Fire Mitigation Research Articles

Peatland Forest Fire Mitigation Policies: Impact on Traditional Farmer’s Food Security and Environmental Improvement

Indonesia is one of the countries with the most vulnerable food security to the effects of climate change. Peatlands have a considerable potential for crop production, but they must be managed carefully. The government issued a regulation restricting burning the land for farming preparation in response to forest and land fires on peatlands. Unfortunately, traditional farmers lost their food security due to that policy. This research aims to: i) analyze farmers’ food security and its impact on improving the environment after the policy banning burning in land preparation. Data was collected through interviews, field observations, and focus group discussions. The acquired data is analyzed qualitatively and descriptively. According to the study’s findings, their land no longer supports farmer’s food availability, and they must pursue new livelihoods to afford to buy their daily needs from the nearest market. Food utilization is still superficial. Farmers’s food stability is extremely fragile due to the impact of policies, pest invasions, droughts, and floods. Although the policy bans burning in land preparation causes farmers to lose their self-sufficient food security, it has improved peatland ecosystems. The government must strengthen community empowerment programs to restore farmers’ food security.

Assessing policy preferences for preventing and managing wildfire in Greece

Extreme temperatures and droughts have led to catastrophic wildfires across Greece over the last two decades, with 2023 experiencing the largest fire-driven evacuation in the country's history. Existing wildfire governance approaches may be outdated in the face of these new challenges. Greek residents' attitudes and willingness to pay for additional prevention and mitigation may be changing with the increased threat. Because policy design can affect public support and subsequent outcomes, we conducted an online national-level survey of Greek residents (n = 722) with an embedded discrete choice experiment, aimed at assessing preferences and willingness-to-pay for different policy alternatives to address wildfire risk. Our results suggest that, in general, Greek residents are unsatisfied with current fire policy, are willing to pay a small amount for additional fire mitigation efforts aimed to reduce burned areas, and prefer action led by the Greek Forest or Fire Services using awareness and education campaign—for example, fire prevention informative mailers or workshops.

Intelligent System AI as A Service Life on Land

Intelligent System - AI as a service” , is a project to predict the occurrence of forest fire.Forest fires pose a significant threat to both the environment and human safety. Timely prediction of forest fires is crucial for effective mitigation and prevention efforts. To enhance real-time monitoring and early warning capabilities, the system incorporates remote sensing data using machine learning techniques. Fires are now causing an additional 3 million hectares (7.5 million acres) of tree cover loss per year than they did in 2001, according to a newly released Global Forest Watch analysis that examined fires that burn all or most of a forest’s living overstory trees. The majority of all fire-caused tree cover loss in the past 20 years (nearly 70%) occurred in boreal regions. Although fires are naturally occurring there, they are now increasing at an annual rate of 3% and burning with greater frequency and severity and over larger areas than historically recorded. Forest fires pose significant threats to ecosystems, human lives, and property. Early prediction and mitigation of forest fires are crucial to reducing their destructive impact. This abstract presents an overview of a forest fire prediction system that leverages modern technology and data-driven approaches. The proposed forest fire prediction system utilizes a combination of remote sensing data, weather information, historical fire data, and machine learning algorithms to forecast the likelihood of forest fires in specific regions. Advanced techniques such as deep learning and ensemble models are employed to analyze the complex interactions between various environmental factors that contribute to fire ignition and spread. Fires are not naturally occurring in tropical rainforests, but in recent years, as deforestation and climate change have degraded and dried out intact forests, fires have been escaping into standing tropical rainforests. GFW findings suggest fires in the tropics have increased by roughly 5% per year since 2001.

Aplicación de Google Earth Engine en el análisis preliminar de la severidad de incendios en la Reserva y Parque Nacional, Argentina

Fires are one of the most aggressive and sudden disturbances that can affect ecosystems. During the first months of the year 2022, a series of fires of great magnitude spread in the Iberá streams, which is the largest wetland in Argentina and the second largest in South America after the Pantanal in Brazil, with devastating environmental and social consequences. The aim of this study is to analyze the fires that occurred in the Iberá Reserve and National Park located in the province of Corrientes at the beginning of the year 2022 using remote sensing techniques through the Google Earth Engine processing platform. In this study, the total affected areas were calculated and their severity was analyzed. The results indicate that approximately 20 % of the reserve and close to 50 % of the Iberá National Park have been burned, with a predominance of severity levels ranging from moderate high to high. Remote sensing techniques are a significant resource in fire monitoring, making it a powerful tool in planning regulations or measures aimed at contributing to the mitigation, management, and early warning of fires.

Spatial analysis and machine learning prediction of forest fire susceptibility: a comprehensive approach for effective management and mitigation

Forest fires (FF) in tropical seasonal forests impact ecosystem. Addressing FF in tropical ecosystems has become a priority to mitigate impacts on biodiversity loss and climate change. The escalating frequency and intensity of FF globally have become a mounting concern. Understanding their tendencies, patterns, and vulnerabilities is imperative for conserving ecosystems and facilitating the development of effective prevention and management strategies. This study investigates the trends, patterns, and spatiotemporal distribution of FF for the period of 2001–2022, and delineates the forest fire susceptibility zones in Odisha State, India. The study utilized: (a) MODIS imagery to examine active fire point data; (b) Kernel density tools; (c) FF risk prediction using two machine learning algorithms, namely Support Vector Machine (SVM) and Random Forest (RF); (d) Receiver Operating Characteristic and Area Under the Curve, along with various evaluation metrics; and (e) a total of 19 factors, including three topographical, seven climatic, four biophysical, and five anthropogenic, to create a map indicating areas vulnerable to FF. The validation results revealed that the RF model achieved a precision exceeding 94 % on the validation datasets, while the SVM model reached 89 %. The estimated forest fire susceptibility zones using RF and SVM techniques indicated that 20.14 % and 16.72 % of the area, respectively, fall under the “Very High Forest Fire” susceptibility class. Trend analysis reveals a general upward trend in forest fire occurrences (R2 = 0.59), with a notable increase after 2015, peaking in 2021. Notably, Angul district was identified as the most affected area, documenting the highest number of forest fire incidents over the past 22 years. Additionally, forest fire mitigation plans have been developed by drawing insights from forest fire management strategies implemented in various countries worldwide. Overall, this analysis provides valuable insights for policymakers and forest management authorities to develop effective strategies for forest fire prevention and mitigation.

Fire Mitigation Game Assisted Project Based Learning Model Towards Elementary School Student’s Cognitive Skill

Cognitive skill was a needed effort for students in nowadays modern era that occurs continuously. The use of fire mitigation game application trough project-based learning was an effort to support the stage of cognitive skills. The main purpose of the research was analysed the model of project-based learning assisted by fire mitigation game in order to improve the student’s cognitive skills. The method that applied in this research was quantitative research that conducted towards 55 SD Muhammadiyah 9 Surabaya students. The participant selection was purposive sampling based on the inclusion criteria that conducted by the researchers and the data collection was conducted by learning implementation observation and student’s critical thinking level test. The data that collected in the research was statistically analysed trough correlational approach (correlational research) and linear regression. Based on the research it was showed that correlation coefficient gained significances values about 0,000 < 0,05 it was confirmed that H0 was rejected and H1 was accepted. Therefore, based on the analysis of the research data it was appropriate with normality test by histogram graphic with bell form without leaning right or left, so that the histogram graphic was recognized as normal. It was also recognized as normal because of normality pretest based on Q-Q plot that the plots was showed the fit line, so that the distribution recognized as normal, because the data above was following the normal line. Responding the result of the analysis that conduct by significances values (sig.) in the F-Test was 0,000. Because sig. 0,000 < \(\alpha\) = 0,05 it could be summed up that there are influence of Project-based learning model assisted by fire mitigation game towards the student’s cognitive skills in elementary school.

The value of local wisdom for peatland fire risk reduction in the wetland area of South Kalimantan

Mitigation of land fires that occur in wetland areas, especially in peatlands, continues to be addressed by the community in Banjarbaru, South Kalimantan Province. Local wisdom that applies in the community, which includes local knowledge, local value, local skills, local sources, and regional society solidarity, is expected to reduce the risk of land fires. The research objective is to analyze the value of local wisdom for peatland fire reduction in the wetland area of South Kalimantan. The respondents interviewed were 30 from the Community and Fire Care Community or Masyarakat Peduli Api (MPA) members. Local wisdom prevailing in the community can reduce the risk of peatland fires. The community has the local knowledge, local value, local skills, local sources, and local society solidarity in managing peatlands. Peatlands managed by communities are less likely to burn than unmanaged lands. The tapulikampar system is a local wisdom in the Banjar community to prepare agricultural peatlands without burning. The Banjar community also has good skills in managing peatlands, which are not easily damaged and prone to burning. Cooperation between community groups in MPA is also well implemented in monitoring land fires and suppression efforts. The community makes maximum efforts so that peatlands are not damaged, and the risk of fire can be reduced because potential resources on peatlands must be passed on to the next generation.

Mitigating land fire disasters: Implementation of agricultural land fire risk management information system in Aunupe Village, South Konawe Regency

Climate change, which causes increased temperatures, prolonged droughts, and dry conditions, heightens the risk of land fires. A similar scenario unfolded in Aunupe Village, where several fires occurred on agricultural land over the past three years, resulting in crop failure and degraded soil quality, leading to financial losses for land-owning farmers. To mitigate the risk of land fire disasters, an agricultural land fire disaster risk management information system is necessary in Aunupe Village, South Konawe Regency. The objective of this community-based empowerment program is to mitigate the risk of land fire disasters. To achieve the desired outcomes, initial coordination with farmer group partners is conducted, followed by the design and installation of fire sensor equipment sets in collaboration with farmer groups. Furthermore, focus group discussions (FGD) are conducted with farmer group partners to ensure their understanding and cooperation. The activities result in the development of an agricultural land fire risk management information system, facilitating the prompt detection, monitoring, and response to fire incidents in the agricultural land of the Lembah Harapan Farmers Group. Additionally, farmer group partners acquire knowledge regarding the utilization of fire mitigation systems.

Diagnostics, mitigation, and extinguishment of fires at non-sanitary landfills

Diagnostics, mitigation, and extinguishment of fires at non-sanitary landfills

Hotspot Distribution Analysis as Forest and Land Fire Indicators in the New National Capital City (IKN)

East Kalimantan Province is planned as the new national capital city (IKN). Forest and land fires occur regularly every year and their frequency is increasing, especially during the dry season. This research uses secondary data, namely hotspot data. Hotspot data was obtained from the results of the 2012-2022 S-NPP VIIRS image recording. Data analysis in this study used descriptive and statistical analysis. The results of processing and analysis of the distribution of hotspots are overlaid with administrative maps so that the distribution of hotspots in each district in the study area can be identified. The results of the study show that hotspots distribution from the 2012-2022 S-NPP VIIRS image recording in East Kalimantan Province is varies quite a bit in each district. The highest hotspots distribution is in Kutai Kartanegara Regency and the lowest is in Mahakam Ulu and Penajam Paser Utara Regency. The higher number of hotspots is the higher incidence for forest and land fires. The distribution of hotspots needs to be known because it can be a form of early detection and fire mitigation so that the negative impact of fires can be minimized.

Community Participation in Forest Conservation as A Forest Fire Mitigation and Adaptation on The Arjuno Mountain

Participatory conservation is an activity to mitigate and adapt to forest and land fires through field farmer school (FFS) activity which forest farmer groups (FFG), non-governmental organizations (NGOs), and academics attend. This research aims to provide an innovative approach to conservation activities with the community, especially on Mount Arjuno, which often experiences forest fires. The results show that local stakeholders and authorities must support community participation in forest conservation. This study shows that FFS (Field Farmer School) activities can facilitate the community in identifying problems and generating ideas for conservation activities through the agroforestry system, mitigation and adaptation of forest and land fires, and edu-ecotourism. Conservation designs and community participation strategic plans are outputs of forest fire mitigation and adaptation activities. The FFS as the methodology used is adequate for knowing what the farmer needs relating to conservation that stakeholders will program. Moreover, generating the conservation activity must be combined with activities to increase the FFG income. So, the FFG will have good welfare.

Social Capital of Banjarese for Peatland Fire Mitigation: Combining of Local Wisdom and Environment

Repeated fires cause peatlands to degrade. Fire management has been carried out, but fires continue to occur, especially during the dry season. Through social capital that exists in the community based on the local wisdom of the Banjar people in environmental management, it is hoped that peatland fires can be overcome in this area. This research aims to analyze the social capital of the Banjar people in mitigating land fires based on local wisdom and the environment. The sample in this study was 250 people who live in an area prone to fires on peatlands in Banjarbaru, South Kalimantan, Indonesia. There are three variables in this study, namely Trust (T), Network (N), and Norm (N). There are 33 Likert scale questions (1–4, strongly agree-strongly disagree). We also conducted interviews with 20 members of the Fire Care Community (MPA) to obtain information about the social capital of the Banjar community in mitigating land fires. The analysis used is Structural Equation Modeling (SEM). The study results show norms have the greatest influence on disaster mitigation of peatland fires compared to trust and social networks. Norms in the community in the form of values from peatlands, rules, norms, and sanctions regulate the community more to deal with the problem of peatland fires than trust and social networks

Electric sampling of soot particles in spreading non-premixed flames: methodology and influence of gravity

Finer strategies of spacecraft fire mitigation require more experimental data related to fire detection. Fire detection systems developed on Earth rely massively on the optical detection of soot particles, which are present in the smoke. To detect the fire correctly, it is thus important to know how the optical properties of these particles are affected in reduced gravity. With different transport processes and increased residence time, soot in reduced gravity can be different from those produced at normal gravity. As their optical properties are related to their morphological properties, a better understanding about the evolution of soot particle morphology in flames under microgravity conditions is required. Within this context, a novel technique of soot sampling using electric field is applied to a spreading non-premixed flame at normal and micro-gravity. The soot particles sampled are observed subsequently under Transmission Electron Microscopy (TEM). Density, soot particle projected area, radius of gyration, fractal dimension, and primary particle size are extracted and the influence of gravity is investigated with the evolution of these morphological properties within the flame. Though the present study cannot be conclusive in itself, the similarity between the evolution of the optical density measured throughout the flame just before the electric perturbation required by the sampling technique and the evolution of the amount of soot deposited due to the electric perturbation along the sampling plates supports the future works that need to be devoted to further assess the consistency of the technique.

Upaya Mitigasi Kebakaran Hutan dan Lahan Melalui Program CSR Budidaya Madu Hutan Gambut PT Pertamina RU II Sungai Pakning

Corporate Social Responsibility is social responsibility for companies as a real effort for companies to contribute to realizing the welfare of society. The incidence of forest and land fires in Riau, especially Bengkalis Regency, is a social issue that is a serious problem for the central and regional governments. The problem formulation of this research is how CSR Pertamina RU II Sungai Pakning involves the community in the process of mitigating forest and land fires. The aim of this research is to determine the process of forest fire mitigation through the CSR program of cultivating peat forest honey. The research method uses qualitative, because this research was conducted to determine, pay attention to and understand problems in social phenomena. The results of this research are that the Biene Honey Group is a pioneer in making people aware of honey seekers in the forest using traditional methods. In the future, it is hoped that PT. Pertamina RU II Sungai Pakning to be sustainable to continue the CSR program. as an effort to improve the welfare of the surrounding community.

Measuring the Results of Weather Modification Technology for Forest Fire Mitigation in Indonesia

Weather Modification Technology (WMT) is one of reliable solution that is often used in forest fire mitigation activity in Indonesia. Through the process of physically engineering clouds into rain and rewetting peatlands, it is hoped to help suppress hotspots and prevent forest fires from spreading. In this study, an analysis of forest fire mitigation activities in the area of Sumatra Island, Indonesia, shows that WMT can increase rainfall by up to 30% during its implementation period. WMT activity is also able to assist in suppressing the escalation of hotspots in the targeted areas. By increasing rainfall, WMT also plays a role in maintaining the wetness of peatlands, thus minimizing the potential for fire expansion. This study also explains that the role of the Indonesian Government in implementing WMT for forest fire mitigation continues to experience development.

Edible fire buffers: Mitigation of wildfire with multifunctional landscapes.

Wildfires ravage lands in seasonally dry regions, imposing high costs on infrastructure maintenance and human habitation at the wildland-urban interface. Current fire mitigation approaches present upfront costs with uncertain long-term payoffs. We show that a new landscape intervention on human-managed wildlands-buffers of a low-flammability crop species such as banana irrigated using recycled water-can mitigate wildfires and produce food profitably. This new intervention can complement existing fire mitigation approaches. Recreating a recent, major fire in simulation, we find that a medium-sized (633 m) banana buffer decreases fireline intensity by 96%, similar to the combination of prescribed burns and mechanical thinning, and delays the fire by 316 min, enabling safer and more effective firefighting. We find that under climate change, despite worsened fires, banana buffers will still have a protective effect. We also find that banana buffers with average yield could produce a profit of $56k USD/hectare through fruit sales, in addition to fire mitigation.

The Synergy of Local Government and Academia in Addressing Peatland Fires in Siak Regency with a Technology-Based Approach

This study aims to explore the synergy between the local government and academia in mitigating peatland fires in Siak Regency. In the fields of social humanities, science, and technology, this study uses an exploratory qualitative method. The study reveals the important role of the local government in disaster mitigation through regional regulations, policies, and synergy between related departments. Through the regional regulation on forest fire prevention and handling, the local government has involved the Regional Disaster Management Agency (BPBD) and other supporting units in mitigation efforts. In addition, academics have also contributed by developing a technology-based peatland fire detection system. The main results of this study show that collaboration between the local government and academia is very significant in peatland fire mitigation efforts. The role of the local government through Governor's Decree No. 9 of 2020 and Regent's Decree No. 4 of 2022, as well as synergy between departments, encourages more effective steps in preventing and handling peatland fires. In addition, the contribution of academics to producing a technology-based peatland fire mitigation technology design opens up the potential for innovative and sustainable solutions. These findings have significant implications, as they highlight the importance of collaboration between the local government and academia in facing the challenges of peatland fire mitigation in Siak Regency. This synergy allows a better understanding of the problem, the development of more effective policies, and the application of advanced technology in preventing and handling peatland fires.

Predicting sub‐continental fuel hazard under future climate and rising atmospheric CO2 concentration

Abstract Bushfire fuel hazard is determined by the type, amount, density and three‐dimensional distribution of plant biomass and litter. The fuel hazard represents a biological control on fire danger and may change in the future with plant growth patterns. Rising atmospheric CO2 concentration (Ca) stimulates plant productivity (‘fertilisation effect’) but also alters climate, leading to a ‘climatic effect’. Both effects have impacts on future vegetation and thus fuel hazard. Quantifying these effects is an important component of predicting future fire regimes and evaluating fire management options. Here, we combined a machine learning algorithm that incorporates the power of large fine spatial resolution (i.e. 90 m) datasets with a novel optimality model that accounts for the climatic and fertilisation effects on vegetation cover. We demonstrated the usefulness and practicality of this framework by predicting fuel hazard across the state of Victoria in Australia. We fitted and evaluated the models with long‐term (i.e. 20 years), ground‐based fuel observations. The models achieved strong agreement with observations across the fuel hazard range (accuracy >65%). We found fuel hazard increased more in dry environments due to future climate and Ca. The contribution of the ‘fertilisation effect’ to future fuel hazard varied spatially by up to 12%. The predictions of future fuel hazard are directly useful to inform fire mitigation policies and as a reference for climate model projections to account for fire impacts. Synthesis and applications: Climate change and rising Ca have profound impacts on vegetation and thus fuel load. Operational fire management and future fire risk forecasts will benefit from our realistic fuel load prediction framework that incorporates plant responses and fine soil and terrain attributes.

Fire Extinguisher Robot: A Smart and Autonomous System for Fire Hazard Mitigation

The rapid growth of the human population and technological advancements have led to an increased occurrence of fire accidents and hazards in various settings. The challenging and demanding nature of fire extinguishing tasks, coupled with the physical limitations of human responders, necessitates innovative solutions to mitigate these risks effectively. One such solution is the development of fire extinguishing robots, which offer the potential to safeguard both human lives and the surrounding environment. This research introduces a hardware model of a fire extinguishing robot designed to address the complexities associated with fire suppression tasks. The robot's primary objective is to detect and extinguish fires swiftly, ideally before they can escalate and cause significant damage. By assuming the role of fire suppression, these robots can significantly reduce errors and overcome the limitations faced by human responders. Our designed fire extinguishing robot possesses several key functionalities. It autonomously explores the area, identifies the location of the fire, and efficiently extinguishes the flames, preventing uncontrolled fire outbreaks. Moreover, this robot demonstrates versatility by effectively handling various types of fires across diverse geographical locations. It navigates through structures while actively scanning for signs of fire, ensuring comprehensive coverage. Additionally, the robot is equipped with an array of sensors capable of monitoring critical parameters such as temperature, humidity, obstacles, and distances. These parameters are displayed in real-time on an LCD interface, providing essential data to operators. The robot's operation is streamlined through a user-friendly Bluetooth Terminal App, allowing remote control and providing users with real-time updates on fire status. In practical applications, our fire extinguishing robot shines in scenarios where the risk to human servicemen entering fire-prone areas is exceptionally high. Compared to existing robotic solutions, our system distinguishes itself by its ability to provide real-time data feedback, making it an invaluable tool for fire mitigation and prevention. Key Words: Fire Extinguishing Robot, Robotics, Fire Safety, Autonomous Systems, Fire Detection, Hazard Mitigation, Sensor Technology, Fire Prevention.

Strategi Mitigasi Kebakaran Lahan Terhadap Kualitas Udara dan Risiko Kesehatan Masyarakat (Studi Kasus: Kecamatan Pangkalan Kerinci, Kabupaten Pelalawan, Provinsi Riau)

Land fires are occurred almost every year during the dry season in Pangkalan Kerinci District. These condition resulted in damage and loss in terms of economic, social and environment that will inhibit the rate of development in Pangkalan Kerinci District so that necessary control measures against land and forest fires. The research method used was a case study, the samples for this study were selected through purposive sampling method were the data for this study were obtained through questioner, interview and observation. The results of this study that there are influence between the incidence of land fires with the level of air quality and the level of public health that occurs in Pangkalan Kerinci District, the formulation of a mitigation strategy for preventing land fires in Pangkalan Kerinci District in quadrant 1, which means that the land fire mitigation strategy must carry out a progressive strategy by utilizing internal; strengths to take advantage of external opportunities to achieve the optimal strategy.