• Journal of The Geomorphological Association of Korea
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• v.26 no.3
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• pp.53-67
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• 2019

The purpose of this study is to identify the quality of landslide susceptibility in a landslide-prone area (Jinbu-myeon, Gangwon-do, South Korea) by spatial prediction modeling approach and compare the results obtained. For this goal, a landslide inventory map was prepared mainly based on past historical information and aerial photographs analysis (Daum Map, 2008), as well as some field observation. Altogether, 550 landslides were counted at the whole study area. Among them, 182 landslides are debris flow and each group of landslides was constructed in the inventory map separately. Then, the landslide inventory was randomly selected through Excel; 50% landslide was used for model analysis and the remaining 50% was used for validation purpose. Total 12 contributing factors, such as slope, aspect, curvature, topographic wetness index (TWI), elevation, forest type, forest timber diameter, forest crown density, geology, landuse, soil depth, and soil drainage were used in the analysis. Moreover, to find out the co-relation between landslide causative factors and incidents landslide, pixels were divided into several classes and frequency ratio for individual class was extracted. Eventually, six landslide susceptibility maps were constructed using the Bayesian Predictive Discriminant (BPD), Empirical Likelihood Ratio (ELR), and Linear Regression Method (LRM) models based on different category dada. Finally, in the cross validation process, landslide susceptibility map was plotted with a receiver operating characteristic (ROC) curve and calculated the area under the curve (AUC) and tried to extract success rate curve. The result showed that Bayesian, likelihood and linear models were of 85.52%, 85.23%, and 83.49% accuracy respectively for total data. Subsequently, in the category of debris flow landslide, results are little better compare with total data and its contained 86.33%, 85.53% and 84.17% accuracy. It means all three models were reasonable methods for landslide susceptibility analysis. The models have proved to produce reliable predictions for regional spatial planning or land-use planning.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.18 no.6
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• pp.61-71
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• 2015

The objectives of this study are to construct an ecoregion map and to extract ecological factors from each ecoregion to adapt FLR (Forest Landscape Restoration) of North Korea. An ecological map was constructed by PCA(Principal Component Analysis) and MGC(Multivatiate Geographical Clustering). An ANOVA test verified the differences among ecoregions, and post-hoc pair wise comparisons were performed to determine similarities between them. Factor analysis was conducted to extract ecoregional characteristics. Ecoregions were distributed into clusters reflecting differences of south and north and of east and west of their ecological factors. About 12% of land area in North Korea shared similar ecological factors with South Korea, but the remaining 88% was found to be ecologically different. The ANOVA test showed a p-value of 0.000, indicating significant differences between the regions. Post-hoc pair wise comparisons indicated statistically significant similarities in annual mean temperature between ecoregion D and G, precipitation seasonality between ecoregion H and O, and precipitation of the warmest quarter between ecoregion K and O. Because ecoregion A and N showed same in their soil water contents, they were assumed that the dense of forest cover in the Southern ecoregion A is similar to that in the Northern ecoregion N of Korean peninsular. Based on the results of this study, it is necessary to accommodate quantitative and spatial based planning, when South Korea aids forest restoration projects in North Korea. In addition, it is recommended for both South and North Korea to share on Forest Landscape Restoration methodologies with each other.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.1
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• pp.34-45
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• 2021

Weather is one of the important factors in the agricultural industry as it affects the price, production, and quality of crops. Upland crops are directly exposed to the natural environment because they are mainly grown in mountainous areas. Therefore, it is necessary to provide accurate weather for upland crops. This study examined the effectiveness of 12 forest soil factors to interpolate the weather in mountainous areas. The daily temperature and precipitation were collected by the Korea Meteorological Administration between January 2009 and December 2018. The Generalized Additive Model (GAM), Kriging, and Random Forest (RF) were considered to interpolate. For evaluating the interpolation performance, automatic weather stations were used as training data and automated synoptic observing systems were used as test data for cross-validation. Unfortunately, the forest soil factors were not significant to interpolate the weather in the mountainous areas. GAM with only geography aspects showed that it can interpolate well in terms of root mean squared error and mean absolute error. The significance of the factors was tested at the 5% significance level in GAM, and the climate zone code (CLZN_CD) and soil water code B (SIBFLR_LAR) were identified as relatively important factors. It has shown that CLZN_CD could help to interpolate the daily average and minimum daily temperature for upland crops.

• Journal of the Korean Institute of Landscape Architecture
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• v.24 no.3
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• pp.115-132
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• 1996

The purpose of this study is to estimate the soil loss amount with Geographic Information System according to the land use change of Buju mountain area in Mokpo city. To estimate the soil loss, Universal Soil Loss Equation which is the most proper technique to predict soil loss in this site condition is adopted and IDRISI, a raster GIS software, is used. GIS application with USLE is very efficient to estimate soil loss accurately and fastly. In order to decide value and to find application method of USLE factors, we used existing rainfall erosion index, soil erodibility analysis, slope length, slope steepness, vegetation management and practices, which are rated by GIS through the analysis of various studies related USLE. The result of this study was compared with the previous other researches to verify our method of constructing numerical data of USLE's factors. The result of verification of our way showed significance for the soil loss in forest area. But the result of verification for the soil loss in forest area. But the result of verification for the soil loss of cultivated area showed some errors. It seems that this result was due to local variation of topographical map.

• Journal of Korean Society of Forest Science
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• v.95 no.6
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• pp.663-671
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• 2006

This study was performed for exploring the spatial distribution pattern of Pinus densiflora and Quercus spp. in Korea. Firstly, the spatial distribution map of Pinus densiflora and Quercus spp. was prepared in grid of $100m{\times}100m$ at national level, using digital forest type map and actual vegetation map. And thematic maps for topography, climate, and soil were also prepared in the raster form of $100m{\times}100m$. Through GIS based spatial analysis of the digital distribution map of Pinus densiflora and Quercus spp. and thematic maps, the spatial characteristics of Pinus densiflora and Quercus spp. distribution was explored in relation to the environmental factors such as topography, climate, and soil. And the occurrence frequency models of Pinus densiflora and Quercus spp. were derived. Pinus densiflora occurs more often than Quercus spp. at low elevation, low slope gradient, and high temperature areas. In addition, Pinus densiflora is mainly distributed at shallow and well-drained loamy soil from igneous rocks. In contrast, Quercus spp. is more common at shallow and well-drained loamy soil from metamorphic rocks. As a result, the prediction model for the spatial distribution of Pinus densiflora and Quercus spp. by topographical variables has proven successful with high statistical significance. The result of this study can contribute to rational management of Pinus densiflora and Quercus spp. stand in Korea, considering environmental factors such as topography, climate, and soil.

• Spatial Information Research
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• v.20 no.3
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• pp.57-66
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• 2012

Gangwon-do has been suffering extensive landslide dam age, because its geography consists mainly of mountains. Analyzing the related factors is crucial for landslide prediction. We digitized the landslide and non-landslide spots on an aerial photo obtained right after a disaster in Inje, Gangwon-do. Three landslide factors-topographic, forest type, and soil factors-w ere statistically analyzed through GIS overlap analysis between topographic map, forest type map, and soil map. The analysis showed that landslides occurred mainly between the inclination of $20^{\circ}$ and $35^{\circ}$, and needleleaf tree area is more vulnerable to a landslide. About soil properties, an area with shallow effective soil depth and parent material of acidic rock has a greater chance of landslide.

• Journal of Plant Biology
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• v.27 no.2
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• pp.51-60
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• 1984

Jisimdo is an island where evergreen broadleaved forests are well preserved. Soil environments and forest structures of Jisimdo were investigated, and an actual vegetation map and profile diagrams were drawn out. The natural vegetation of Jisimdo was divided into two stand units, one was evergreen broadleaved forest and the other was Pinus thunbergii forest. 26 species were identified as evergreen broadoeaved trees, and among them, Camellia japonica was the dominont of the tree layer of evergreen broadleaved forest. Profile diagram shows that Camellia japonica, with average height of 7∼8m, formed lower tree layer, and laurels like Cinnamomum japonicum, Machilus thunbergii, and Neolitsea sericea formed upper tree layer. In Pinus thunbergii forest, plants of shrub and herb layers were abundant because of much light penetrated into the forest floor, and these layers were largely composed of evergreen broadleaved trees. This fact shows the possibility of succession from Pinus thunbergii forest into evergreen broadleaved forest. Jisimdo is geographically adjacent to Jangseungpo and Okpo, and this increases the economic value of Jisimdo as a place of public resort. It will be necessary from being destroyed by land development and human interferences.

• Journal of Korean Society of Forest Science
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• v.96 no.1
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• pp.7-13
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• 2007

This study was done to develop PDA based application system for forest geographic information with GPS. The major results obtained in this study were as follows. A PDA based application program was developed to work on $Microsoft^{TM}$ PocketPC 2002 and 2003 operating system. The screen of PDA displays a 1:25,000 digital topographical map adopted DXF format converted from PC, and the map data with 1:2,500 to 1:30,000 on PDA can be zoomed in or out to five levels. Current position and navigating path received from GPS can be displayed on the screen and be saved in PDA. Information selected among layers of digital topographic map in DXF format can be converted into binary files which can be used on forest geographic information software. This can compress DXF files to 90% in size, and the processing speed of PDA was improved. The forest geographic information management system can be used to manage sample plots on which forest inventory is done, with the help of the sub-menus and grid index values with position information received from GPS. Forest workers can in quire forest geographic information such as forest type, location, forest roads, soil erosion control dams using forest geographic information management system in the field. The forest geographic information management system can provide current position and mobile path information to people who enjoy forest related activities like mountain-climbing, sightseeing, and visiting to historic spots.

• Journal of The Geomorphological Association of Korea
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• v.27 no.2
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• pp.65-80
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• 2020

This paper deals with risk assessment of life in a landslide-prone area by a GIS-based modeling method. Landslide susceptibility maps can provide a probability of landslide prone areas to mitigate or proper control this problems and to take any development plan and disaster management. A landslide inventory map of the study area was prepared based on past historical information and aerial photography analysis. A total of 550 landslides have been counted at the whole study area. The extracted landslides were randomly selected and divided into two different groups, 50% of the landslides were used for model calibration and the other were used for validation purpose. Eleven causative factors (continuous and thematic) such as slope, aspect, curvature, topographic wetness index, elevation, forest type, forest crown density, geology, land-use, soil drainage, and soil texture were used in hazard analysis. The correlation between landslides and these factors, pixels were divided into several classes and frequency ratio was also extracted. Eventually, a landslide susceptibility map was constructed using a logistic regression model based on entire events. Moreover, the landslide susceptibility map was plotted with a receiver operating characteristic (ROC) curve and calculated the area under the curve (AUC) and tried to extract a success rate curve. Based on the results, logistic regression produced an 85.18% accuracy, so we believed that the model was reliable and acceptable for the landslide susceptibility analysis on the study area. In addition, for risk assessment, vulnerability scale were added for social thematic data layer. The study area predictive landslide affected pixels 2,000 and 5,000 were also calculated for making a probability table. In final calculation, the 2,000 predictive landslide affected pixels were assumed to run. The total population causalities were estimated as 7.75 person that was relatively close to the actual number published in Korean Annual Disaster Report, 2006.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1847-1859
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• 2022

Wildfires in North Korea can have a directly or indirectly affect South Korea if they go south to the Demilitarized Zone. Therefore, this study calculates the regional optimized Forest Fire Danger Index (FFDI) based on Local Data Assessment and Prediction System (LDAPS) weather data to obtain forest fire risk in North Korea, and applied it to the cases in Goseong-gun and Cheorwon-gun, North Korea in April 2022. As a result, the suitability was confirmed as the FFDI at the time of ignition corresponded to the risk class Extreme and Severe sections, respectively. In addition, a qualitative comparison of the risk map and the soil moisture map before and after the wildfire, the correlation was grasped. A new forest fire risk index that combines drought factors such as soil moisture, Standardized Precipitation Index (SPI), and Normalized Difference Water Index (NDWI) will be needed in the future.