• 한국지형학회지
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• 제26권3호
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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.

• 한국산림과학회지
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• 제94권6호
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• pp.481-487
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• 2005

이 연구에서는 지표화 중심의 산불확산예측 알고리즘을 기반으로 GIS 환경에서 운용이 가능한 지표화 확산예측모델을 개발하였다. 이 모델은 지형, 연료, 기상 등 산불환경인자를 분석하고 입력하는 부분과 시간에 따라 확산속도, 화선에서의 산불강도, 연소면적을 예측하는 지표화 확산예측 부분, 마지막으로 예측결과를 사용자에게 제시하는 출력 부분으로 구성되었다. 산불확산속도를 계산하기 위해서 산불행동에 영향을 미치는 산불환경인자중에서 지형인자는 경사, 기상인자는 풍속, 풍향, 실효습도를 고려하였다. 또한 연료인자는 수치임상도를 이용하여 연료깊이, 연료량, 소화습도를 계산할 수 있는 연료모듈을 개발하여 입력되도록 하였다. 연료습도는 실효습도, 최고온도, 강수량, 일일 적산량의 함수관계로 추정하였다. 모델을 2002년 청양에서 발생한 산불에 적용한 결과 확산속도에 대해 61%의 일치도를 보였다.

• 환경영향평가
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• 제14권6호
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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.

• 한국지리정보학회지
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• 제17권1호
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• pp.1-12
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• 2014

수관화는 대형산불의 주된 확산유형으로 빠른 확산속도와 높은 산불강도의 특성을 보이며 많은 피해를 입힌다. 이 연구에서는 수관화 피해를 사전에 예측하기 위해서 수관전소 피해를 입은 지역의 지형 임상 기상 특성을 분석하여 수관화확산확률식을 개발하였다. 영덕 울진 고령 예천에서 일어난 4개의 산불피해지를 대상으로 하였으며, 총 18개의 공간 변수를 구축한 뒤 기타연소지에 대한 수관전소지의 비를 이용하여 각 변수별 구간 가중치를 구하고 로지스틱 회귀모형을 이용하여 변수와의 상관계수를 산출하였다. 그 결과, 수관화확산확률은 임상이 침엽수림일 때, 250m 이상에서 고도가 높아질수록, 기복이 심할수록, 사면향은 남서 또는 남동사면일 경우, 능선일수록, 일사량이 많아질수록 높게 나타났다. 고도와 경사가 낮은 곳에서는 교란현상이 많이 나타나 일정한 패턴을 보이지 않았다. 이 확률식을 통해 수관화 위험지를 사전에 분석할 수 있고, 산불방지 숲가꾸기 지역 선정 및 진화 우선 지역 선정 등에 효과적으로 활용할 수 있을 것이다.

• 한국농림기상학회지
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• 제13권2호
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• pp.87-92
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• 2011

본 연구에서는 광릉 활엽수림의 수문순환과정에서 낙엽층의 역할을 이해하기 위해 낙엽층의 차단저류능을 산정하였다. 낙엽층 두께의 공간 분포를 조사하여 낙엽층 두께 지도를 작성하였으며, 낙엽층의 두께와 차단저류능 간의 관계를 확인하고자 낙엽 표본을 채집하여 실험을 수행하였다. 25~100mm 두께의 낙엽 표본에 대한 실험 결과, 둘 간에 선형 비례 관계가 존재함을 확인하였다. 낙엽층의 응집이 상대적으로 적은 0~25mm 두께에서는 낙엽층 두께의 증가에 따라 더 급격한 차단저류능 증가가 일어나는 비선형적인 관계를 보였다. 또한 강우 강도가 약한 경우에도 낙엽층 두께와 차단저류능 간의 비선형 관계가 더 크게 나타날 수 있음을 확인하였다. 제작된 낙엽층 두께 지도와 낙엽층 두께와 차단저류능 사이의 관계식을 통하여 산정한 낙엽층의 차단저류능은 평균 $0.94{\pm}0.39mm$ 이었다. 산정된 낙엽층(평균 두께 $59{\pm}32mm$)의 차단저류능은 군락의 차단저류능과 비교할 때 그 크기가 비슷하였으며, 이는 낙엽층이 광릉 활엽수림의 수문순환에 중요한 역할을 할 수 있음을 보여준다.

• 한국농공학회논문집
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• 제46권7호
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• pp.3-12
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• 2004

The need to predict the rate of soil erosion, both under existing conditions and those expected to occur following soil conservation practice, has been led to the development of various models. In this study Morgan model especially developed for field-sized areas on hill slopes was applied to assess the rate of soil erosion using RS/GIS environment in the Dukchun river basin, one of two tributaries flowing into Jinyang lake. In order to run the model, land cover mapping was made by the supervised classification method with Landsat TM satellite image data, the digital soil map was generated from scanning and screen digitizing from the hard copy of soil maps, digital elevation map (DEM) in order to generate the slope map was made by the digital map (DM) produced by National Geographic Information Institute (NGII). Almost all model parameters were generated to the multiple raster data layers, and the map calculation was made by the raster based GIS software, IL WIS which was developed by ITC, the Netherlands. Model results show that the annual soil loss rates are 5.2, 18.4, 30.3, 58.2 and 60.2 ton/ha/year in forest, paddy fields, built-up area, bare soil, and upland fields respectively. The estimated rates seemed to be high under the normal climatic conditions because of exaggerated land slopes due to DEM generation using 100 m contour interval. However, the results were worthwhile to estimate soil loss in hilly areas and the more precise result could be expected when the more accurate slope data is available.

• 한국환경과학회지
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• 제13권12호
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• pp.1033-1039
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• 2004

The methodology developed by Soil Conservation Service for determination of runoff value from precipitation is applied to estimate the precipitation recharge in the Pyungchang river basin. Two small areas of the basin are selected for this study. The CN values are determined by considering the type of soil, soil cover and land use with the digital map of 1:25,000. Forest covers more than $94{\%}$ of the study area.. The CN values for the study area vary between 47 in the forest area and 94 in the bare soil under AMC 2 condition. The precipitation recharge rate is calculated for the year when the precipitation data is available since 1990. To obtain the infiltration rate, the index of CN and five day antecedent moisture conditions are applied to each precipitation event during the study period. As a result of estimation, the value of precipitation recharge ratio in the study area vary between $15.2{\%}\;and\;35.7{\%}$ for the total precipitation of the year. The average annual precipitation recharge rate is $26.4{\%}\;and\;26.8{\%}$, meaning 377.9mm/year and 397.5mm/year in each basin.

• The Korean Journal of Ecology
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• 제21권4호
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• pp.389-399
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• 1998

this study was focused on the effects of fire on spatial change of vegetation landscape in rural region. Fire types recognized as erown fire, severe surface fire and light surface fire in order of increasing intensity were described in a fire map. GIS was introduced to understand the relationship between fire types and topographic conditions or vegetation types. We also investigated land-use type and regeneration strategies after burning. Fire intensity depended on topographic conditions and vegetation types. Special land-use type in this area was collection of edible mushroom (Tricholoma matsutake). Mushrooms had been obtained from Pinus densiflora forests existing as edaphic climax or managed artificially. Regeneration strategy in burned areas was to make sprouts from burned oak stumps. A higher density and growth rate of sprouts, as compared to those on unburned areas, facilitated vegetation succession from P. densiflora forest to oak forest and consequently led to change of landscape pattern.

• 한국지형학회지
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• 제28권1호
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• pp.83-99
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• 2021

Burn severity analysis using satellite imagery has high capabilities for research and management in inaccessible areas. We extracted the forest fire area of the DMZ (Demilitarized Zone) in the western Imjin Estuary which is restricted to access due to the confrontation between South and North Korea. Then we analyzed the forest fire severity and recoverability using atmospheric corrected Surface Reflectance Level-2 data collected from Landsat-8 OLI (Operational Land Imagery) / TIRS (Thermal Infrared Sensor). Normalized Burn Ratio (NBR), differenced NBR (dNBR), and Relative dNBR (RdNBR) were analyzed based on changes in the spectral pattern of satellite images to estimate burn severity area and intensity. Also, we evaluated the recoverability after a forest fire using a land cover map which is constructed from the NBR, dNBR, and RdNBR analyzed results. The results of dNBR and RdNBR analysis for the six years (during May 30, 2014 - May 30, 2020) showed that the intensity of monthly burn severity was affected by seasonal changes after the outbreak and the intensity of annual burn severity gradually decreased after the fire events. The regrowth of vegetation was detected in most of the affected areas for three years (until May 2020) after the forest fire reoccurred in May 2017. The monthly recoverability (from April 2014 to December 2015) of forests and grass fields was increased and decreased per month depending on the vegetation growth rate of each season. In the case of annual recoverability, the growth of forest and grass field was reset caused by the recurrence of a forest fire in 2017, then gradually recovered with grass fields from 2017 to 2020. We confirmed that remote sensing was effectively applied to research of the burn severity and recoverability in the DMZ. This study would also provide implications for the management and construction statistics database of the forest fire in the DMZ.

• 한국지형학회지
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• 제27권3호
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• pp.87-103
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• 2020

The purpose of this study is to evaluate the risk of cropland and man-made infrastructures in a landslide-prone area using a GIS-based method. To achieve this goal, a landslide inventory map was prepared based on aerial photograph analysis as well as field observations. A total of 550 landslides have been counted in the entire study area. For model analysis and validation, extracted landslides were randomly selected and divided into two groups. The landslide causative factors 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 the analysis. Moreover, to identify the correlation between landslides and causative factors, pixels were divided into several classes and frequency ratio was also extracted. A landslide susceptibility map was constructed using a bayesian predictive model (BPM) based on the entire events. In the cross validation process, the landslide susceptibility map as well as observation data were plotted with a receiver operating characteristic (ROC) curve then the area under the curve (AUC) was calculated and tried to extract a success rate curve. The results showed that, the BPM produced 85.8% accuracy. We believed that the model was acceptable for the landslide susceptibility analysis of the study area. In addition, for risk assessment, monetary value (local) and vulnerability scale were added for each social thematic data layers, which were then converted into US dollar considering landslide occurrence time. Moreover, the total number of the study area pixels and predictive landslide affected pixels were considered for making a probability table. Matching with the affected number, 5,000 landslide pixels were assumed to run for final calculation. Based on the result, cropland showed the estimated total risk as US $ 35.4 million and man-made infrastructure risk amounted to US $ 39.3 million.