Fire Disaster Research Articles

FireDrone: Multi‐Environment Thermally Agnostic Aerial Robot

Deploying robots in extreme environments reduces risks to human lives. However, robot operating conditions are often limited by environmental factors such as extreme temperatures encountered in fire disasters or polar regions. Especially drones face challenges in carrying thermal management systems protecting vital components, due to limited payload capacity compared to ground robots. Herein, a thermally agnostic aerial robot comprising structural thermally insulating material and a phase change material cooling system, inspired by natural thermal regulation principles, is designed, modelled and experimentally validated. Building on the robot development paradigm of physical artificial intelligence, the concurrent development of materials and design enables the creation of novel physiologically adaptive systems. Polyimide aerogel is applied as one of the main structural materials in the drone's design to adapt the robot's structure and properties to extreme temperatures. Glass fiber reinforcement with silica aerogel particles reduces high‐temperature shrinkage and pore structure degradation after exposure to high temperatures and most of the composite aerogel features are preserved. A high technology‐readiness‐level drone prototype, allowing for operation in a broad range of ambient temperatures, is demonstrated. The proposed technology for thermally agnostic drones may unleash the great potential of aerial robotics in multiple industrial and research applications.

The effect of broadleaf forests in wildfire mitigation in the WUI – A simulation study

The increasing occurrence of large wildfires in Southern European countries calls for the adoption of more effective measures of fire prevention, to protect people and infrastructures, namely in the Wildland-Urban Interface (WUI). Previous research suggests that broadleaf forests could mitigate the effects of these wildfires due to their lower flammability. However, few attempts have been made to investigate the possibility of using broadleaf-based green firebreaks to protect infrastructures, as an alternative to current less ecologically and economically sustainable fuel reduction techniques. Here, we assess the relevance of a broadleaves fuel model in reducing fire hazard in the WUI, by analyzing a set of six Industrial Zones (IZs) in Central Portugal, severely affected by wildfires during the catastrophic fire season of 2017. We developed alternative scenarios for the spatial simulation of fire behavior, using a factorial combination of weather conditions (standard and extreme), buffer around each IZ (distances of 100 m and 500 m) and land cover (current and broadleaves fuel model). The simulations were grounded on real-world data obtained from reconstructed fire front isochrones and fieldwork. Our results suggest that replacing the flammable vegetation present in the WUI with broadleaf forests could reduce fireline intensity by up to five times, even under extreme weather conditions. This reduction occurs subtly as the broadleaf cover interface is expanded from 100 m to 500 m. Our results show that fires that exceed the suppression capacity in pine and eucalypt forests (>4 m flame length) can be effectively suppressed in broadleaf forests under extreme fire weather (1.4 m flame length) and easily suppressed in broadleaf forests in standard weather (0.8 m flame length). Due to significant changes in land use and extreme weather events, future large wildfires could occur again in Portugal. In this regard, our results corroborate the urgent need to discuss forest management in the country, which has already proven to be insufficient to prevent fire disasters in the WUI.

A novel approach for active and synchronous removal of fire-generated CO based on Co-La0.1 catalyst: From lab-scale to full-scale tests

CO is an invisible killer that severely threatens the safety of trapped personnel in fire disasters. The existing CO removal approaches are passive and ineffective, which could not satisfy the emergency rescue needs. An active and synchronous CO removal approach (ASCR) based on catalytic oxidation is proposed. By spraying dry powder extinguishant and catalyst powder, the isolation layer and oxidation layer are formed on the fuel surface. CO removal is achieved by both combustion suppression and CO oxidation methods. The synthesized Co-La0.1 catalyst exhibited superior catalytic activity, thermal stability, and selectivity, which met the application requirements of the ASCR approach. The results of lab-scall tests demonstrated that the CO concentration in the smoke flow decreased from 135 ppm to 0 ppm immediately once employing the ASCR approach. Full-scale tests in the confined tunnel further verified the practical application performance. With spraying 2 kg extinguishant and 0.9 kg catalyst powder, CO concentration increased merely by ∼ 20 ppm within 50 min, which was far lower than that without taking any disposal measures (∼800 ppm). This approach can effectively control the CO concentration below the safety threshold in fire disasters and is significant for emergency rescue.

Optimizing disaster communication for future fire mitigation

Forest and land fires are disasters that often occur every dry season in Kalimantan. Fire information often does not reach the public, so disaster communication is urgently needed. Disaster communication is a very important parameter in disaster mitigation so it needs to be improved and requires collaboration and coordination of various stakeholders, such as government, companies, media, scientists, advocacy groups, and the community. There has not been much research on communication with the theme of fire, so more in-depth research is needed. The purpose of this research is to find out how to Optimize Disaster Communication for Future Fires Mitigation”. Research on disaster communication was carried out in the location of the new state capital, East Kalimantan. The research used the descriptive-analytic method to identify the research area and collect secondary data. Disaster communication is an activity carried out by several parties, in this case, the authorities in preventing and overcoming the negative impacts that may arise due to fires. The results showed that the disaster management agency in East Kalimantan was the Regional Disaster Management Agency (BPBD). In mitigating fire disasters the community is known to use social media, namely Instagram, Twitter, and Facebook.

Fire Detection with Image Processing

Abstract: Convolutional neural networks (CNNs) have yielded state-of-theart performance in image classification and other computer vision tasks. Their application in fire detection systems will substantially improve detection accuracy, which will eventually minimize fire disasters and reduce the ecological and social ramifications. However, the major concern with CNNbased fire detection systems is their implementation in realworld surveillance networks, due to their high memory and computational requirements for inference. In this paper, we propose an original, energy-friendly, and computationally efficient CNN architecture, inspired by the SqueezeNet architecture for fire detection, localization, and semantic understanding of the scene of the fire. It uses smaller convolutional kernels and contains no dense, fully connected layers, which helps keep the computational requirements to a minimum. Despite its low computational needs, the experimental results demonstrate that our proposed solution achieves accuracies that are comparable to other, more complex models, mainly due to its increased depth. Moreover, this paper shows how a tradeoff can be reached between fire detection accuracy and efficiency, by considering the specific characteristics of the problem of interest and the variety of fire data

Development of an emission estimation method with satellite observations for significant forest fires and comparison with global fire emission inventories: Application to catastrophic fires of summer 2021 over the Eastern Mediterranean

In the past few decades, forest fires have increased in number and severity, especially in the Mediterranean regions of Türkiye and Greece, where significant fires caused damage to thousands of hectares of land as well as wildlife. The main objective of the present study is to develop an emission estimation method with satellite-based burned area data from significant forest fire events in the Eastern Mediterranean in July–August 2021. In the first stage of this study, pre-fire and post-fire images of the study area acquired by the Sentinel-2 satellite were processed to calculate the normalized burn rate difference index (dNBR). Then, CORINE Land Cover (CLC) data were used for detecting land cover classes in the burned areas. Atmospheric emissions of NOx, CO, SO2, total suspended particulate matter (TSP), particulate matter with diameters that are equal to or smaller than 2.5 μm (PM2.5), and black carbon (BC) were estimated using the EMEP/EEA Tier 2 - technology-specific approach method, in which burned area maps were retrieved using Sentinel-2 imageries and later combined with land cover type and burning efficiency to estimate the quantity of burning biomass emissions. Emission factors were then used to estimate the fires' trace gas and aerosol emissions. The results showed that the highest burned areas were found in the western Mediterranean region in Türkiye and Central Greece (⁓50,000 ha). The atmospheric emissions from these fires were calculated to be similar in both countries. Furthermore, emission amounts were compared with three different global fire emission inventories including GFAS, GFED, and FINN. The emissions obtained from the GFAS database were the highest emissions of the four emission estimation approaches and our estimated emissions were close to the GFAS. Emissions calculated from the other two databases (FINN and GFED) mostly provided underestimated emissions. The emission uncertainties in this study mainly originated from assumptions regarding the inclusion of burned area efficiency in emission calculations, the landcover dataset, and the emission factors used. Overall, this study is considered a new approach to emission calculations using Sentinel-2 data. This research provides further insight into the use of Sentinel-2 data in emission calculation applications at the local to regional scales.

Heat and fire-resistant nanofiber networks: Towards tailoring the new generation of lightweight intermeshing polymer composite systems

Safe use of materials is a primary focus of emerging low-carbon industry. Catastrophic fire incidents due to high flammability of polymers as versatile materials necessitate developing fire-proof polymer composites. In this study, a novel and robust strategy is implemented to fabricate non-flammable and fire-proof thermoplastics with remarkably lower flame retardant (FR) content leading to outstanding limiting oxygen index (LOI) of 30% and UL 94-V0. This can be achieved using nano-fibrillation by forming networks of heat-resistant polymeric nanofibers (polyphenylene ether (PPE) or polyphenylene sulfide (PPS)) within polystyrene (PS). Formation of heat-resistant nanofibers creates a continuous network-structured layer/shield to preserve the matrix against burning and suppresses dripping by boosting the melt-strength. Nanofibers also lead to promoting a graphitized char layer to thoroughly protect the polymer against fire. These synergistic effects enhance FR efficiency, as demonstrated by a 30% reduction in fire growth rate and peak heat release rate, upon inclusion of 15 wt% PPE nanofibers, compared to an equivalent composite with spherical particles. Only the PS sample containing 25 wt% FR and 15 wt% heat-resistant nanofibers meets UL 94-V0 while presence of a similar content of spherical PPE or PPS, graphene nanoparticles, or carbon nanotubes does not provide this feature. Nanofibers also strengthen energy absorption leading to high impact strength of PS composites (120%). Hence, this novel strategy can be extended to a wide range of polymer systems to fabricate novel generation of fire-proof devices with tunable properties for various potential applications including energy storages packs, electronic equipment, and robotics.

PENENTUAN TINGKAT RESIKO KEBAKARAN HUTAN DAN LAHAN MENGGUNAKAN METODE INDEKS CUACA KEBAKARAN (FIRE WEATHER INDEX) DAN JUMLAH TITIK PANAS (HOTSPOT) DI KABUPATEN BANJAR PROVINSI KALIMANTAN SELATAN

Various indicators of hotspot occurrence as a cause of forest and land fires (karhutla) in Banjar District are still difficult to determine due to limited information. The analysis of FFMC (Fine Fuel Moisture Code) and DC (Drought Code) as well as the monitoring of the number of hotspots aims to determine the level of risk of forest and land fire hazards and can be an early picture of future forest and land fire disasters in the Banjar District of South Kalimantan Province. The data processing process to obtain the FFMC and DC values and their relationship with the number of hotspots is to calculate the FFMC and DC values of station observations and model observations through the Microsoft Excel Add-In (FWI Add-in) program. The two models will then be verified with a scatter plot and through the Pearson correlation test the relationship between the FFMC and DC of the ERA5 model and the number of hotspots can be found. As a result, the FFMC and DC (station observation and model) showed extreme risk levels for the 2014, 2015 and 2018 forest and land fires. Both models show a positive and linear relationship on the scatter plot. And in the Pearson correlation test, both variables between the FFMC and DC of the ERA5 model and the number of hotspots are moderately to strongly correlated. This condition indicates that an increase in the risk level of forest and land fires will be followed by a significant increase in the incidence of forest and land fires in the Banjar Regency area of South Kalimantan Province.

Hyperspectral Classification of Hazardous Materials Based on Deep Learning

The identification of hazardous materials is a key measure in the prevention and control of fire and explosion disasters. Conventional techniques used to identify hazardous materials include contact detection and post-sampling laboratory testing, which cannot meet the needs of extreme environments, where personnel and equipment are not accessible for on-site detection. To address this problem, this paper proposes a method for the classification and identification of hazardous materials based on convolutional neural networks, which can achieve non-contact remote detection of hazardous materials. Firstly, a dataset containing 1800 hyperspectral images of hazardous materials, which can be used for deep learning, is constructed based on the hazardous materials hyperspectral data cube. Secondly, based on this, an improved ResNet50-based classification method for hazardous materials is proposed, which innovatively utilizes a classification network based on offset sampling convolution and split context-gated convolution. The results show that the method can achieve 93.9% classification accuracy for hazardous materials, which is 1% better than the classification accuracy of the original ResNet50 network. The network also has high performance under small data volume conditions, effectively solving the problem of low classification accuracy due to small data volume and blurred image data features of labelled hazardous material images. In addition, it was found that offset sampling convolution and split context-gated convolution showed synergistic effects in improving the performance of the network.

Reducing the Risk of Fire Outbreak in Compliance with Fire Safety Regulations in Ghana

Fire outbreak is a disturbing phenomenon that has over the years destroyed market centers. There is growing knowledge that the persistence of these fire disasters is as a result of people’s noncompliance with fire safety regulations. This study therefore contributes to the search for solutions by assessing stakeholders’ capacity to manage fires, While creating the individual trader’s awareness and knowledge on what they need to do against fire risk and disasters. The study is cross-sectional and involved 140 traders and three institutions: National Disaster Management Organization, Kumasi Metropolitan Assembly and Ghana National Fire Service. A systematic sampling technique was used in selecting 140 respondents from a total of 386 with the help of the Sloving technique. The study revealed that traders in the Kumasi Central Market were unaware of what they need to do in case of fire outbreak. It was also shown that, both traders and firefighting institutions do not comply with the safety measures to preventing fire outbreaks. Again it was revealed that haphazard development within the city center serves as a major hindrance for effective fire prevention and control. Based on findings, the study recommends intensive education of traders on how to prevent fire and how to use firefighting tools in case of fire disasters. The study further recommends the review and enforcement of fire prevention codes and regulations to ensure compliance by traders. Keywords: Fire, Safety, Safety measures Risk, Firefighting, Fire training DOI: 10.7176/JEP/14-13-07 Publication date: May 31 st 2023

Mapping of fire level using S-NPP VIIRS as disaster management reference in Banjarbaru City

Fire is a natural disaster that usually occurs during dry season in both developed and developing countries. Best visualization of fire information is a map, because map is easy to use, and has a strong visual impression. Maps can also be used as a medium to deliver fire mitigation instruction. Fire data can be seen from hotspots data recorded using S-NPP VIIRS satellite imagery. Hotspot data from satellite imagery processed in Arc GIS to compose Fire Level Maps which is then used as fire disaster management reference. Based on this, it is necessary to conduct a study which purposively can map a fire level from S-NPP VIIRS satellite imagery hotspot data so it can used as disaster management reference. So this study entitled as Mapping of Fire Levels using S-NPP VIIRS as a Disaster Management Reference. This research is classified as quantitative descriptive research. Population and samples of the research are all hotspots recorded by S-NPP VIIRS satellite imagery in Banjarbaru City covering Banjarbaru Utara, Landasan Ulin, Cempaka, Banjarbaru Selatan and Lianganggang Subdistrict from 2012-2022. Monthly hotspot data is used in this research and are based on high, medium and low confidence levels. Hotspot data recorded from satellite imagery is processed using geographic information systems and remote sensing technology. The results show the number of hotspots recorded from S-NPP VIIRS Satellite Imagery from 2012-2022 in Banjarbaru City was 2.900 hotspot. The highest number of hotspots was in Linganggang (1429 hotspot) followed by Landasan Ulin (1.165 hotspot) and the least in Banjarbaru Selatan (14 hotspot). Most hotspots are found in dry months; August (307 hotspot), September (1.370 hotspot), October (1.053 hotspot) and November (128 hotspot). The number of hotspots based on the medium level of confidence is mostly found in Banjarbaru City (2.560 hotspot). High number of high and medium confidence hotspots data resulting into higher fire risk. Result from hotspot data processing is a Fire Level Map which can be used as a basis for disaster management so that the negative impact of fires can be minimized.

Maximum entropy application in predicting the vulnerability of land and forest fires in South Sumatra Province, Indonesia

Land and forest fire disasters impact humans, biodiversity, and the environment. Identification and distribution of land and forest fire vulnerabilities are essential so that disaster mitigation and management can be fast, precise, and prioritized. The research objectives are to identify land and forest fires that occurred in South Sumatra Province in the 2017–2021 period, to identify environmental and anthropogenic variables that influence the occurrence of land and forest fires, and to map the distribution of land and forest fire vulnerability in South Sumatra Province. Land and forest fires use MODIS Hotspots data for 2017–2021. Prediction land and forest fire vulnerability using maximum entropy (Maxent) with predictive variables are climates, topography, soil, vegetation, and anthropogenic. The accuracy of the maxent model uses the AUC value. The number of hotspots with a confidence level of 70% in South Sumatra Province from the 2017–2021 period was 6,778 hotspots, with the highest number of hotspots occurring in 2019 being 5,826 hotspots. Maximum entropy (Maxent) can predict land and forest fires well in South Sumatra with AUC values of 0.807 (training data) and 0.801 (test data). Soil organic carbon, mean temperature of driest quarter, slope, and distance from rivers are essential variables influencing land and forest fires. The areas of land and forest fires vulnerability in South Sumatra Province are not vulnerable at 35,104 km2 (41.28%), low vulnerability at 26,394 km2 (31.04%), medium vulnerability at 15,413 km2 (18.13%), and high vulnerability at 8,119 km2 (9.55%). The districts/cities in South Sumatra Province with the most expansive areas of medium and high vulnerability are Ogan Komering Ilir, Musi Banyuasin, and Banyuasin districts. Data on land and forest fire vulnerability distribution in South Sumatra can be a reference for all parties in land and forest fire mitigation and prevention activities.

Community Participation In Fire Disaster Mitigation In The City Of Banjarmasin

Very heterogeneous community conditions where urban environmental conditions cause areas to become congested and result in environmental conditions that tend to be slums. City environmental conditions, housing, factories and so on must have good access, in order to avoid hazards that will occur such as the danger of residential fires. The development paradigm that exists in Banjarmasin City, the government's role as a provider of public facilities has changed slightly with the community's efforts to participate in assisting the city government in the community-based fire disaster mitigation process. The purpose of this study was to find out how the form of community participation in mitigating fires in the Malay Village, Central Banjarmasin District, Banjarmasin City. This type of research is a qualitative descriptive research. Data collection techniques in this study, researchers used documentation study techniques, guided interviews and direct observation from the field. The data analysis technique that will be used is descriptive qualitative method. The results of the study show that the presence of the self-help Fire Brigade (BPK) has become the identity of the city both at the national and international levels, as a city of a thousand rivers and a city of a thousand firefighters. Community participation is quite diverse and very innovative in reducing the risk of residential fire disasters in Malay sub-districts. Interestingly, the presence of the self-help Fire Brigade (BPK) is unpaid, the members on duty do not get a salary in carrying out this humanitarian task, their participation is sincere and voluntary

Legal Review of the Performance of Firefighters and Rescue Workers in Deli Serdang

Fire and Rescue or abbreviated as Fire and Rescue are implementing elements of the Government which have the responsibility to assist the community in handling fires and rescue. The research objective was to find out the legal review regarding the performance of firefighters and rescue workers in Deli Serdang Regency. And it is necessary to have a legal study on how to deal with fires in accordance with rescue procedures from the government which can create common perceptions and uniformity of ways of acting for all personnel involved. The type of research in this paper is normative with a statutory and conceptual approach. While the specification of the research is analytical descriptive, namely explaining the problem according to the research title. The data used as primary legal materials include Regulation of the Minister of Home Affairs of the Republic of Indonesia Number 16 of 2020 Concerning Nomenclature Guidelines for Provincial and District/City Fire and Rescue Services, and secondary legal materials in the form of books, journals, writings, media , and documents or other information related to the research title. By carrying out the procedures from the government, efficient suppression efforts can be achieved in deploying personnel to minimize losses and work as optimally as possible in blackout operations and rescue operations. Therefore, it is recommended for Firefighters and Rescue Executors to improve performance and timeliness, quality of facilities and infrastructurein tackling fire disasters and better rescue so that more and more people are saved. Especially to improve the procedures, rules and performance of officers to do more optimal fire prevention and rescue so that they run according to community expectations and regulation from government.

Risk Assessment of Fire Hazards in Semarang City Residential Areas

Based on data from the Semarang City Fire Department in 2013-2016, 1028 fire incidents took place in Semarang City. This incidence reached its highest in 2015 with 399 cases of fire which caused material losses of up to IDR 398.3 billion. Based on these figures, Semarang City possesses the highest incidence rate of fire cases in Central Java Province. However, studies on the risk and mitigation of fire hazard disasters in Semarang City still need to be carried out. This study aims to identify fire risks, to mitigate the disaster’s hazards in Semarang City, and to provide recommendations for arranging relevant buildings and the environment. The method used in this study is a qualitative descriptive method, in which interviews are conducted with key persons, with the utilization of GIS analysis to assess the risk of fire. The results of this study exhibit that in Semarang City, 14 villages have a high level of fire hazard risk, one of which is Rejosari Village which has the highest level of fire risk. This occurred mainly because historically, there have been many fire incidents in this area and even claiming several lives. The density of buildings and the difficulty of access further increase vulnerability in the case of fire. Nevertheless, the inhabitants still lack an understanding of this hazard. Accordingly, the fundamental mitigation to be carried out in Rejosari Village is to increase community comprehension and to consider the addition of fire protection and safety facilities, including hydrants, in densely populated buildings and areas, in order to reduce the risk of fire hazards.

Hotspot Spatial Patterns Using SNNP-VIIRS for Fire Potential Monitoring

The province of East Kalimantan is officially designated as the State Capital because the area has the least risk of disaster, even though it cannot be separated from disasters such as forest and land fires. This study aims to determine the spatial pattern of hotspots using SNPP-VIIRS for monitoring potential fires. The research used the descriptive-analytic method to identify the research area and collect secondary data. Secondary data is spatial and nonspatial data consisting of hotspot data from the recording of the SNPP -VIIRS image, including frequency and distribution of hotspots. The data usage from 2012–2021 using SNPP-VIIRS morning and evening recordings. The study results show that the spatial pattern of potential hotspots in the capital city of a new country is quite varied. The spatial pattern of hotspots shows that Kutai Kartanegara Regency as one of the locations for the new State Capital, has the highest number of hotspots, namely 38,970 with the highest accuracy in East Kalimantan Province, namely, 1,616 (low), 36,253 (nominal), and 1,101 (high). The potential for fire disasters in Kutai Kartanegara Regency as an IKN location is high, so planning is urgently needed for future fire prevention, mitigation, and prevention strategies. The spatial pattern of hotspots is known, so it can be used to monitor potential fires and minimize fire occurrences.

Framework for Fire Safety Management of Hotels in Nigeria: A Structural Equation Modeling Approach

Recent findings indicate Nigeria is among the top countries with devastating consequences of fire incidences. The volatile position of Port-Harcourt as an oil-producing capital city is seen as one of the reasons why fire disasters occur in hotels, among other high rises institutional building structures. This study, therefore, explored the factors responsible for the high incidences of fires in Port-Harcourt, Nigeria. As phenomenological research involving humans, a 5-point Likert scale cross-sectional questionnaire survey instruments were developed using online Google forms to evaluate people's awareness, identify the material factors that promote fire incidents, and assess the present policy and standards to control fire incidents. The ordinal scaled data collected from 108 respondents were tested to be reliable with a Cronbach alpha of 0.958 using the SPSS Statistic software and further analyzed using the Structural Equation Modelling approach. Results show that hotel workers in Port-Harcourt are aware of fire safety management issues, though periodic retraining is required as new technologies evolve. Safety standards are also relatively maintained in the placement of equipment power points, extinguishers, and emergency controls. However, the significant causes of the fire were attributed to electrical and mechanical devices installed and utilized on the hotel premises. While the study calls for the installation of high-quality equipment in hotels, more inquiry is needed to check the reliability of individual equipment. A framework was finally conceptualized for further research and replicating the study in other contexts. This study's findings are essential to hotel entrepreneurs and managers, fire experts, building designers, and researchers.

Emergency Response Demand and Supply: A GIS-Based Network Analysis for Fire Station’s Service Coverage Delineation in Kano Metropolis, Nigeria

Inadequate fire emergency response infrastructure and a lack of defined service coverage remain key barriers to timely fire disaster response. This study is applied research which employed geospatial techniques and aimed at examining fire disaster emergency response demand and supply relationships with the view to delineating service coverage and locating more facilities for optimum coverage in Kano metropolis. Locations of the existing fire stations and fire incidents (2009-2019) were gathered through GPS surveying. Network data set were generated. Nearest Neighbor and Network Analysis (origin-destination, service coverage and location-allocation) were conducted to determine emergency response demand and supply relationships, service coverage area delineation and identifying best site for allocating new facilities within the metropolis respectively. It was found that no clearly defined service coverage exist as emergency response supply takes more than 4-8 times the NFPA travel standard, and with a great deal of overlapping response patterns. New service coverage areas were proposed and best sites for 8 firefighting facilities identified for optimum coverage. It is concluded that emergency fire disaster response demand and supply relationships within Kano metropolis is imbalanced, with extensive recurrent demand especially within the core area served by overstretched and inefficient response supply. This, therefore, implies continuous exposure of lives and properties to the menace of fire disaster in Kano metropolis.
 Keywords: Fire Facilities; Location-allocation; Response Demand; Response Supply; Service Coverage
 
 Copyright (c) 2023 Geosfera Indonesia and Department of Geography Education, University of Jember
 This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License

Detecting, Monitoring and Foreseeing Wildland Fire Requires Similar Multiscale Viewpoints as Meteorology and Climatology

Achieving sustainable coexistence with wildfires in the Anthropocene requires skilful integrated fire observations, fire behaviour predictions, forecasts of fire risk, and projections of change to fire climates. The diverse and multiscale approaches used by the atmospheric sciences, to understand geographic patterns, temporal trends and likely trajectories of weather and climate, provide a role model for how multiscale assessments of fire danger can be formulated and delivered to fire managers, emergency responders and at-risk communities. Adaptation to escalating risk of fire disasters requires specialised national agencies, like weather services, that provide to provide a diverse range of products to enable detection and near and longer-range prediction of landscape fire activity.

INFORMATION MEDIA AS A PUBLIC COMMUNICATION IN FIRE MITIGATION IN SOUTH KALIMANTAN

South Kalimantan is one of the regions in Indonesia that has a high vulnerability to fire disasters. The Fire Disaster Management Agency is an agency that has a major role as an early warning system in the process of mitigating fire disasters in South Kalimantan. The purpose of this study was to determine the use of the five elements of communication according to Harold Laswell and information media as a public communication channel carried out by the Regional Disaster Management Agency/ Badan Penanggulangan Bencana Daerah (BPBD) of South Kalimantan. The research method used was a qualitative descriptive approach. The results show that in the process of mitigating fire disasters in South Kalimantan Province, the Regional Disaster Management Agency/ Badan Penanggulangan Bencana Daerah (BPBD) of South Kalimantan Province has carried out a public communication process by implementing all elements of communication and presenting Information Media as a communication channel through direct communication with the community in the area. disaster or using conventional communication channels such as leaflets, disaster pocketbooks as well as mass and digital media communication channels such as radio and social media