• Journal of Korean Society of Forest Science
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• v.100 no.1
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• pp.70-78
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• 2011

In this study, we develop a fire stochastic simulation model by season based on the historical fire data in Korea. The model is utilized to generate sequences of fire events that are consistent with Korean fire history. We employ a three-stage approach. First, a random draw from a Bernoulli distribution is used to determine if any fire occurs for each day of a simulated fire season. Second, if a fire does occur, a random draw from a geometric multiplicity distribution determines their number. Last, ignition times for each fire are randomly drawn from a Poisson distribution. This specific distributional forms are chosen after analysis of Korean historical fire data. Maximum Likelihood Estimation (MLE) is used to estimate the primary parameters of the stochastic models. Fire sequences generated with the model appear to follow historical patterns with respect to diurnal distribution and total number of fires per year. We expect that the results of this study will assist a fire manager for planning fire suppression policies and suppression resource allocations.

• Journal of Forest and Environmental Science
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• v.25 no.3
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• pp.177-185
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• 2009

Dryland species and ecosystems have developed unique strategies to cope with low and sporadic rainfall. They are highly resilient and recover quickly from prevailing disturbances such as fires, herbivore pressure and drought. Dryland people have engineered pastoral and farming systems, which are adapted to these conditions and have sustained the livelihoods of dryland people for centuries. In this article, we present the status of potentials and threats to dryland biodiversity and explore options for its conservation and sustainable use. Findings of the research can be summarized as follows: (i) The ecosystem goods and services are highly valued by the community but mechanism for wise use of the resources has disappeared, (ii) forests are under the ownership of the government but the local community is the realistic custodian of the forests through village leaderships and environmental committees; (iii) the immediate major threat to dryland biodiversity held in the forests appears to be the degradation of ecosystems and habitats caused by new and powerful forces of environmental degradation such as large scale irrigation of rice farms, poverty-induced overexploitation of natural resources, and disappearance and ignorance of traditional institutions for management of dryland biodiversity. These new forms of disturbances often overpower the legendary resilience of dryland ecosystems and constitute potentially serious threats to dryland biodiversity. Forests, wetlands and oases all of which are micro hot spots of dryland biodiversity, appear to be particularly vulnerable hence the need to set up some rules and regulations for sustainable utilization of these resources.

• Journal of Korean Society for Atmospheric Environment
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• v.31 no.1
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• pp.83-91
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• 2015

Biomass burning is known to be one of the main sectors emitting greenhouse gases as well as air pollutants. Unfortunately, the inventory of biomass burning sector has not been established well. We estimated greenhouse gas (GHG) and air pollution (AP) integrated emissions from biomass burning sector in Seoul during year 2010. The data of GHG and AP emissions from biomass burning, classified into open burning, residential fireplace and wood stove, meat cooking, fires, and cremation, were obtained from Statistics Korea and Seoul City. Estimation methodologies and emission factors were gathered from reports and published literatures. Estimated GHG and AP integrated emissions during year 2010 were $3,867tonCO_{2eq}$, and 2,320 tonAP, respectively. Major sources of GHG were forest fires ($1,533tonCO_{2eq}$) and waste open burning ($1,466tonCO_{2eq}$), while those of AP were meat cooking (1,240 tonAP) and fire incidence (907 tonAP). Total emissions by administrative district in Seoul, representing similar patterns in both GHG and AP, indicated that Seocho-gu and Gangseo-gu were the largest emitters whereas Jung-gu was the smallest emitter, ranged in $2{\sim}165tonCO_{2eq}$ and 0.1~8.31 tonAP. GHG emissions per $km^2$ showed different results from total emissions in that Gwanak-gu, Jungnang-gu, Gangdong-gu and Seodaemun-gu were the largest emitters, while Seocho-gu and Gangseo-gu were near-averaged emission districts, ranged in $0.2{\sim}21tonCO_{2eq}/km^2$. However, AP emissions per $km^2$ revealed relatively minor differences among districts, ranged in $2.3{\sim}6.1tonAP/km^2$.

• Asian Journal of Atmospheric Environment
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• v.7 no.1
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• pp.25-37
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• 2013

Open biomass burning (excluding biofuels) is an important contributor to air pollution in the Asian region. Estimation of emissions from fires, however, has been problematic, primarily because of uncertainty in the size and location of sources and in their temporal and spatial variability. Hence, more comprehensive tools to estimate wildfire emissions and that can characterize their temporal and spatial variability are needed. Furthermore, an emission processing system that can generate speciated, gridded, and temporally allocated emissions is needed to support air-quality modeling studies over Asia. For these reasons, a biomass-burning emissions modeling system based on satellite imagery was developed to better account for the spatial and temporal distributions of emissions. The BlueSky Framework, which was developed by the USDA Forest Service and US EPA, was used to develop the Asian biomass-burning emissions modeling system. The sub-models used for this study were the Fuel Characteristic Classification System (FCCS), CONSUME, and the Emissions Production Model (EPM). Our domain covers not only Asia but also Siberia and part of central Asia to assess the large boreal fires in the region. The MODIS fire products and vegetation map were used in this study. Using the developed modeling system, biomass-burning emissions were estimated during April and July 2008, and the results were compared with previous studies. Our results show good to fair agreement with those of GFEDv3 for most regions, ranging from 9.7 % in East Asia to 52% in Siberia. The SMOKE modeling system was combined with this system to generate three-dimensional model-ready emissions employing the fire-plume rise algorithm. This study suggests a practicable and maintainable methodology for supporting Asian air-quality modeling studies and to help understand the impact of air-pollutant emissions on Asian air quality.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.483-490
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• 2019

Assessing the effect of forest fires and measuring the gas concentration around a fire has received little attention. Therefore, the concentrations of various gases in areas surrounding a fire need to be measured by the development of a suitable device. Unlike conventional portable devices, the AQS (Air Quality System) proposed in this paper is a portable instrument that measures five types of gases simultaneously, including CO, CO2, NOx, VOCs, and NH3, and has high durability through sensor protection algorithms. A PC-based program with an AQS connection was developed to monitor the real-time changes in the gas concentration. The reliability of the developed device was proven through a comparison of the results with other commercial gas analyzers. Measurements of the concentration due to indoor and outdoor fires were performed around a fire area to review the applicability and the predicted results were obtained.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.843-847
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• 2023

In this paper, we propose a model for detecting efficient fire identification to prevent fires that can lead to various industrial accidents, farmland and large forest fires, with the widespread use of various chemicals and flammable substances as modern technology advances. This paper presents an algorithm that can detect fire smoke in a high-efficiency and short time using images, and an algorithm based on SVM(Support Vector Machine) and K fold cross-verification technologies. By analyzing images, fire and smoke detection algorithms have relatively superior detection performance compared to existing algorithms, and the analysis of fire and smoke characteristics detected in this paper is analyzed stably and efficiently and is expected to be used in various fields that may be exposed to fire risks in the future.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1299-1308
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• 2023

Forest fires are becoming more frequent and larger around the world due to climate change. Remote sensing such as satellite images can be used as an alternative or assistance data because it reduces various difficulties of field survey. Forest burn severity (differenced normalized burn ratio, dNBR) is calculated through the difference in normalized burn ratio (NBR) before and after a forest fire. The images used in the NBR formula are based on Landsat's near-infrared (NIR) and short-wavelength infrared (SWIR) bands. South Korea's satellite images don't have a SWIR band. So domestic studies related to forest burn severity calculated dNBR using overseas images or indirectly using the normalized difference vegetation index (NDVI) using South Korea's satellite images. Therefore, in this study, dNBR was calculated by substituting the mid-wavelength infrared (MWIR) band of Kompsat-3A (K3A) instead of the SWIR band in the NBR formula. The results were compared with the dNBR results obtained through Landsat which is the standard for dNBR formula. As a result, it was shown that dNBR using K3A's MWIR band has a wider range of values and can be expressed in more detail than dNBR using Landsat's SWIR band. Therefore, it is considered that K3A images will be highly useful in surveying burn areas and severity affected by forest fires. In addition, this study used the K3A's MWIR band images degraded to 30 m. It is considered that much better results will be obtained if a higher-resolution MWIR band is used.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.208-220
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• 2016

Automatic Mountain Meteorology Observation System (AMOS) is an important ingredient for several climatological and forest disaster prediction studies. In this study, we select the optimal sites for AMOS in the mountain areas of Honam and Jeju in order to prevent forest disasters such as forest fires and landslides. So, this study used spatial dataset such as national forest map, forest roads, hiking trails and 30m DEM(Digital Elevation Model) as well as forest risk map(forest fire and landslide), national AWS information to extract optimal site selection of AMOS. Technical methods for optimal site selection of the AMOS was the firstly used multifractal model, IDW interpolation, spatial redundancy for 2.5km AWS buffering analysis, and 200m buffering analysis by using ArcGIS. Secondly, optimal sites selected by spatial analysis were estimated site accessibility, observatory environment of solar power and wireless communication through field survey. The threshold score for the final selection of the sites have to be higher than 70 points in the field assessment. In the result, a total of 159 polygons in national forest map were extracted by the spatial analysis and a total of 64 secondary candidate sites were selected for the ridge and the top of the area using Google Earth. Finally, a total of 26 optimal sites were selected by quantitative assessment based on field survey. Our selection criteria will serve for the establishment of the AMOS network for the best observations of weather conditions in the national forests. The effective observation network may enhance the mountain weather observations, which leads to accurate prediction of forest disasters.

• Korean Journal of Plant Resources
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• v.30 no.1
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• pp.110-123
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• 2017

The authors reviewed the history of creation and management, purposes, extents, methods of creation, planting species and mediums, structure of vegetation layers and legal management, etc. of coastal forests of Korea. Since the Goryeo dynasty, the inhabitants in the coastal regions has long been aware the safety from natural disasters and the local governments manages for the defence and natural disasters, and collaboration among GO and NGOs, as well as enterprises are participating to the conservation of coastal forests in Korea. The purposes of creation and management of coastal forests in historical aspects are prevention of disasters, safety by the Fengsui, military uses, and timber productions, but partly as the places for religious beliefs, safety from diseases and fires, increasing of forest products and fishes, as well as tourists, improving of amenity and landscapes and recreation, inherits of traditional culture, habitats for wildlife, and ecological corridors, etc. The inhabitant in the coastal region who experienced frequent natural disasters has strong supports for the conservation of coastal forest and as a natural resources to inherits to the coming generations as the coastal forests has high values of academic researches on human society, culture, ecology and recreational uses, etc. The extensive overall researches on the creation and managements of coastal forests, as well as cultural tradition in the coastal forests of Korean peninsula are critically essential.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.6
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• pp.1506-1514
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• 2015

In this paper, we proposed a forest fires prediction and detection system. It could provide a situation of fire prediction and detection methods using context awareness sensor. A fire occurs wide range of sensing a fire in a single camera sensor, it is difficult to detect the occurrence of a fire. In this paper, we propose an algorithm for real-time by using a temperature sensor, humidity, Co2, the flame presence information acquired and comparing the data based on multiple conditions, analyze and determine the weighting according to fire in complex situations. In addition, it is possible to differential management of intensive fire detection and prediction for required dividing the state of fire zone. Therefore we propose an algorithm to determine the prediction and detection from the fire parameters as an temperature, humidity, Co2 and the flame in real-time by using a context awareness sensor and also suggest algorithm that provide the path of fire diffusion and service the secure safety zone prediction.