• Journal of Forest and Environmental Science
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• v.40 no.1
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• pp.24-34
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• 2024

Fire, being primarily a natural phenomenon, is impossible to control, although it is feasible to map the forest fire risk zone, minimizing the frequency of fires. The spread of a fire starting in any stand in a forest can be predicted, given the burning conditions. The natural cover of the land and the safety of the population may be threatened by the spread of forest fires; thus, the prevention of fire damage requires early discovery. Satellite data and geographic information system (GIS) can be used effectively to combine different forest-fire-causing factors for mapping the forest fire risk zone. This study mainly focuses on mapping forest fire risk in the Madikhola watershed. The primary causes of forest fires appear to be human negligence, uncontrolled fire in nearby forests and agricultural regions, and fire for pastoral purposes which were used to evaluate and assign risk values to the mapping process. The majority of fires, according to MODIS events, occurred from December to April, with March recording the highest occurrences. The Risk Zonation Map, which was prepared using LULC, Forest Type, Slope, Aspect, Elevation, Road Proximity, and Proximity to Water Bodies, showed that a High Fire Risk Zone comprised 29% of the Total Watershed Area, followed by a Moderate Risk Zone, covering 37% of the total area. The derived map products are helpful to local forest managers to minimize fire risks within the forests and take proper responses when fires break out. This study further recommends including the fuel factor and other fire-contributing factors to derive a higher resolution of the fire risk map.

• Korean Journal of Remote Sensing
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• v.17 no.4
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• pp.359-368
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• 2001

The prototype of forest fire management system on Web was studied. In the architecture of this system, one of the most important concerns is to handle load upcoming to Web Server so that it provides Web service without any delay or failure. In order to solve this problem, the agent is designed on dispatcher in a Web server cluster and implemented to distribute load dynamically by considering the information related to load coming to the Web Server such as the number of connection to the Map Server. The proposed forest fire management system has user-friendly interface with the GIS mapping functionality by selecting Map Objects Internet Map Server (MO IMS) as Map Server and is implemented using Java as programming language.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.687-690
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• 2005

Recently there have been a lot of kinds of damages in forest area such as forest fires, forest pest, landslide so that the efficient methods to mange those information and the way to face them are deadly needed. In this study, there were preparing the various vegetation index map and comparing them with the field surveying the tried to figure out which vegetation index algorism is the best proper to present forest fire damaged area. These all were based on Landsat ETM+ satellite image (2000.10.16). The result of this study is to select the high correlation algorism among the various vegetation indexes and then construct the forest fire disaster map, the case of forest fires damaged area.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.328-330
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• 2003

The land cover of burned area has changed dramatically since Daxinganling forest fire in Northeastern China during May 6 ? June 4, 1987. This research focused on determining the burn severity and assessment of forest recovery. Burned severity was classified into three levels from June 1987 Landsat TM data acquired just after the fire. A regression model was established between the forest canopy closure from 1999 forest stand map and the NDVI values from June 2000 Landsat ETM+ data. The map of canopy closure was got according to the regression model. And vegetation cover was classified into four types according to forest closure density. The change matrix was built using the classified map of burn severity and vegetation recovery. Then the change conversions of every forest type were analyzed. Results from this research indicate: forest recovery status is well in most of burned scars; and vegetation change detection can be accomplished using postclassification comparison method.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.537-540
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• 2004

Space-borne multi-sensor data could provide fire scar and bum severity mapping. This paper will present detail mapping of burnt areas in Cheongyange Yesan of Korea with ETM+ image. Burn severity map based on ETM+ image was found to be affected by strong topographic illumination effects in mountainous forest area. Topographic effect is a factor which causes errors in classification of high spatial resolution image like IKONOS image. Minnaert constants J( in each band of ETM+ image is derived for reduction of mountainous terrain effects. Finally, this paper computes quantitative analysis of forest fire damage by each forest types.

• Journal of Korean Society of Forest Science
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• v.101 no.1
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• pp.1-6
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• 2012

To achieve the forest fire management goals such as early detection and quick suppression, fire resources should be allocated at high probability area where forest fires occur. The objective of this study was to develop and validate models to estimate spatially distributed probabilities of occurrence of forest fire. The models were builded by exploring relationships between fire ignition location and forest, terrain and anthropogenic factors using logistic regression. Distance to forest, cemetery, fire history, forest type, elevation, slope were chosen as the significant factors to the model. The model constructed had a good fit and classification accuracy of the model was 63%. This model and map can support the allocation optimization of forest fire resources and increase effectiveness in fire prevention and planning.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.3
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• pp.126-135
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• 2011

In this study, the algorithm for priority area of forest fire surveillance was developed to enhance the effectiveness of fire detection. The high priority surveillance area for forest fire detection was defined as the area with not only low value of viewshed analysis of the lookouts and detection cameras but also high fire occurrence probability. To build the priority map, fuzzy function and map algebra were used. The analysis results of Bonghwa-gun, Gyeongbuk Province, showed that the surveillance priority of central and southern area is higher than north area. This algorithm could be used in the allocation of fire prevention resources and selection of suitable point for new fire detection system.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.1
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• pp.21-28
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• 2010

Forest fire is one of the main factor disturbing the environment of forest, and it influences greatly the structure and function on forest. The process of vegetation recovery could be decided according to the extent of the damage. It is required a lot of man powers and budgets to understand born severity and process of vegetation rehabilitation at the damaged area after large-fire. However, the analysis of born severity in the forest area using satellite imagery can acquire rapidly information and more objective results remotely in the large-fire area. In this study, the space sensors have been used to map area burned, assess characteristics of active fires. For classifying fire damaged area and analyzing severity of Cheongyang-Yesan fire in 2002, in this paper we use pre- and post-fire imagery from the Landsat TM and ETM+ to compute the evaluate large-scale patterns of burn severity, use the digital stock map to calculate the damaged condition about the forest fires damaged regions and use the NDVI to monitoring the situation of the revegetation.

• Journal of the Korean Association of Geographic Information Studies
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• v.5 no.4
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• pp.93-105
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• 2002

In this paper forest fire status information management system was developed under web environment using web GIS(geographic information system) technology. Though this system, general users can easily retrieval domestic forest fire status information and obtain that in visual way such as maps, graphs, and texts if they have only certain web browsers. Moreover, officials, who have system access authority, can easily control and manage all domestic forest fire status information through input interface, retrieval interface, and out interface of the system. This system can be considered as the first domestic system to manage forest fire status data and service them in visual through user friendly interfaces on web. In order to implement this system, IIS 5.0 of Microsoft is used as web server and Oracle 8i and ASP(active server page) are used for database construction and dynamic web page operation, respectively. Also, ArcGIS IMS(internet map server) of ESRI is used to serve maps by using Java and HTML as system development languages. Not only the domestic tendency of forest fire but also the forest fire status information of certain area and time such as the frequency and the loss can be presented through distribution maps, graphs and tables. Therefore, this system is supposed to play as a important role when the policy relate to domestic forest fire is established. In addition, the self consciousness of people against forest fire can be inspired and the foundation of scientific and systemic forest fire services can be obtained through this system in the future.

• The Journal of Engineering Geology
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• v.34 no.1
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• pp.107-115
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• 2024

This study assesses forest fire susceptibility in Gangwon-do, South Korea, which hosts the largest forested area in the nation and constitutes ~21% of the country's forested land. With 81% of its terrain forested, Gangwon-do is particularly susceptible to wildfires, as evidenced by the fact that seven out of the ten most extensive wildfires in Korea have occurred in this region, with significant ecological and economic implications. Here, we analyze 480 historical wildfire occurrences in Gangwon-do between 2003 and 2019 using 17 predictor variables of wildfire occurrence. We utilized three machine learning algorithms—random forest, logistic regression, and support vector machine—to construct wildfire susceptibility prediction models and identify the best-performing model for Gangwon-do. Forest and soil map data were integrated as important indicators of wildfire susceptibility and enhanced the precision of the three models in identifying areas at high risk of wildfires. Of the three models examined, the random forest model showed the best predictive performance, with an area-under-the-curve value of 0.936. The findings of this study, especially the maps generated by the models, are expected to offer important guidance to local governments in formulating effective management and conservation strategies. These strategies aim to ensure the sustainable preservation of forest resources and to enhance the well-being of communities situated in areas adjacent to forests. Furthermore, the outcomes of this study are anticipated to contribute to the safeguarding of forest resources and biodiversity and to the development of comprehensive plans for forest resource protection, biodiversity conservation, and environmental management.