• Journal of Climate Change Research
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• v.5 no.1
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• pp.21-36
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• 2014

Forest ecosystem provides variety goods and services for human being. Unlike goods, forest ecosystem services could not be easily priced by market mechanism. This uncertainty has been caused to conflict in decision-making related forest ecosystem services. Quantification of forest ecosystem services is required to understand the importance of ecosystem services and their contribution to decision-making. As a growing concern of climate change, it is necessary to quantify and calculate carbon storage and sequestration in forest. In this study, for quantifying carbon storage and sequestration, we compared scale, output, input data availability of the models and analyzed the applicability of the models to Korea. The results of this study show that most models are applicable for quantifying carbon storage and sequestration. However, relatively few models are applicable for other regulating services (air quality regulation, flood mitigation, erosion control, water quality, etc.) of forest. This study would be helpful for quantifying regulating services of forest ecosystem research.

• Journal of Korean Society of Forest Science
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• v.98 no.1
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• pp.33-48
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• 2009

Forests store carbon dioxide ($CO_2$), one of the major factors of global warming, in vegetation and soils through photosynthesis process. In addition, woods deposit $CO_2$ for a long term until the harvested wood is decomposed or burned, and deforested areas could be expanded the carbon sinks through reforestation. Forests are a lso able to decrease temperature through transpiration and contribute to control the micro climate in global climate systems. Consequently, forests are considered as one of major sinks of greenhouse gases for mitigating global warming. It is very important to develop a Korea specific forest carbon flux model for preparing adaptation measures to climate change. In this study, we compared the climate change impact models in forests developed in foreign countries and analyzed the applicability of the models to Korean forest. Also we selected models applicable to Korean forest and suggested approaches for developing Korean specific model.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2013.11a
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• pp.113-115
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• 2013

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2019.08a
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• pp.227-227
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• 2019

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.3
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• pp.189-204
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• 2018

This study has developed a forest fire occurrence probability model for inaccessible areas such as North Korea and Demilitarized Zone and we have developed a real-time forest fire danger rating system that can be used in fire-related works. There are limitations on the research that it is impossible to conduct site investigation for data acquisition and verification for forest fire weather index model and system development. To solve this problem, we estimated the fire spots in the areas where access is impossible by using MODIS satellite data with scientific basis. Using the past meteorological reanalysis data(5㎞ resolution) produced by the Korea Meteorological Administration(KMA) on the extracted fires, the meteorological characteristics of the fires were extracted and made database. The meteorological factors extracted from the forest fire ignition points in the inaccessible areas are statistically correlated with the forest fire occurrence and the weather factors and the logistic regression model that can estimate the forest fires occurrence(fires 1 and non-fores 0). And used to calculate the forest fire weather index(FWI). The results of the statistical analysis show that the logistic models(p<0.01) strongly depends on maximum temperature, minimum relative humidity, effective humidity and average wind speed. The logistic regression model constructed in this study showed a relatively high accuracy of 66%. These findings may be beneficial to the policy makers in Republic of Korea(ROK) and Democratic People's Republic of Korea(DPRK) for the prevention of forest fires.

• Journal of Forest and Environmental Science
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• v.28 no.3
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• pp.152-157
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• 2012

Sarawak is the largest state in Malaysia that covers 37.5% of the total land area. Multitemporal satellite images of Landsat and SPOT were used to examine deforestation and forest fragmentation in Sarawak between 1990 and 2009. Supervised classification with maximum likelihood classifier was used to classify the land cover types in Sarawak. The overall accuracies of all classifications were more than 80%. Our results showed that forests were reduced at 0.62% annually during the two decades. The peat swamp forest suffered a tremendous loss of almost 50% between 1990 and 2009 especially at coastal divisions due to intensified oil palm plantation development. Fragmentation analysis revealed the loss of about 65% of the core area of intact forest during the change period. The core area of peat swamp forest had almost completely disappeared during the two decades.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2008.04a
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• pp.333-336
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• 2008

This study is the result between the variation of fuel moisture and the risk of forest fire through measuring the change of moisture containing ratio on-site and its average analysis for each diameter of surface dead fuels in the forest. The measurement was performed on six days from the day after a rainfall. The fuel moisture on-site was measured on the day when the accumulated rainfall was above 5.0mm, and the measurements was 2 times in spring. From the pine forest which were distributed around Samcheok and Donghae in Kangwondo, three regions were selected by loose, medium, and dense forest density, and the fuel moisture was measured on the ranges which are less than 0.6cm, 0.6-3.0cm, 3.0-6.0cm, and more than 6.0cm in the forest for six days from the day after a rainfall. The study showed that the moisture containing ratio converged on 3 - 4 days for surface deads fuels which diameter are less than 3.0cm and the convergence was made more than six days for ones which diameters are more than 3.0cm except the surface dead fuel of 3.0-6.0cm diameter of loose forest density.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.149-152
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• 2008

This study is the result between the variation of fuel moisture and the risk of forest fire through measuring the change of moisture containing ratio on-site and its average analysis for fallen leaves layer, humus layer, and soil layer in the forest. The measurement was performed on six days from the day after a rainfall. The fuel moisture on-site was measured on the day when the accumulated rainfall was above 5.0mm, and the measurements was 2 times in spring and 1 time in fall. From the pine forest which were distributed around Samcheok and Donghae in Kangwondo, three regions were selected by loose, medium, and dense forest density, and the fuel moisture was measured on fallen leaves layer, humus layer, and soil layer in the forest. for six days from the day after a rainfall. The study showed that the moisture containing ratio converged on 3 - 4 days in spring and fall for fallen leaves layer, and the convergence was made more than six days in spring and fall for the humus layer. In the other case of soil layer, the variation of moisture containing ratio after rainfall was not distinguishable regardless of season.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.965-967
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• 2003

Information on forest volume, forest coverage and biomass are important for developing global perspectives about CO$_{2}$ concentration changes. Forest biomass cannot be directly measured from space yet, but remotely sensed greenness can be used to estimate biomass on decadal and longer time scales in regions of distinct seasonality, as in the north. Hence, in this research, numerical methods were used to estimate forest biomass in higher northern regions. A regression model linking Normalized Difference Vegetation Index(NDVI), to forest biomass extracted from SPOT/4 VEGETATION data and PAL 8km data in regional and continental area (N40-N70) respectively. Statistical tests indicated that the regression model can be used to represent the changes of forest biomass carbon pools and sinks at high latitude regions over years 1982-2000. This study suggests that the implementation of estimation of biomass based on 8-km resolution NOAA/AVHRR PAL and SPOT-4/VEGETATION data could be detected over a range of land cover change processes of interest for global biomass change studies.

• Journal of Environmental Impact Assessment
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• v.14 no.6
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• pp.387-402
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• 2005

In this study, we tried to predict the change of future land-cover and relationships between land-cover change and geo-spatial information in the Gongju area by using fuzzy logic operation. Quantitative evaluation of prediction models was carried out using a prediction rate curve using. Based on the analysis of correlations between the geo-spatial information and land-cover change, the class with the highest correlation was extracted. Fuzzy operations were used to predict land-cover change and determine the land-cover prediction maps that were the most suitable. It was predicted that in urban areas, the urban expansion of old and new towns would occur centering on the Gem-river, and that urbanization of areas along the interchange and national roads would also expand. Among agricultural areas, areas adjacent to national roads connected to small tributaries of the Gem-river and neighboring areas would likely experience changes. Most of the forest areas are located in southeast and from this result we can guess why the wide chestnut-tree cultivation complex is located in these areas and the possibility of forest damage is very high. As a result of validation using the prediction rate curve, it was indicated that among fuzzy operators, the maximum fuzzy operator was the most suitable for analyzing land-cover change in urban and agricultural areas. Other fuzzy operators resulted in the similar prediction capabilities. However, in the prediction rate curve of integrated models for land-cover prediction in the forest areas, most fuzzy operators resulted in poorer prediction capabilities. Thus, it is necessary to apply new thematic maps or prediction models in connection with the effective prediction of changes in the forest areas.