• 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.

• Journal of Life Science
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• v.13 no.5
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• pp.740-745
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• 2003

The vegetation of Mt. Geum in Namhae-gun Gyeongsangnam-do was investigated by the methodology of the ZM school, from February, 2000 to May, 2002. An actural vegetation map and vegetation table were constructed to understand the distribution of plant community in this area. The vegetation in this study area was classified into 10 communities (Pinus. densiflora, P. thunbergii, Quercus acutissima, Q. serrata, Q. variablis, Q. mongolica, Styrax ja-ponica, Corylopsis coreana, Zelkova serrata and Carpinus tschonoskii) and 1 afforestation (Chamaecyparis obtusa). According to the actual vegetation map, P. thunbergii forest, Q. serrata forest and Q. mongolica forest were found at the southern slope, northern slope and the center region of Mt. Geum, respectively. The forest of P. thunbergii was widely distributed in this area.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.10 no.5
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• pp.20-30
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• 2007

Environmental Conservation Value Assessment Map (ECVAM) is the class map to divide the national land into conservation areas and development areas based on legal and ecological assessment criteria. It contributes to enhancements of the efficiency and the scientificity when framing a policy in various fields including the environment. However, it is impossible to understand the multiphase vegetation structure as data on judging the national forest class in ECVAM are restricted to areal information of Ecological Nature Status, Degree of Green Naturality and Forest Map. This point drops the reliability of ECVAM. Therefore we constructed vegetation information using LiDAR (Light Detection And Raging) technology. We generated Biomass Class Maps as final results of this study, to introduce the new forest assessment criterion in ECVAM that alternates or makes up for existing forest assessment criteria. And then, we compared these with Forest Map and Landsat TM NDVI image. As a result, biomass classes are generally higher than stand age classes and DBH classes of Vegetation Map, and lower than NDVI of Landsat TM image because of the difference of time on data construction. However distributions between these classes are mostly similar. Therefore we estimates that it is possible to apply the biomass item to the new forest assessment criterion of ECVAM. The introduction of the biomass in ECVAM makes it useful to detect the vegetation succession, to adjust the class of the changed zone since the production of Vegetation Map and to rectify the class error of Vegetation Map because variations on tree heights, forest area, gaps between trees, vegetation vitality and so on are acquired as interim findings in process of computing biomass.

• 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 Korean Society for Geospatial Information Science
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• v.14 no.3 s.37
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• pp.23-30
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• 2006

The case of a forest area has tome limitations of adopting a ground surveying like as TS (Total Station) and RTK-GPS (Real Time Kinematic-GPS) due to the specificity of the forest area. Therefore, the new method, is different from exist the cadastral re-surveying method in a metro area and a cropland, is applicably considered in the forest area. In this paper, we suggest the applicability of the digital cadastral map of forest which is used at KLIS. According to the result of study, the most important area error value for adopted in the cadastral re-surveying is almost contained the error tolerance. Therefore, KLIS data, if it is related with the actual reference data for adjusting the location boundary, is suitable to be adopted in the cadastral re-surveying.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.198-200
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• 2003

This study proved if the high resolution satellite imagery of IKONOS is suitable for preparing digital forest cover map. Three methods, the pixel based classification with maximum likelihood (PML), the segment based classification with majority principle(SMP), and the segment based classification with maximum likelihood(SML), were applied to classify and delimitate forest cover of IKONOS imagery taken in May 2000 in a forested area in the central Korea. The segment-based classification was more suitable for classifying and deliminating forest cover in Korea using IKONOS imagery. The digital forest cover map in which each class is delimitated in the form of a polygon can be prepared on the basis of the segment-based classification.

• The Korean Journal of Ecology
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• v.11 no.3
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• pp.145-152
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• 1988

The potential natural vegetation of Naejangsan national park area, southwestern Korea, was inferred from the actual vegetation. With the phytosociological classification, ordinatins and field surveys, the actual vegetation map of the area was made in scale 1:25, 000, including ten communities of Pinus densiflora, quercus mongolica, Quercus variabilis, Carpinus laxiflora, Daphnipyllum macropodum, Carpinus tschonoskii, Quercus aliena-Carpinus tschonoskii, Cornus controversa-Lindera erythrocarpa, Torreya mucifera-Zelkova serrate and Acer mono-Zelkova serrata community. The analyses of species richness, age structure and various informations on vegetation changes suggest the three pathways of late stage succession from P. densiflora forest to climatic climax. The first of them is through Q. variabilis forest to Q. monogolica forest in the upper parts of the mountain, the second through Q. variabilis and Q. serrata forest to C. laxiflora forest in the middle parts and the third through Q. aliena forest to C. tschonoskii forest in lower parts. Considering the actual vegetation and informations on the vegetation changes including human activities, the potential natural vegetation of the mountain mainly composed of Q. monogolica, C. laxiflora, C. tschonoskii, P. densiflora and Z. serrata forest as climatic climax and/or edaphic climax was inferred. The present situration of nature conservation in the area was estimated by the examination on the actual vegetation and potential natural vegetation map.

• Journal of Korean Society of Forest Science
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• v.100 no.3
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• pp.455-465
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• 2011

In order to assess and mitigate climate change, the role of forest biomass as carbon sink has to be understood spatially and quantitatively. Since existing forest statistics can not provide spatial information about forest resources, it is needed to predict spatial distribution of forest biomass under an alternative scheme. This study focuses on developing an upscaling method that expands forest variables from plot to landscape scale to estimate spatially explicit aboveground biomass(AGB). For this, forest stand variables were extracted from National Forest Inventory(NFI) data and used to develop AGB regression models by tree species. Dominant/codominant height and crown density were used as explanatory variables of AGB regression models. Spatial distribution of AGB could be estimated using AGB models, forest type map and the stand height map that was developed by forest type map and height regression models. Finally, it was estimated that total amount of forest AGB in Danyang was 6,606,324 ton. This estimate was within standard error of AGB statistics calculated by sample-based estimator, which was 6,518,178 ton. This AGB upscaling method can provide the means that can easily estimate biomass in large area. But because forest type map used as base map was produced using categorical data, this method has limits to improve a precision of AGB map.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.41-44
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• 2008

In this paper, major species of tree were discriminated in compartment by using LiDAR data and optic imagery. This is an important work in forest field. A current digital stock map has created the aerial photo and collecting survey data. Unlike high resolution imagery, LiDAR data is not influenced by topographic effects since it is an active sensory system. LiDAR system can measure three dimension information of individual tree. And the main methods of this study were to extract reliable the individual tree and analysis techniques to facilitate the used LiDAR data for calculating tree crown 2D parameter. We should estimate the forest inventory for calculating parameter. 2D parameter has need of area, perimeter, diameter, height, crown shape, etc. Eventually, major species of tree were determined the tree parameters, compared a digital stock map.

• Journal of Climate Change Research
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• v.7 no.4
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• pp.499-506
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• 2016

This study was conducted to estimate carbon stock and uptake for Larix kaempferi Lamb., the single species, which is the most widely distributed one following Pinus densiflora, using data from 6th national forest inventory and forest type map of 1:5,000. Overall distribution area of Larix kaempferi in South Korea was shown as 272,800ha, in detail, Gangwon-do was the most widely distributed region with 39.6% (108,141 ha) of the whole forest area, and Gyeongsangbuk-do was 18.6%(50,839 ha), Chungcheongbuk-do was 15.1%(41,205ha) in order. As the results of analysis in carbon stock and uptake for each province, the values were high with Gyeonggi-do 109.0 tC/ha, $10.3tCO_2/ha/yr$, Gangwon-do 349.1 tC/ha, $9.7tCO_2/ha/yr$ in order, and Jeollabuk-do was the lowest with 78.3 tC/ha, $7.6tCO_2/ha/yr$. Also, the results of estimation in total carbon stocks and uptakes by year (1989~2015) were turned out that total carbon stocks and uptakes were 24,891 thousand tC, $2,428thousand\;tCO_2$ in 2015, increasing about 4.8 times and 3.8 times each compared with 5,238 thousand C/ha, $640thousand\;CO_2$ in 1989. Although forest area was decreased 26.6% with 371,884 ha in 1989 to 272,800 ha in 2015, carbon stocks and uptakes were increased in 2015 in that forest stock was increased 126% compared to 1989.