EFICIÊNCIA DE COMBATE AOS INCÊNDIOS FLORESTAIS EM UNIDADES DE CONSERVAÇÃO BRASILEIRAS

A precariedade dos planos de combate aos incêndios florestais, torna o fogo a principal ameaça às Unidades de Conservação. Os Registros de Ocorrência de Incêndios (ROIs) são estratégias para aumentar a eficiência no enfrentamento aos incêndios. Assim, com a presente pesquisa objetivou-se analisar a eficiência de combate aos incêndios florestais em Unidades de Conservação brasileiras. Foram utilizados os ROIs do Sistema Nacional de Informações sobre Fogo referentes ao intervalo de 2010 a 2020. Foram avaliados o número de ROIs completos e incompletos, tipos de detecção, quantidade de área queimada, tempo de detecção, de ataque e de combate. Os resultados evidenciaram que apenas 52,33% dos ROIs estavam completos e que 2019 foi o ano com mais ROIs completos. Os pontos de observação e a ronda foram os principais métodos de detecção. As unidades de conservação brasileiras sofreram com a destruição de 31.918.617,41 hectares no período analisado, que significa índice de severidade extremo. Conclui-se que as unidades de conservação brasileiras apresentam baixa eficiência de combate aos incêndios florestais, principalmente de ataque inicial e combate, sendo necessário melhorar a eficiência da detecção e combate, infraestrutura, realizar treinamentos e conscientização sobre a importância dos ROIs. Palavras-chave: proteção florestal; registro de ocorrência de incêndios; áreas protegidas. Firefighting efficiency in Brazilian Protected Areas ABSTRACT: The precariousness of plans to combat forest fires, makes fire the main threat to Protected areas. Fire Occurrence Records (ROIs) are strategies to increase efficiency in fighting fires. Thus, we aimed analyze the efficiency of fighting forest fires in Brazilian Protected Areas. ROIs by National Fire Information System for the period 2010 to 2020 were used. The number of complete and incomplete ROIs, types of detection, amount of area burned, time of detection, attack and combat were evaluated. The results showed that only 52.33% of the ROIs were complete and that 2019 was the year with the most complete ROIs. Observation points and patrol were the main detection methods. Brazilian protected areas suffered from the destruction of 31,918,617.41 hectares in the analyzed period, which means an extreme severity index. It is concluded that Brazilian protected areas have low efficiency in combating forest fires, mainly in initial attack and combat, and it is necessary to improve the efficiency of detection and combat, infrastructure, conduct training and awareness about the importance of ROIs. Keywords: forest protection; record of fire occurrences; protected areas.

Development of Smart Evacuation System for Fire Response in Apartments

A smart evacuation system is developed herein to reduce damage to lives and property by inducing rapid evacuation of the residents in the event of apartment fires. The smart evacuation system provides a safe evacuation environment and the best physical evacuation conditions by detecting the loads to be applied to evacuation facilities at all times. In addition, fire information is automatically disseminated to the residents and managers during a fire for initial evacuation, and the function for early fire extinguishing is enabled via report to the 119 situation room. The smart evacuation system comprises a safety ladder for evacuation, an ideal detection system to detect obstructions in the evacuation facilities, and a communication system to quickly inform authorities, residents, and managers of a fire. To verify effective performance of the safety ladder, real safety ladders were constructed and their structural performance and usability were verified. In addition, to ensure their permanent space in evacuation facilities, we verified that obstructions to evacuation were accurately detected as anomalies in real time using contactless sensors and communication modules. Finally, the fire information was sent to residents and managers in case of a fire to assist evacuation as well as reported to 119 for rapid suppression. Thus, we demonstrate that the smart evacuation system allows safe and effective evacuation with fast and accurate information in the event of a fire and is useful for initial response for fire suppression.

Fire hazard assessment with indoor spaces for evacuation route selection in building fire scenarios

A safe and effective evacuation route is important for reducing casualties during building fires, and this topic has been a long-term focus of emergency management. Indoor space is a space within one or multiple buildings consisting of architectural components and is the basis of indoor route analyses. Based on indoor space, an indoor network model is designed that considers fire protection design, spatial matching between fire information and the indoor space, and the passability of the indoor space during a fire. Then, an evacuation route selection algorithm that considers hazard and time is proposed. The key features of the route selection algorithm, which include assessing the fire hazards, evacuation time in each indoor space and parallel computing in the route selection algorithm, are subsequently presented. Finally, taking a gymnasium as an example, case modelling and fire information integration are performed to investigate two fire scenarios and the optimal evacuation routes over time are identified in each scenario.

Copernicus data for wildfire mapping and monitoring in Ireland

<p>Although wildfires in Ireland are not extensive, information on their impacts in terms of atmospheric emissions and pollutants, and habitat losses is essential.  Current ground-based wildfire data are limited by their incompleteness, inconsistency in reporting, and a lack of timeliness. Additional data on fire alerts are drawn from international satellite derived databases such as NASA’s Fire Information for Resource Management System (FIRMS) and the European Forest Fire Information System (EFFIS) to produce a more consistent national summary. However, these databases exploit thermal anomalies derived from low spatial resolution satellite imagery, which can result in a large number of omissions of small, short-lived fires, especially when extensive cloud-cover persists, as is common in Ireland. To overcome these limitations, a new approach is proposed whereby data from the Copernicus Atmosphere Monitoring Service (CAMS) are used to identify atmospheric pollutant anomalies that may be associated with a wildfire, with Sentinel-2 pre- and post-fire imagery providing a more detailed account of the area burned and the vegetation cover affected. An inventory of fire events in Ireland reported by local and social media and the FIRMS and EFFIS databases from 2015-2020 was compiled. The average hourly concentration of selected pollutants (CO, O3, PM2.5, PM10, SO2, NOx) was derived from the CAMS European air quality analysis product at the location of each fire shortly before, during, and after the event. The average concentrations for the same period from the years excluding the year of the fire being studied were compared to the pollutant concentrations observed during the event. Preliminary results suggest that the concentration of PM2.5, PM10, SO2, and NOx show the clearest deviations from the baseline during the occurrence of a fire. Clear-sky Sentinel-2 images preceding and after selected fires were identified, and a number of different indices (NBR, dNBR, RdNBR, dMIRBI) calculated and combined to delineate burn event areas. Post-processing was undertaken to remove errors due to water, shadow and cloud cover, and eliminate features less than 0.4ha in size. Preliminary results show that burn scars can be clearly distinguished and their areas calculated, including fire events omitted from the 2015-2020 inventory. However, false alarms arise from natural land cover change, especially agricultural activity, and attempts to exclude these are being explored using the national mapping agency’s object-oriented digital mapping data model, PRIME2. Further analysis of the Sentinel-2 imagery to map the habitats burned is in progress, with a particular focus on identifying the location of gorse (Ulex europaeus), which is highly flammable in dry summer conditions due to the presence of deadwood. Atmospheric chemistry colleagues are undertaking a field campaign during 2021 to monitor the air quality during a burn event, along with laboratory measurements in a burn chamber, from which emissions factors for gorse can be calculated. Subsequently, it is hoped that detailed estimates of emissions from upland wildfires can be derived leading to improved national GHG inventories, and an assessment of these events made in terms of atmospheric impacts on population centres and environmental impacts on habitats and biodiversity.</p>

Rancang Bangun Alat Peringatan Dini Dan Informasi Lokasi Kebakaran Berbasis Arduino Uno

Bahaya kebakaran adalah bahaya yang diakibatkan oleh adanya ancaman potensial dan derajat terkena pancaran api sejak dari awal terjadi kebakaran hingga penjalaran api, asap dan gas yang ditimbulkan. Kebakaran adalah terjadinya api yang tidak dikehendaki. Proses informasi adanya kebakaran pada umumnya masih memakai cara manual, hal ini dilakukan karena belum memanfaatkan kecanggihan teknologi yang sekarang ini sangat berkembang pesat. Informasi kebakaran ini kurang cepat dan tepat khususnya pada satuan pemadam kebakaran. Tujuan dari penelitian ini adalah merancang sistem yang dapat digunakan untuk menginformasikan kebakaran dengan cepat beserta informasi lokasi pada tempat terjadinya kebakaran. Metode yang digunakan dalam penelitian ini yaitu metode eksperimen dan perancangan baik dalam pembuatan perangkat keras serta perangkat lunak pendukungnya. Perangkat kerasnya menggunakan sensor api, sensor asap dan sensor suhu, dan menginformasikan melalui modul GSM serta modul GPS untuk membaca koordinat lokasi kebakaran. Hasil dari perancangan alat peringatan dini dan informasi lokasi kebakaran berbasis arduino uno bekerja dengan baik. Pada alat pengirim, saat kondisi ada api, ada asap dan suhu diatas 50 derajat alat mengirimkan sms untuk menyalakan alat penerima dan sms link google maps lokasi kebakaran. Pada alat penerima, saat alat menerima sms dari alat pengirim, alat akan menyalakan buzzer. Alat bekerja sesuai dengan yang telah direncanakan dan bisa digunakan untuk mendeteksi adanya kebakaran. Fire hazard is a danger that is caused by the potential threat and the degree of exposure to fire from the start of a fire to the spread of fire, smoke, and the gas it causes. Fire is a fire incident that is not desired. In general, the information process for fires still uses the manual method, this is done because it has not taken advantage of the sophistication of technology which is now very rapidly developing. This fire information is not fast and accurate, especially for fire fighting units. The purpose of this research is to design a system that can be used to quickly inform fires along with location information at the scene of the fire. The method used in this research is the experimental method and design both in hardware and supporting software. The hardware uses fire sensors, smoke sensors, and temperature sensors, and informs via GSM module as well as the GPS module to read the coordinates of the fire location. The results of the design of early warning tools and fire location information based on Arduino Uno worked well. On the sending device, when there is a fire, there is smoke and the temperature is above 50 degrees, the device sends an SMS to the receiving device and the SMS link on the google maps location of the fire. On the receiving device, when the device receives an SMS from the sending device, the device will create a buzzer. The tool works as planned and can be used to check for fires.

BURNT AREA DETECTION USING MEDIUM RESOLUTION SENTINEL 2 AND LANDSAT 8 SATELLITES

Forest fire is one of the most serious environmental problems in Kenya that influences human activities, climate change and biodiversity. The main goal of this study is to apply medium resolution sensors (Landsat 8 OLI and Sentinel 2 MSI) to produce burnt area severity maps that will include small fires (< 100 ha) in order to improve burnt area detection and mapping in Kenya. Normalized burnt area indices were generated for specified pre- and post-fire periods. The difference between pre- and post-fire Normalized Burnt Ration (NBR) was used to compute δNBR index depicting forest disturbance by fire events. Thresholded classes were derived from the computed δNBR indices to obtain burnt severity maps. The spatial and temporal agreements of the Burnt area detection dates were validated by comparing against the MODIS MCD641 500 m products and MODIS Fire Information for Resource Management System (FIRMS) 1 km daily product hot-spot acquisition dates. This approach was implemented on Google Earth Engine (GEE) platform with a simple user interface that allows users to auto-generate burnt area maps and statistics. The operational GEE application developed can be used to obtain burnt area severity maps and statistics that allow for initial accurate approximation of fire damage.