildfire behavior"> wildfire behavior</a> </p> <a href="https://publications.waset.org/abstracts/192554/exploring-the-influence-of-wind-on-wildfire-behavior-in-china-a-data-driven-study-using-machine-learning-and-remote-sensing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/192554.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">20</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6030</span> A Systematic Map of the Research Trends in Wildfire Management in Mediterranean-Climate Regions </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Renata%20Martins%20Pacheco">Renata Martins Pacheco</a>, <a href="https://publications.waset.org/abstracts/search?q=Jo%C3%A3o%20Claro"> João Claro</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Wildfires are becoming an increasing concern worldwide, causing substantial social, economic, and environmental disruptions. This situation is especially relevant in Mediterranean-climate regions, present in all the five continents of the world, in which fire is not only a natural component of the environment but also perhaps one of the most important evolutionary forces. The rise in wildfire occurrences and their associated impacts suggests the need for identifying knowledge gaps and enhancing the basis of scientific evidence on how managers and policymakers may act effectively to address them. Considering that the main goal of a systematic map is to collate and catalog a body of evidence to describe the state of knowledge for a specific topic, it is a suitable approach to be used for this purpose. In this context, the aim of this study is to systematically map the research trends in wildfire management practices in Mediterranean-climate regions. A total of 201 wildfire management studies were analyzed and systematically mapped in terms of their: Year of publication; Place of study; Scientific outlet; Research area (Web of Science) or Research field (Scopus); Wildfire phase; Central research topic; Main objective of the study; Research methods; and Main conclusions or contributions. The results indicate that there is an increasing number of studies being developed on the topic (most from the last 10 years), but more than half of them are conducted in few Mediterranean countries (60% of the analyzed studies were conducted in Spain, Portugal, Greece, Italy or France), and more than 50% are focused on pre-fire issues, such as prevention and fuel management. In contrast, only 12% of the studies focused on “Economic modeling” or “Human factors and issues,” which suggests that the triple bottom line of the sustainability argument (social, environmental, and economic) is not being fully addressed by fire management research. More than one-fourth of the studies had their objective related to testing new approaches in fire or forest management, suggesting that new knowledge is being produced on the field. Nevertheless, the results indicate that most studies (about 84%) employed quantitative research methods, and only 3% of the studies used research methods that tackled social issues or addressed expert and practitioner’s knowledge. Perhaps this lack of multidisciplinary studies is one of the factors hindering more progress from being made in terms of reducing wildfire occurrences and their impacts. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=wildfire" title="wildfire">wildfire</a>, <a href="https://publications.waset.org/abstracts/search?q=Mediterranean-climate%20regions" title=" Mediterranean-climate regions"> Mediterranean-climate regions</a>, <a href="https://publications.waset.org/abstracts/search?q=management" title=" management"> management</a>, <a href="https://publications.waset.org/abstracts/search?q=policy" title=" policy"> policy</a> </p> <a href="https://publications.waset.org/abstracts/122431/a-systematic-map-of-the-research-trends-in-wildfire-management-in-mediterranean-climate-regions" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/122431.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">124</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6029</span> Wildfire-Related Debris-Flow and Flooding Using 2-D Hydrologic Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Cheong%20Hyeon%20Oh">Cheong Hyeon Oh</a>, <a href="https://publications.waset.org/abstracts/search?q=Dongho%20Nam"> Dongho Nam</a>, <a href="https://publications.waset.org/abstracts/search?q=Byungsik%20Kim"> Byungsik Kim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Due to the recent climate change, flood damage caused by local floods and typhoons has frequently occurred, the incidence rate and intensity of wildfires are greatly increased due to increased temperatures and changes in precipitation patterns. Wildfires cause primary damage, such as loss of forest resources, as well as secondary disasters, such as landslides, floods, and debris flow. In many countries around the world, damage and economic losses from secondary damage are occurring as well as the direct effects of forest fires. Therefore, in this study, the Rainfall-Runoff model(S-RAT) was used for the wildfire affected areas in Gangneung and Goseong, which occurred on April 2019, when the stability of vegetation and soil were destroyed by wildfires. Rainfall data from Typhoon Rusa were used in the S-RAT model, and flood discharge was calculated according to changes in land cover before and after wildfire damage. The results of the calculation showed that flood discharge increased significantly due to changes in land cover, as the increase in flood discharge increases the possibility of the occurrence of the debris flow and the extent of the damage, the debris flow height and range were calculated before and after forest fire using RAMMS. The analysis results showed that the height and extent of damage increased after wildfire, but the result value was underestimated due to the characteristics that using DEM and maximum flood discharge of the RAMMS model. This research was supported by a grant(2017-MOIS31-004) from Fundamental Technology Development Program for Extreme Disaster Response funded by Korean Ministry of Interior and Safety (MOIS). This paper work (or document) was financially supported by Ministry of the Interior and Safety as 'Human resoure development Project in Disaster management'. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=wildfire" title="wildfire">wildfire</a>, <a href="https://publications.waset.org/abstracts/search?q=debris%20flow" title=" debris flow"> debris flow</a>, <a href="https://publications.waset.org/abstracts/search?q=land%20cover" title=" land cover"> land cover</a>, <a href="https://publications.waset.org/abstracts/search?q=rainfall-runoff%20meodel%20S-RAT" title=" rainfall-runoff meodel S-RAT"> rainfall-runoff meodel S-RAT</a>, <a href="https://publications.waset.org/abstracts/search?q=RAMMS" title=" RAMMS"> RAMMS</a>, <a href="https://publications.waset.org/abstracts/search?q=height" title=" height"> height</a> </p> <a href="https://publications.waset.org/abstracts/113919/wildfire-related-debris-flow-and-flooding-using-2-d-hydrologic-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/113919.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">122</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6028</span> Preliminary WRF SFIRE Simulations over Croatia during the Split Wildfire in July 2017</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ivana%20%20%C4%8Cavlina%20Toma%C5%A1evi%C4%87">Ivana Čavlina Tomašević</a>, <a href="https://publications.waset.org/abstracts/search?q=Vi%C5%A1njica%20Vu%C4%8Deti%C4%87"> Višnjica Vučetić</a>, <a href="https://publications.waset.org/abstracts/search?q=Maja%20Teli%C5%A1man%20Prtenjak"> Maja Telišman Prtenjak</a>, <a href="https://publications.waset.org/abstracts/search?q=Barbara%20Male%C4%8Di%C4%87"> Barbara Malečić</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Split wildfire on the mid-Adriatic Coast in July 2017 is one of the most severe wildfires in Croatian history, given the size and unexpected fire behavior, and it is used in this research as a case study to run the Weather Research and Forecasting Spread Fire (WRF SFIRE) model. This coupled fire-atmosphere model was successfully run for the first time ever for one Croatian wildfire case. Verification of coupled simulations was possible by using the detailed reconstruction of the Split wildfire. Specifically, precise information on ignition time and location, together with mapped fire progressions and spotting within the first 30 hours of the wildfire, was used for both – to initialize simulations and to evaluate the model’s ability to simulate fire’s propagation and final fire scar. The preliminary simulations were obtained using high-resolution vegetation and topography data for the fire area, additionally interpolated to fire grid spacing at 33.3 m. The results demonstrated that the WRF SFIRE model has the ability to work with real data from Croatia and produce adequate results for forecasting fire spread. As the model in its setup has the ability to include and exclude the energy fluxes between the fire and the atmosphere, this was used to investigate possible fire-atmosphere interactions during the Split wildfire. Finally, successfully coupled simulations provided the first numerical evidence that a wildfire from the Adriatic coast region can modify the dynamical structure of the surrounding atmosphere, which agrees with observations from fire grounds. This study has demonstrated that the WRF SFIRE model has the potential for operational application in Croatia with more accurate fire predictions in the future, which could be accomplished by inserting the higher-resolution input data into the model without interpolation. Possible uses for fire management in Croatia include prediction of fire spread and intensity that may vary under changing weather conditions, available fuels and topography, planning effective and safe deployment of ground and aerial firefighting forces, preventing wildland-urban interface fires, effective planning of evacuation routes etc. In addition, the WRF SFIRE model results from this research demonstrated that the model is important for fire weather research and education purposes in order to better understand this hazardous phenomenon that occurs in Croatia. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=meteorology" title="meteorology">meteorology</a>, <a href="https://publications.waset.org/abstracts/search?q=agrometeorology" title=" agrometeorology"> agrometeorology</a>, <a href="https://publications.waset.org/abstracts/search?q=fire%20weather" title=" fire weather"> fire weather</a>, <a href="https://publications.waset.org/abstracts/search?q=wildfires" title=" wildfires"> wildfires</a>, <a href="https://publications.waset.org/abstracts/search?q=couple%20fire-atmosphere%20model" title=" couple fire-atmosphere model"> couple fire-atmosphere model</a> </p> <a href="https://publications.waset.org/abstracts/162421/preliminary-wrf-sfire-simulations-over-croatia-during-the-split-wildfire-in-july-2017" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/162421.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">89</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6027</span> Volunteered Geographic Information Coupled with Wildfire Fire Progression Maps: A Spatial and Temporal Tool for Incident Storytelling</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Cassandra%20Hansen">Cassandra Hansen</a>, <a href="https://publications.waset.org/abstracts/search?q=Paul%20Doherty"> Paul Doherty</a>, <a href="https://publications.waset.org/abstracts/search?q=Chris%20Ferner"> Chris Ferner</a>, <a href="https://publications.waset.org/abstracts/search?q=German%20Whitley"> German Whitley</a>, <a href="https://publications.waset.org/abstracts/search?q=Holly%20Torpey"> Holly Torpey</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Wildfire is a natural and inevitable occurrence, yet changing climatic conditions have increased the severity, frequency, and risk to human populations in the wildland/urban interface (WUI) of the Western United States. Rapid dissemination of accurate wildfire information is critical to both the Incident Management Team (IMT) and the affected community. With the advent of increasingly sophisticated information systems, GIS can now be used as a web platform for sharing geographic information in new and innovative ways, such as virtual story map applications. Crowdsourced information can be extraordinarily useful when coupled with authoritative information. Information abounds in the form of social media, emergency alerts, radio, and news outlets, yet many of these resources lack a spatial component when first distributed. In this study, we describe how twenty-eight volunteer GIS professionals across nine Geographic Area Coordination Centers (GACC) sourced, curated, and distributed Volunteered Geographic Information (VGI) from authoritative social media accounts focused on disseminating information about wildfires and public safety. The combination of fire progression maps with VGI incident information helps answer three critical questions about an incident, such as: where the first started. How and why the fire behaved in an extreme manner and how we can learn from the fire incident's story to respond and prepare for future fires in this area. By adding a spatial component to that shared information, this team has been able to visualize shared information about wildfire starts in an interactive map that answers three critical questions in a more intuitive way. Additionally, long-term social and technical impacts on communities are examined in relation to situational awareness of the disaster through map layers and agency links, the number of views in a particular region of a disaster, community involvement and sharing of this critical resource. Combined with a GIS platform and disaster VGI applications, this workflow and information become invaluable to communities within the WUI and bring spatial awareness for disaster preparedness, response, mitigation, and recovery. This study highlights progression maps as the ultimate storytelling mechanism through incident case studies and demonstrates the impact of VGI and sophisticated applied cartographic methodology make this an indispensable resource for authoritative information sharing. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=storytelling" title="storytelling">storytelling</a>, <a href="https://publications.waset.org/abstracts/search?q=wildfire%20progression%20maps" title=" wildfire progression maps"> wildfire progression maps</a>, <a href="https://publications.waset.org/abstracts/search?q=volunteered%20geographic%20information" title=" volunteered geographic information"> volunteered geographic information</a>, <a href="https://publications.waset.org/abstracts/search?q=spatial%20and%20temporal" title=" spatial and temporal"> spatial and temporal</a> </p> <a href="https://publications.waset.org/abstracts/140122/volunteered-geographic-information-coupled-with-wildfire-fire-progression-maps-a-spatial-and-temporal-tool-for-incident-storytelling" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/140122.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">176</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6026</span> Assessing the Legacy Effects of Wildfire on Eucalypt Canopy Structure of South Eastern Australia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yogendra%20K.%20Karna">Yogendra K. Karna</a>, <a href="https://publications.waset.org/abstracts/search?q=Lauren%20T.%20Bennett"> Lauren T. Bennett </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Fire-tolerant eucalypt forests are one of the major forest ecosystems of south-eastern Australia and thought to be highly resistant to frequent high severity wildfires. However, the impact of different severity wildfires on the canopy structure of fire-tolerant forest type is under-studied, and there are significant knowledge gaps in relation to the assessment of tree and stand level canopy structural dynamics and recovery after fire. Assessment of canopy structure is a complex task involving accurate measurements of the horizontal and vertical arrangement of the canopy in space and time. This study examined the utility of multitemporal, small-footprint lidar data to describe the changes in the horizontal and vertical canopy structure of fire-tolerant eucalypt forests seven years after wildfire of different severities from the tree to stand level. Extensive ground measurements were carried out in four severity classes to describe and validate canopy cover and height metrics as they change after wildfire. Several metrics such as crown height and width, crown base height and clumpiness of crown were assessed at tree and stand level using several individual tree top detection and measurement algorithm. Persistent effects of high severity fire 8 years after both on tree crowns and stand canopy were observed. High severity fire increased the crown depth but decreased the crown projective cover leading to more open canopy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=canopy%20gaps" title="canopy gaps">canopy gaps</a>, <a href="https://publications.waset.org/abstracts/search?q=canopy%20structure" title=" canopy structure"> canopy structure</a>, <a href="https://publications.waset.org/abstracts/search?q=crown%20architecture" title=" crown architecture"> crown architecture</a>, <a href="https://publications.waset.org/abstracts/search?q=crown%20projective%20cover" title=" crown projective cover"> crown projective cover</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-temporal%20lidar" title=" multi-temporal lidar"> multi-temporal lidar</a>, <a href="https://publications.waset.org/abstracts/search?q=wildfire%20severity" title=" wildfire severity"> wildfire severity</a> </p> <a href="https://publications.waset.org/abstracts/94022/assessing-the-legacy-effects-of-wildfire-on-eucalypt-canopy-structure-of-south-eastern-australia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/94022.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">175</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6025</span> Impacts on Atmospheric Mercury from Changes in Climate, Land Use, Land Cover, and Wildfires</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shiliang%20Wu">Shiliang Wu</a>, <a href="https://publications.waset.org/abstracts/search?q=Huanxin%20Zhang"> Huanxin Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Aditya%20Kumar"> Aditya Kumar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> There have been increasing concerns on atmospheric mercury as a toxic and bioaccumulative pollutant in the global environment. Global change, including changes in climate change, land use, land cover and wildfires activities can all have significant impacts on atmospheric mercury. In this study, we use a global chemical transport model (GEOS-Chem) to examine the potential impacts from global change on atmospheric mercury. All of these factors in the context of global change are found to have significant impacts on the long-term evolution of atmospheric mercury and can substantially alter the global source-receptor relationships for mercury. We also estimate the global Hg emissions from wildfires for present-day and the potential impacts from the 2000-2050 changes in climate, land use and land cover and Hg anthropogenic emissions by combining statistical analysis with global data on vegetation type and coverage as well as fire activities. Present global Hg wildfire emissions are estimated to be 612 Mg year-1. Africa is the dominant source region (43.8% of global emissions), followed by Eurasia (31%) and South America (16.6%). We find significant perturbations to wildfire emissions of Hg in the context of global change, driven by the projected changes in climate, land use and land cover and Hg anthropogenic emissions. 2000-2050 climate change could increase Hg emissions by 14% globally. Projected changes in land use by 2050 could decrease the global Hg emissions from wildfires by 13% mainly driven by a decline in African emissions due to significant agricultural land expansion. Future land cover changes could lead to significant increases in Hg emissions over some regions (+32% North America, +14% Africa, +13% Eurasia). Potential enrichment of terrestrial ecosystems in 2050 in response to changes in Hg anthropogenic emissions could increase Hg wildfire emissions both globally (+28%) and regionally. Our results indicate that the future evolution of climate, land use and land cover and Hg anthropogenic emissions are all important factors affecting Hg wildfire emissions in the coming decades. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=climate%20change" title="climate change">climate change</a>, <a href="https://publications.waset.org/abstracts/search?q=land%20use" title=" land use"> land use</a>, <a href="https://publications.waset.org/abstracts/search?q=land%20cover" title=" land cover"> land cover</a>, <a href="https://publications.waset.org/abstracts/search?q=wildfires" title=" wildfires"> wildfires</a> </p> <a href="https://publications.waset.org/abstracts/81118/impacts-on-atmospheric-mercury-from-changes-in-climate-land-use-land-cover-and-wildfires" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/81118.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">326</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6024</span> Application of Machine Learning on Google Earth Engine for Forest Fire Severity, Burned Area Mapping and Land Surface Temperature Analysis: Rajasthan, India</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alisha%20Sinha">Alisha Sinha</a>, <a href="https://publications.waset.org/abstracts/search?q=Laxmi%20Kant%20Sharma"> Laxmi Kant Sharma</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Forest fires are a recurring issue in many parts of the world, including India. These fires can have various causes, including human activities (such as agricultural burning, campfires, or discarded cigarettes) and natural factors (such as lightning). This study presents a comprehensive and advanced methodology for assessing wildfire susceptibility by integrating diverse environmental variables and leveraging cutting-edge machine learning techniques across Rajasthan, India. The primary goal of the study is to utilize Google Earth Engine to compare locations in Sariska National Park, Rajasthan (India), before and after forest fires. High-resolution satellite data were used to assess the amount and types of changes caused by forest fires. The present study meticulously analyzes various environmental variables, i.e., slope orientation, elevation, normalized difference vegetation index (NDVI), drainage density, precipitation, and temperature, to understand landscape characteristics and assess wildfire susceptibility. In addition, a sophisticated random forest regression model is used to predict land surface temperature based on a set of environmental parameters. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=wildfire%20susceptibility%20mapping" title="wildfire susceptibility mapping">wildfire susceptibility mapping</a>, <a href="https://publications.waset.org/abstracts/search?q=LST" title=" LST"> LST</a>, <a href="https://publications.waset.org/abstracts/search?q=random%20forest" title=" random forest"> random forest</a>, <a href="https://publications.waset.org/abstracts/search?q=GEE" title=" GEE"> GEE</a>, <a href="https://publications.waset.org/abstracts/search?q=MODIS" title=" MODIS"> MODIS</a>, <a href="https://publications.waset.org/abstracts/search?q=climatic%20parameters" title=" climatic parameters"> climatic parameters</a> </p> <a href="https://publications.waset.org/abstracts/191316/application-of-machine-learning-on-google-earth-engine-for-forest-fire-severity-burned-area-mapping-and-land-surface-temperature-analysis-rajasthan-india" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/191316.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">22</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6023</span> Instance Segmentation of Wildfire Smoke Plumes using Mask-RCNN</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jamison%20Duckworth">Jamison Duckworth</a>, <a href="https://publications.waset.org/abstracts/search?q=Shankarachary%20Ragi"> Shankarachary Ragi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Detection and segmentation of wildfire smoke plumes from remote sensing imagery are being pursued as a solution for early fire detection and response. Smoke plume detection can be automated and made robust by the application of artificial intelligence methods. Specifically, in this study, the deep learning approach Mask Region-based Convolutional Neural Network (RCNN) is being proposed to learn smoke patterns across different spectral bands. This method is proposed to separate the smoke regions from the background and return masks placed over the smoke plumes. Multispectral data was acquired using NASA’s Earthdata and WorldView and services and satellite imagery. Due to the use of multispectral bands along with the three visual bands, we show that Mask R-CNN can be applied to distinguish smoke plumes from clouds and other landscape features that resemble smoke. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=deep%20learning" title="deep learning">deep learning</a>, <a href="https://publications.waset.org/abstracts/search?q=mask-RCNN" title=" mask-RCNN"> mask-RCNN</a>, <a href="https://publications.waset.org/abstracts/search?q=smoke%20plumes" title=" smoke plumes"> smoke plumes</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20bands" title=" spectral bands"> spectral bands</a> </p> <a href="https://publications.waset.org/abstracts/150196/instance-segmentation-of-wildfire-smoke-plumes-using-mask-rcnn" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/150196.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">127</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6022</span> A Comprehensive Study of Spread Models of Wildland Fires</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Manavjit%20Singh%20Dhindsa">Manavjit Singh Dhindsa</a>, <a href="https://publications.waset.org/abstracts/search?q=Ursula%20Das"> Ursula Das</a>, <a href="https://publications.waset.org/abstracts/search?q=Kshirasagar%20Naik"> Kshirasagar Naik</a>, <a href="https://publications.waset.org/abstracts/search?q=Marzia%20Zaman"> Marzia Zaman</a>, <a href="https://publications.waset.org/abstracts/search?q=Richard%20Purcell"> Richard Purcell</a>, <a href="https://publications.waset.org/abstracts/search?q=Srinivas%20Sampalli"> Srinivas Sampalli</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdul%20Mutakabbir"> Abdul Mutakabbir</a>, <a href="https://publications.waset.org/abstracts/search?q=Chung-Horng%20Lung"> Chung-Horng Lung</a>, <a href="https://publications.waset.org/abstracts/search?q=Thambirajah%20Ravichandran"> Thambirajah Ravichandran</a> </p> <p class="card-text"><strong>Abstract:</strong></p> These days, wildland fires, also known as forest fires, are more prevalent than ever. Wildfires have major repercussions that affect ecosystems, communities, and the environment in several ways. Wildfires lead to habitat destruction and biodiversity loss, affecting ecosystems and causing soil erosion. They also contribute to poor air quality by releasing smoke and pollutants that pose health risks, especially for individuals with respiratory conditions. Wildfires can damage infrastructure, disrupt communities, and cause economic losses. The economic impact of firefighting efforts, combined with their direct effects on forestry and agriculture, causes significant financial difficulties for the areas impacted. This research explores different forest fire spread models and presents a comprehensive review of various techniques and methodologies used in the field. A forest fire spread model is a computational or mathematical representation that is used to simulate and predict the behavior of a forest fire. By applying scientific concepts and data from empirical studies, these models attempt to capture the intricate dynamics of how a fire spreads, taking into consideration a variety of factors like weather patterns, topography, fuel types, and environmental conditions. These models assist authorities in understanding and forecasting the potential trajectory and intensity of a wildfire. Emphasizing the need for a comprehensive understanding of wildfire dynamics, this research explores the approaches, assumptions, and findings derived from various models. By using a comparison approach, a critical analysis is provided by identifying patterns, strengths, and weaknesses among these models. The purpose of the survey is to further wildfire research and management techniques. Decision-makers, researchers, and practitioners can benefit from the useful insights that are provided by synthesizing established information. Fire spread models provide insights into potential fire behavior, facilitating authorities to make informed decisions about evacuation activities, allocating resources for fire-fighting efforts, and planning for preventive actions. Wildfire spread models are also useful in post-wildfire mitigation strategies as they help in assessing the fire's severity, determining high-risk regions for post-fire dangers, and forecasting soil erosion trends. The analysis highlights the importance of customized modeling approaches for various circumstances and promotes our understanding of the way forest fires spread. Some of the known models in this field are Rothermel’s wildland fuel model, FARSITE, WRF-SFIRE, FIRETEC, FlamMap, FSPro, cellular automata model, and others. The key characteristics that these models consider include weather (includes factors such as wind speed and direction), topography (includes factors like landscape elevation), and fuel availability (includes factors like types of vegetation) among other factors. The models discussed are physics-based, data-driven, or hybrid models, also utilizing ML techniques like attention-based neural networks to enhance the performance of the model. In order to lessen the destructive effects of forest fires, this initiative aims to promote the development of more precise prediction tools and effective management techniques. The survey expands its scope to address the practical needs of numerous stakeholders. Access to enhanced early warning systems enables decision-makers to take prompt action. Emergency responders benefit from improved resource allocation strategies, strengthening the efficacy of firefighting efforts. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=artificial%20intelligence" title="artificial intelligence">artificial intelligence</a>, <a href="https://publications.waset.org/abstracts/search?q=deep%20learning" title=" deep learning"> deep learning</a>, <a href="https://publications.waset.org/abstracts/search?q=forest%20fire%20management" title=" forest fire management"> forest fire management</a>, <a href="https://publications.waset.org/abstracts/search?q=fire%20risk%20assessment" title=" fire risk assessment"> fire risk assessment</a>, <a href="https://publications.waset.org/abstracts/search?q=fire%20simulation" title=" fire simulation"> fire simulation</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=remote%20sensing" title=" remote sensing"> remote sensing</a>, <a href="https://publications.waset.org/abstracts/search?q=wildfire%20modeling" title=" wildfire modeling"> wildfire modeling</a> </p> <a href="https://publications.waset.org/abstracts/176767/a-comprehensive-study-of-spread-models-of-wildland-fires" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/176767.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">81</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6021</span> Risk Measure from Investment in Finance by Value at Risk</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammed%20El-Arbi%20Khalfallah">Mohammed El-Arbi Khalfallah</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Lakhdar%20Hadji"> Mohamed Lakhdar Hadji</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Managing and controlling risk is a topic research in the world of finance. Before a risky situation, the stakeholders need to do comparison according to the positions and actions, and financial institutions must take measures of a particular market risk and credit. In this work, we study a model of risk measure in finance: Value at Risk (VaR), which is a new tool for measuring an entity's exposure risk. We explain the concept of value at risk, your average, tail, and describe the three methods for computing: Parametric method, Historical method, and numerical method of Monte Carlo. Finally, we briefly describe advantages and disadvantages of the three methods for computing value at risk. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=average%20value%20at%20risk" title="average value at risk">average value at risk</a>, <a href="https://publications.waset.org/abstracts/search?q=conditional%20value%20at%20risk" title=" conditional value at risk"> conditional value at risk</a>, <a href="https://publications.waset.org/abstracts/search?q=tail%20value%20at%20risk" title=" tail value at risk"> tail value at risk</a>, <a href="https://publications.waset.org/abstracts/search?q=value%20at%20risk" title=" value at risk"> value at risk</a> </p> <a href="https://publications.waset.org/abstracts/61669/risk-measure-from-investment-in-finance-by-value-at-risk" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/61669.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">441</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6020</span> Insect Outbreaks, Harvesting and Wildfire in Forests: Mathematical Models for Coupling Disturbances</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20C.%20A.%20Leite">M. C. A. Leite</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20Chen-Charpentier"> B. Chen-Charpentier</a>, <a href="https://publications.waset.org/abstracts/search?q=F.%20Agusto"> F. Agusto</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A long-term goal of sustainable forest management is a relatively stable source of wood and a stable forest age-class structure has become the goal of many forest management practices. In the absence of disturbances, this forest management goal could easily be achieved. However, in the face of recurring insect outbreaks and other disruptive processes forest planning becomes more difficult, requiring knowledge of the effects on the forest of a wide variety of environmental factors (e.g., habitat heterogeneity, fire size and frequency, harvesting, insect outbreaks, and age distributions). The association between distinct forest disturbances and the potential effect on forest dynamics is a complex matter, particularly when evaluated over time and at large scale, and is not well understood. However, gaining knowledge in this area is crucial for a sustainable forest management. Mathematical modeling is a tool that can be used to broader the understanding in this area. In this talk we will introduce mathematical models formulation incorporating the effect of insect outbreaks either as a single disturbance in the forest population dynamics or coupled with other disturbances: either wildfire or harvesting. The results and ecological insights will be discussed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=age-structured%20forest%20population" title="age-structured forest population">age-structured forest population</a>, <a href="https://publications.waset.org/abstracts/search?q=disturbances%20interaction" title=" disturbances interaction"> disturbances interaction</a>, <a href="https://publications.waset.org/abstracts/search?q=harvesting%20insects%20outbreak%20dynamics" title=" harvesting insects outbreak dynamics"> harvesting insects outbreak dynamics</a>, <a href="https://publications.waset.org/abstracts/search?q=mathematical%0D%0Amodeling" title=" mathematical modeling"> mathematical modeling</a> </p> <a href="https://publications.waset.org/abstracts/16948/insect-outbreaks-harvesting-and-wildfire-in-forests-mathematical-models-for-coupling-disturbances" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/16948.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">525</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6019</span> Ecosystem Post-Wildfires Effects of Thasos Island</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=George%20D.%20Ranis">George D. Ranis</a>, <a href="https://publications.waset.org/abstracts/search?q=Valasia%20Iakovoglou"> Valasia Iakovoglou</a>, <a href="https://publications.waset.org/abstracts/search?q=George%20N.%20Zaimes"> George N. Zaimes</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Fires are one of the main types of disturbances that shape ecosystems in the Mediterranean region. However nowadays, climate alterations towards higher temperature regimes results on the increased levels of the intensity, frequency and the spread of fires inducing obstacles for the natural regeneration. Thasos Island is one of the Greek islands that have experienced those problems. Since 1984, a series of wildfires led to the reduction of forest cover from 61.6% to almost 20%. The negative impacts were devastating in many different aspects for the island. The absence of plant cover, post-wildfire precipitation and steep slopes were the major factors that induced severe soil erosion and intense flooding events. That also resulted to serious economic problems to the local communities and the ability of the burnt areas to regenerate naturally. Despite the substantial amount of published work regarding Thasos wildfires, there is no information related to post-wildfire effects on the hydrology and soil erosion. More research related to post-fire effects should help to an overall assessment of the negative impacts of wildfires on land degradation through processes such as soil erosion and flooding. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=erosion" title="erosion">erosion</a>, <a href="https://publications.waset.org/abstracts/search?q=land%20degradation" title=" land degradation"> land degradation</a>, <a href="https://publications.waset.org/abstracts/search?q=Mediterranean%20islands" title=" Mediterranean islands"> Mediterranean islands</a>, <a href="https://publications.waset.org/abstracts/search?q=regeneration" title=" regeneration"> regeneration</a>, <a href="https://publications.waset.org/abstracts/search?q=Thasos" title=" Thasos"> Thasos</a>, <a href="https://publications.waset.org/abstracts/search?q=wildfires" title=" wildfires"> wildfires</a> </p> <a href="https://publications.waset.org/abstracts/39531/ecosystem-post-wildfires-effects-of-thasos-island" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/39531.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">325</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6018</span> Multi-Spectral Deep Learning Models for Forest Fire Detection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Smitha%20Haridasan">Smitha Haridasan</a>, <a href="https://publications.waset.org/abstracts/search?q=Zelalem%20Demissie"> Zelalem Demissie</a>, <a href="https://publications.waset.org/abstracts/search?q=Atri%20Dutta"> Atri Dutta</a>, <a href="https://publications.waset.org/abstracts/search?q=Ajita%20Rattani"> Ajita Rattani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Aided by the wind, all it takes is one ember and a few minutes to create a wildfire. Wildfires are growing in frequency and size due to climate change. Wildfires and its consequences are one of the major environmental concerns. Every year, millions of hectares of forests are destroyed over the world, causing mass destruction and human casualties. Thus early detection of wildfire becomes a critical component to mitigate this threat. Many computer vision-based techniques have been proposed for the early detection of forest fire using video surveillance. Several computer vision-based methods have been proposed to predict and detect forest fires at various spectrums, namely, RGB, HSV, and YCbCr. The aim of this paper is to propose a multi-spectral deep learning model that combines information from different spectrums at intermediate layers for accurate fire detection. A heterogeneous dataset assembled from publicly available datasets is used for model training and evaluation in this study. The experimental results show that multi-spectral deep learning models could obtain an improvement of about 4.68 % over those based on a single spectrum for fire detection. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=deep%20learning" title="deep learning">deep learning</a>, <a href="https://publications.waset.org/abstracts/search?q=forest%20fire%20detection" title=" forest fire detection"> forest fire detection</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-spectral%20learning" title=" multi-spectral learning"> multi-spectral learning</a>, <a href="https://publications.waset.org/abstracts/search?q=natural%20hazard%20detection" title=" natural hazard detection"> natural hazard detection</a> </p> <a href="https://publications.waset.org/abstracts/146865/multi-spectral-deep-learning-models-for-forest-fire-detection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/146865.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">241</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6017</span> Model of MSD Risk Assessment at Workplace</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=K.%20Sekulov%C3%A1">K. Sekulová</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20%C5%A0imon"> M. Šimon</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This article focuses on upper-extremity musculoskeletal disorders risk assessment model at workplace. In this model are used risk factors that are responsible for musculoskeletal system damage. Based on statistic calculations the model is able to define what risk of MSD threatens workers who are under risk factors. The model is also able to say how MSD risk would decrease if these risk factors are eliminated. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ergonomics" title="ergonomics">ergonomics</a>, <a href="https://publications.waset.org/abstracts/search?q=musculoskeletal%20disorders" title=" musculoskeletal disorders"> musculoskeletal disorders</a>, <a href="https://publications.waset.org/abstracts/search?q=occupational%20diseases" title=" occupational diseases"> occupational diseases</a>, <a href="https://publications.waset.org/abstracts/search?q=risk%20factors" title=" risk factors"> risk factors</a> </p> <a href="https://publications.waset.org/abstracts/13024/model-of-msd-risk-assessment-at-workplace" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13024.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">551</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6016</span> Relationship Between Wildfire and Plant Species in Arasbaran Forest, Iran</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zhila%20Hemati">Zhila Hemati</a>, <a href="https://publications.waset.org/abstracts/search?q=Seyed%20Sajjad%20Hosseni"> Seyed Sajjad Hosseni</a>, <a href="https://publications.waset.org/abstracts/search?q=Sohrab%20Zamzami"> Sohrab Zamzami</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In nature, forests serve a multitude of functions. They stabilize and nourish soil, store carbon, clean the air and water, and support biodiverse ecosystems. A natural disaster that can affect forests and ecosystems locally or globally is wildfires. Iran experiences annual forest fires that affect roughly 6000 hectares, with the Arasbaran forest being the most affected. These fires may be generated unnaturally by human activity in the forests, or they could occur naturally as a result of climate change. These days, wildfires pose a major natural risk. Wildfires significantly reduce the amount of property and human life in ecosystems globally. Concerns regarding the immediate and longterm effects have been raised by the rise in fire activity in various Iranian regions in recent decades. Natural ecosystem abundance, quality, and health will all be impacted by pasture and forest fires. Monitoring is the first line of defense against and control for forest fires. To determine the spatial-temporal variations of these occurrences in the vegetation regions of Arasbaran, this study was carried out to estimate the areas affected by fires. The findings indicated that July through September, which spans over 130000 hectares, is when fires in Arasbaran's vegetation areas occur to their greatest extent. A significant portion of the nation's forests caught fire in 2024, particularly in the northwest of the Arasbaran vegetation area. On the other hand, January through March sees the least number of fire locations in the Arasbaran vegetation areas. The Arasbaran forest experiences its greatest number of forest fires during the hot, dry months of the year. As a result, the linear association between the burned and active fire regions in the Arasbaran forest indicates a substantial relationship between species abundance and plant species. This link demonstrates that some of the active forest fire centers are the burned regions in Arasbaran's vegetation areas. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=wildfire" title="wildfire">wildfire</a>, <a href="https://publications.waset.org/abstracts/search?q=vegetation" title=" vegetation"> vegetation</a>, <a href="https://publications.waset.org/abstracts/search?q=plant%20species" title=" plant species"> plant species</a>, <a href="https://publications.waset.org/abstracts/search?q=forest" title=" forest"> forest</a> </p> <a href="https://publications.waset.org/abstracts/185188/relationship-between-wildfire-and-plant-species-in-arasbaran-forest-iran" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/185188.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">44</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6015</span> Characterization of Forest Fire Fuel in Shivalik Himalayas Using Hyperspectral Remote Sensing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Neha%20Devi">Neha Devi</a>, <a href="https://publications.waset.org/abstracts/search?q=P.%20K.%20Joshi"> P. K. Joshi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Fire fuel map is one of the most critical factors for planning and managing the fire hazard and risk. One of the most significant forms of global disturbance, impacting community dynamics, biogeochemical cycles and local and regional climate across a wide range of ecosystems ranging from boreal forests to tropical rainforest is wildfire Assessment of fire danger is a function of forest type, fuelwood stock volume, moisture content, degree of senescence and fire management strategy adopted in the ground. Remote sensing has potential of reduction the uncertainty in mapping fuels. Hyperspectral remote sensing is emerging to be a very promising technology for wildfire fuels characterization. Fine spectral information also facilitates mapping of biophysical and chemical information that is directly related to the quality of forest fire fuels including above ground live biomass, canopy moisture, etc. We used Hyperion imagery acquired in February, 2016 and analysed four fuel characteristics using Hyperion sensor data on-board EO-1 satellite, acquired over the Shiwalik Himalayas covering the area of Champawat, Uttarakhand state. The main objective of this study was to present an overview of methodologies for mapping fuel properties using hyperspectral remote sensing data. Fuel characteristics analysed include fuel biomass, fuel moisture, and fuel condition and fuel type. Fuel moisture and fuel biomass were assessed through the expression of the liquid water bands. Fuel condition and type was assessed using green vegetation, non-photosynthetic vegetation and soil as Endmember for spectral mixture analysis. Linear Spectral Unmixing, a partial spectral unmixing algorithm, was used to identify the spectral abundance of green vegetation, non-photosynthetic vegetation and soil. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=forest%20fire%20fuel" title="forest fire fuel">forest fire fuel</a>, <a href="https://publications.waset.org/abstracts/search?q=Hyperion" title=" Hyperion"> Hyperion</a>, <a href="https://publications.waset.org/abstracts/search?q=hyperspectral" title=" hyperspectral"> hyperspectral</a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20spectral%20unmixing" title=" linear spectral unmixing"> linear spectral unmixing</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20mixture%20analysis" title=" spectral mixture analysis"> spectral mixture analysis</a> </p> <a href="https://publications.waset.org/abstracts/102309/characterization-of-forest-fire-fuel-in-shivalik-himalayas-using-hyperspectral-remote-sensing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/102309.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">165</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6014</span> Reduce the Impact of Wildfires by Identifying Them Early from Space and Sending Location Directly to Closest First Responders</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Gregory%20Sullivan">Gregory Sullivan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The evolution of global warming has escalated the number and complexity of forest fires around the world. As an example, the United States and Brazil combined generated more than 30,000 forest fires last year. The impact to our environment, structures and individuals is incalculable. The world has learned to try to take this in stride, trying multiple ways to contain fires. Some countries are trying to use cameras in limited areas. There are discussions of using hundreds of low earth orbit satellites and linking them together, and, interfacing them through ground networks. These are all truly noble attempts to defeat the forest fire phenomenon. But there is a better, simpler answer. A bigger piece of the solutions puzzle is to see the fires while they are small, soon after initiation. The approach is to see the fires while they are very small and report their location (latitude and longitude) to local first responders. This is done by placing a sensor at geostationary orbit (GEO: 26,000 miles above the earth). By placing this small satellite in GEO, we can “stare” at the earth, and sense temperature changes. We do not “see” fires, but “measure” temperature changes. This has already been demonstrated on an experimental scale. Fires were seen at close to initiation, and info forwarded to first responders. it were the first to identify the fires 7 out of 8 times. The goal is to have a small independent satellite at GEO orbit focused only on forest fire initiation. Thus, with one small satellite, focused only on forest fire initiation, we hope to greatly decrease the impact to persons, property and the environment. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=space%20detection" title="space detection">space detection</a>, <a href="https://publications.waset.org/abstracts/search?q=wildfire%20early%20warning" title=" wildfire early warning"> wildfire early warning</a>, <a href="https://publications.waset.org/abstracts/search?q=demonstration%20wildfire%20detection%20and%20action%20from%20space" title=" demonstration wildfire detection and action from space"> demonstration wildfire detection and action from space</a>, <a href="https://publications.waset.org/abstracts/search?q=space%20detection%20to%20first%20responders" title=" space detection to first responders"> space detection to first responders</a> </p> <a href="https://publications.waset.org/abstracts/179337/reduce-the-impact-of-wildfires-by-identifying-them-early-from-space-and-sending-location-directly-to-closest-first-responders" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/179337.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">70</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6013</span> UEMSD Risk Identification: Case Study</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=K.%20Sekulov%C3%A1">K. Sekulová</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20%C5%A0imon"> M. Šimon</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The article demonstrates on a case study how it is possible to identify MSD risk. It is based on a dissertation risk identification model of occupational diseases formation in relation to the work activity that determines what risk can endanger workers who are exposed to the specific risk factors. It is evaluated based on statistical calculations. These risk factors are main cause of upper-extremities musculoskeletal disorders. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=case%20study" title="case study">case study</a>, <a href="https://publications.waset.org/abstracts/search?q=upper-extremity%20musculoskeletal%20disorders" title=" upper-extremity musculoskeletal disorders"> upper-extremity musculoskeletal disorders</a>, <a href="https://publications.waset.org/abstracts/search?q=ergonomics" title=" ergonomics"> ergonomics</a>, <a href="https://publications.waset.org/abstracts/search?q=risk%20identification" title=" risk identification"> risk identification</a> </p> <a href="https://publications.waset.org/abstracts/14518/uemsd-risk-identification-case-study" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14518.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">500</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6012</span> The Response of Mammal Populations to Abrupt Changes in Fire Regimes in Montane Landscapes of South-Eastern Australia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jeremy%20Johnson">Jeremy Johnson</a>, <a href="https://publications.waset.org/abstracts/search?q=Craig%20Nitschke"> Craig Nitschke</a>, <a href="https://publications.waset.org/abstracts/search?q=Luke%20Kelly"> Luke Kelly</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Fire regimes, climate and topographic gradients interact to influence ecosystem structure and function across fire-prone, montane landscapes worldwide. Biota have developed a range of adaptations to historic fire regime thresholds, which allow them to persist in these environments. In south-eastern Australia, a signal of fire regime changes is emerging across these landscapes, and anthropogenic climate change is likely to be one of the main drivers of an increase in burnt area and more frequent wildfire over the last 25 years. This shift has the potential to modify vegetation structure and composition at broad scales, which may lead to landscape patterns to which biota are not adapted, increasing the likelihood of local extirpation of some mammal species. This study aimed to address concerns related to the influence of abrupt changes in fire regimes on mammal populations in montane landscapes. It first examined the impact of climate, topography, and vegetation on fire patterns and then explored the consequences of these changes on mammal populations and their habitats. Field studies were undertaken across diverse vegetation, fire severity and fire frequency gradients, utilising camera trapping and passive acoustic monitoring methodologies and the collection of fine-scale vegetation data. Results show that drought is a primary contributor to fire regime shifts at the landscape scale, while topographic factors have a variable influence on wildfire occurrence at finer scales. Frequent, high severity wildfire influenced forest structure and composition at broad spatial scales, and at fine scales, it reduced occurrence of hollow-bearing trees and promoted coarse woody debris. Mammals responded differently to shifts in forest structure and composition depending on their habitat requirements. This study highlights the complex interplay between fire regimes, environmental gradients, and biotic adaptations across temporal and spatial scales. It emphasizes the importance of understanding complex interactions to effectively manage fire-prone ecosystems in the face of climate change. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fire" title="fire">fire</a>, <a href="https://publications.waset.org/abstracts/search?q=ecology" title=" ecology"> ecology</a>, <a href="https://publications.waset.org/abstracts/search?q=biodiversity" title=" biodiversity"> biodiversity</a>, <a href="https://publications.waset.org/abstracts/search?q=landscape%20ecology" title=" landscape ecology"> landscape ecology</a> </p> <a href="https://publications.waset.org/abstracts/172700/the-response-of-mammal-populations-to-abrupt-changes-in-fire-regimes-in-montane-landscapes-of-south-eastern-australia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/172700.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">73</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6011</span> Enterprise Risk Management: A Future Outlook</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ruchi%20Agarwal">Ruchi Agarwal</a>, <a href="https://publications.waset.org/abstracts/search?q=Jake%20Ansell"> Jake Ansell</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Austerity impacts on all aspects of society. Companies into the future will have to be more capable of dealing with the risks they face. Enterprise Risk Management (ERM) has widely been accepted in recent years as an approach to manage risks within businesses. ERM attempts to tackle risk holistically with gains from opportunities in a managing risk and reduction in the risk of failure. The paper reviews merits and demerits of approaches to risk management in regard to antifragility. A qualitative study has investigated current practices and the problems with ERM implementation by interviewing over 25 chief risk officers and senior management. The findings indicate the gap in ERM description, understanding, and implementation. The paper suggests risk learning and expertise knowledge supports development of effective enterprise risk management by designing systems with inherent resilience. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=risk%20management" title="risk management">risk management</a>, <a href="https://publications.waset.org/abstracts/search?q=interviews" title=" interviews"> interviews</a>, <a href="https://publications.waset.org/abstracts/search?q=antifragility" title=" antifragility"> antifragility</a>, <a href="https://publications.waset.org/abstracts/search?q=failure" title=" failure"> failure</a> </p> <a href="https://publications.waset.org/abstracts/11136/enterprise-risk-management-a-future-outlook" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/11136.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">562</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6010</span> Fire Risk Information Harmonization for Transboundary Fire Events between Portugal and Spain</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Domingos%20Viegas">Domingos Viegas</a>, <a href="https://publications.waset.org/abstracts/search?q=Miguel%20Almeida"> Miguel Almeida</a>, <a href="https://publications.waset.org/abstracts/search?q=Carmen%20Rocha"> Carmen Rocha</a>, <a href="https://publications.waset.org/abstracts/search?q=Ilda%20Novo"> Ilda Novo</a>, <a href="https://publications.waset.org/abstracts/search?q=Yolanda%20Luna"> Yolanda Luna</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Forest fires along the more than 1200km of the Spanish-Portuguese border are more and more frequent, currently achieving around 2000 fire events per year. Some of these events develop to large international wildfire requiring concerted operations based on shared information between the two countries. The fire event of Valencia de Alcantara (2003) causing several fatalities and more than 13000ha burnt, is a reference example of these international events. Currently, Portugal and Spain have a specific cross-border cooperation protocol on wildfires response for a strip of about 30km (15 km for each side). It is recognized by public authorities the successfulness of this collaboration however it is also assumed that this cooperation should include more functionalities such as the development of a common risk information system for transboundary fire events. Since Portuguese and Spanish authorities use different approaches to determine the fire risk indexes inputs and different methodologies to assess the fire risk, sometimes the conjoint firefighting operations are jeopardized since the information is not harmonized and the understanding of the situation by the civil protection agents from both countries is not unique. Thus, a methodology aiming the harmonization of the fire risk calculation and perception by Portuguese and Spanish Civil protection authorities is hereby presented. The final results are presented as well. The fire risk index used in this work is the Canadian Fire Weather Index (FWI), which is based on meteorological data. The FWI is limited on its application as it does not take into account other important factors with great effect on the fire appearance and development. The combination of these factors is very complex since, besides the meteorology, it addresses several parameters of different topics, namely: sociology, topography, vegetation and soil cover. Therefore, the meaning of FWI values is different from region to region, according the specific characteristics of each region. In this work, a methodology for FWI calibration based on the number of fire occurrences and on the burnt area in the transboundary regions of Portugal and Spain, in order to assess the fire risk based on calibrated FWI values, is proposed. As previously mentioned, the cooperative firefighting operations require a common perception of the information shared. Therefore, a common classification of the fire risk for the fire events occurred in the transboundary strip is proposed with the objective of harmonizing this type of information. This work is integrated in the ECHO project SpitFire - Spanish-Portuguese Meteorological Information System for Transboundary Operations in Forest Fires, which aims the development of a web platform for the sharing of information and supporting decision tools to be used in international fire events involving Portugal and Spain. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=data%20harmonization" title="data harmonization">data harmonization</a>, <a href="https://publications.waset.org/abstracts/search?q=FWI" title=" FWI"> FWI</a>, <a href="https://publications.waset.org/abstracts/search?q=international%20collaboration" title=" international collaboration"> international collaboration</a>, <a href="https://publications.waset.org/abstracts/search?q=transboundary%20wildfires" title=" transboundary wildfires"> transboundary wildfires</a> </p> <a href="https://publications.waset.org/abstracts/51987/fire-risk-information-harmonization-for-transboundary-fire-events-between-portugal-and-spain" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/51987.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">252</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6009</span> A Guidance to Enhance the Risk Culture among the Organizations</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Najeebah%20Almahmeed">Najeebah Almahmeed</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Risk Management is an evolving subject among organizations that include corporations, governments, non-governmental organizations, and not-for-profit corporations. In order to enhance awareness around the importance of Risk Management and make sure everyone is using it in their day-to-day job, the Risk Culture topic has emerged and gained importance not only in the Finance Sector but also in the National Oil Companies in Kuwait. Risk Culture can be defined as the shared beliefs, attitudes, and behaviors within a company that guide its approach to managing risks. It acts as a connecting force that links policies, procedures, and individuals, influencing how risks are understood and tackled through activities. In this research, benefits of Risk Culture are shared, guidelines are presented to promote a risk aware culture, and fully embed and enforce Risk-based processes and procedures. Moreover, this research demonstrates methodologies of measuring the Risk Culture using specific dimensions and clusters. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=clusters" title="clusters">clusters</a>, <a href="https://publications.waset.org/abstracts/search?q=dimensions" title=" dimensions"> dimensions</a>, <a href="https://publications.waset.org/abstracts/search?q=national%20oil%20companies" title=" national oil companies"> national oil companies</a>, <a href="https://publications.waset.org/abstracts/search?q=risk%20culture" title=" risk culture"> risk culture</a>, <a href="https://publications.waset.org/abstracts/search?q=risk%20management" title=" risk management"> risk management</a> </p> <a href="https://publications.waset.org/abstracts/172830/a-guidance-to-enhance-the-risk-culture-among-the-organizations" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/172830.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">79</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6008</span> Risk Assessment for International Investment: A Standardized Approach to Identify Risk, Risk Appetite, Risk Rating, Risk Treatment and Mitigation Plans</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pui%20Yong%20Leo">Pui Yong Leo</a>, <a href="https://publications.waset.org/abstracts/search?q=Normy%20Maziah%20Mohd%20Said"> Normy Maziah Mohd Said</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Change of global economy landscape and business environment has led to companies’ decision to go global and enter international markets. As the companies go beyond the comfort zone (i.e. investing in the home country), it is important to ensure a comprehensive risk assessment is carried out. This paper describes a standardized approach for international investment, ensuring identification of risk, risk appetite, risk rating, risk treatment and mitigation plans for respective international investment proposal. The standardized approach is divided into three (3) stages as follows: Stage 1 – Preliminary Risk profiling; with the objective to gauge exposure to countries and high level risk factors as first level assessment. Stage 2 – Risk Parameters; with the objective to define risk appetite for the international investment from the perspective of likelihood and impact. Stage 3 – Detailed Risk Assessments; with the objectives to assess in detail any triggered elements from Stage 1, and project specific risks. The final output will include the mitigation plans for the identified risks for the total investment. Example will be given in this paper to show how comprehensive risk assessment is carried out for an international investment in power energy sector. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=international%20investment" title="international investment">international investment</a>, <a href="https://publications.waset.org/abstracts/search?q=mitigation%20plans" title=" mitigation plans"> mitigation plans</a>, <a href="https://publications.waset.org/abstracts/search?q=risk%20appetite" title=" risk appetite"> risk appetite</a>, <a href="https://publications.waset.org/abstracts/search?q=risk%20assessment" title=" risk assessment"> risk assessment</a> </p> <a href="https://publications.waset.org/abstracts/61464/risk-assessment-for-international-investment-a-standardized-approach-to-identify-risk-risk-appetite-risk-rating-risk-treatment-and-mitigation-plans" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/61464.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">388</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6007</span> Research on Measuring Operational Risk in Commercial Banks Based on Internal Control</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Baobao%20Li">Baobao Li</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Operational risk covers all operations of commercial banks and has a close relationship with the bank’s internal control. But in the commercial banks' management practice, internal control is always separated from the operational risk measurement. With the increasing of operational risk events in recent years, operational risk is paid more and more attention by regulators and banks’ managements. The paper first discussed the relationship between internal control and operational risk management and used CVaR-POT model to measure operational risk, and then put forward a modified measurement method (to use operational risk assessment results to modify the measurement results of the CVaR-POT model). The paper also analyzed the necessity and rationality of this method. The method takes into consideration the influence of internal control, improves the accuracy and effectiveness of operational risk measurement and save the economic capital for commercial banks, avoiding the drawbacks of using some mainstream models one-sidedly. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=commercial%20banks" title="commercial banks">commercial banks</a>, <a href="https://publications.waset.org/abstracts/search?q=internal%20control" title=" internal control"> internal control</a>, <a href="https://publications.waset.org/abstracts/search?q=operational%20risk" title=" operational risk"> operational risk</a>, <a href="https://publications.waset.org/abstracts/search?q=risk%20measurement" title=" risk measurement"> risk measurement</a> </p> <a href="https://publications.waset.org/abstracts/10143/research-on-measuring-operational-risk-in-commercial-banks-based-on-internal-control" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/10143.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">398</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6006</span> Provisions for Risk in Islamic Banking and Finance in Comparison to the Conventional Banks in Malaysia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rashid%20Masoud%20Ali%20Al-Mazrui">Rashid Masoud Ali Al-Mazrui</a>, <a href="https://publications.waset.org/abstracts/search?q=Ramadhani%20Mashaka%20Shabani"> Ramadhani Mashaka Shabani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Islamic banks and financial institutions are exposed to the same risks as conventional banking. These risks include the rate return risk, credit or market risk, liquidity risk, and operational risk among others. However, being a financial institution that operates Islamic banking and finance operations, there is additional risk associated with its operations different from conventional finance, such as displacing commercial risk. They face Shari'ah compliance risks because of their failure to follow Shari'ah principles. To have proper mitigation and risk management, banks should have proper risk management policies to mitigate risks. This paper aims to study the risk management taken by Islamic banks in comparison with conventional banks. Also, the study evaluates the provisions for risk management taken by selected Islamic banks and conventional banks. The study employs qualitative analysis using secondary data by applying a content analysis approach with a sample size of 4 Islamic banks and four conventional banks ranging from 2010 to 2020. We find that these banks all use the same technique, except for the associated risk. The extra ways are used, but only for additional risks that are available to Islamic banking and finance. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=emerging%20risk" title="emerging risk">emerging risk</a>, <a href="https://publications.waset.org/abstracts/search?q=risk%20management" title=" risk management"> risk management</a>, <a href="https://publications.waset.org/abstracts/search?q=Islamic%20banking" title=" Islamic banking"> Islamic banking</a>, <a href="https://publications.waset.org/abstracts/search?q=conventional%20bank" title=" conventional bank"> conventional bank</a> </p> <a href="https://publications.waset.org/abstracts/155652/provisions-for-risk-in-islamic-banking-and-finance-in-comparison-to-the-conventional-banks-in-malaysia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/155652.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">83</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6005</span> Holistic Risk Assessment Based on Continuous Data from the User’s Behavior and Environment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Cinzia%20Carrodano">Cinzia Carrodano</a>, <a href="https://publications.waset.org/abstracts/search?q=Dimitri%20Konstantas"> Dimitri Konstantas</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Risk is part of our lives. In today’s society risk is connected to our safety and safety has become a major priority in our life. Each person lives his/her life based on the evaluation of the risk he/she is ready to accept and sustain, and the level of safety he/she wishes to reach, based on highly personal criteria. The assessment of risk a person takes in a complex environment and the impact of actions of other people’actions and events on our perception of risk are alements to be considered. The concept of Holistic Risk Assessment (HRA) aims in developing a methodology and a model that will allow us to take into account elements outside the direct influence of the individual, and provide a personalized risk assessment. The concept is based on the fact that in the near future, we will be able to gather and process extremely large amounts of data about an individual and his/her environment in real time. The interaction and correlation of these data is the key element of the holistic risk assessment. In this paper, we present the HRA concept and describe the most important elements and considerations. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=continuous%20data" title="continuous data">continuous data</a>, <a href="https://publications.waset.org/abstracts/search?q=dynamic%20risk" title=" dynamic risk"> dynamic risk</a>, <a href="https://publications.waset.org/abstracts/search?q=holistic%20risk%20assessment" title=" holistic risk assessment"> holistic risk assessment</a>, <a href="https://publications.waset.org/abstracts/search?q=risk%20concept" title=" risk concept"> risk concept</a> </p> <a href="https://publications.waset.org/abstracts/145051/holistic-risk-assessment-based-on-continuous-data-from-the-users-behavior-and-environment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/145051.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">126</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=wildfire%20risk.&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=wildfire%20risk.&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=wildfire%20risk.&page=4">4</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=wildfire%20risk.&page=5">5</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=wildfire%20risk.&page=6">6</a></li> <li class="page-item"><a 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