• Title/Summary/Keyword: Topographic Index

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County-Based Vulnerability Evaluation to Agricultural Drought Using Principal Component Analysis - The case of Gyeonggi-do - (주성분 분석법을 이용한 시군단위별 농업가뭄에 대한 취약성 분석에 관한 연구 - 경기도를 중심으로 -)

  • Jang, Min-Won
    • Journal of Korean Society of Rural Planning
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    • v.12 no.1 s.30
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    • pp.37-48
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    • 2006
  • The objectives of this study were to develop an evaluation method of regional vulnerability to agricultural drought and to classify the vulnerability patterns. In order to test the method, 24 city or county areas of Gyeonggi-do were chose. First, statistic data and digital maps referred for agricultural drought were defined, and the input data of 31 items were set up from 5 categories: land use factor, water resource factor, climate factor, topographic and soil factor, and agricultural production foundation factor. Second, for simplification of the factors, principal component analysis was carried out, and eventually 4 principal components which explain about 80.8% of total variance were extracted. Each of the principal components was explained into the vulnerability components of scale factor, geographical factor, weather factor and agricultural production foundation factor. Next, DVIP (Drought Vulnerability Index for Paddy), was calculated using factor scores from principal components. Last, by means of statistical cluster analysis on the DVIP, the study area was classified as 5 patterns from A to E. The cluster A corresponds to the area where the agricultural industry is insignificant and the agricultural foundation is little equipped, and the cluster B includes typical agricultural areas where the cultivation areas are large but irrigation facilities are still insufficient. As for the cluster C, the corresponding areas are vulnerable to the climate change, and the D cluster applies to the area with extensive forests and high elevation farmlands. The last cluster I indicates the areas where the farmlands are small but most of them are irrigated as much.

Flood Runoff Analysis using TOPMODEL Linked with Muskingum Method - Anseong-cheon Watershed - (TOPMODEL과 Muskingum 기법을 연계한 안성천 유역의 홍수유출 분석)

  • Kwon, Hyung-Joong;Kim, Seong-Joon
    • Journal of the Korean Association of Geographic Information Studies
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    • v.6 no.1
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    • pp.1-11
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    • 2003
  • In this study, TOPMODEL(TOPography based hydrologic MODEL) was tested linked with Muskingum river routing technique for $581.7km^2$ Anseong-cheon watershed. Linear trend surface interpolation was used to give flow direction for flat areas located in downstream watershed. MDF (multiple flow direction) algorithm was adopted to derive the distribution of ln(a/$tan{\beta}$) values of the model. Because the coarser DEM resolution, the greater information loss, the watershed was divided into subwaterhseds to keep DEM resolution, and the simulation result of the upstream watershed was transferred to downstream watershed by Muskingum techniques. Relative error of the simulated result by 500 m DEM resolution showed 27.2 %. On the other hand, the relative error of the simulated result of 300 m DEM resolution by linked 2 subwatersheds with Muskingum method showed 15.8 %.

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The Characteristics of the Sites and Prospects of the Bear Shelves of Asiatic Black Bear (Ursus Thibetanus) on Jirisan National Park (지리산 반달가슴곰 상사리 입지와 조망 특성)

  • Yu, Jaeshim;Park, Chonghwa;Woo, Donggul
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.15 no.4
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    • pp.41-49
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    • 2012
  • The objective of this study is to investigate the characteristics of the location and prospects of the bear shelves built by Asiatic black bears in the Jirisan National Park. Previous researchers have been analyzed bear shelves in terms of places for resting and eating, but we are going to analyze based on the prospect-and-refuge theory. Characteristics of the sites of bear shelves are measured through field survey and topographic analysis by using digital elevation model (DEM). The normalized difference vegetation index (NDVI) is used to evaluate the optimum location of bear shelves in terms of crown density. Man-made objects are identified by viewshed analysis based on geographical information system (GIS). Findings of this paper can be summarized as follows. First, most bear trees are located deep inside of the mountainous national park, slopes of 30~40 degrees, altitude of 400~1,200m, and relatively low vegetation density with NDVI value of 0.4~0.6 compared to the average NDVI of the park. Second, the average height of bear shelves is 12.44m, or 74% of the average height of bear trees. They are located at suitable places to observe nearby trails and other park facilities. Third, man-made objects within the 100m radius of bear trees include lodge, bear training center, beekeeping camp, and hiking trails. Thus we may temporarily conclude that one of the main criteria of the bear tree selection in the park has been to identify optimum places for the monitoring of human activities in their habitat.

Development of Semi-Distributed TOPMODEL (준분포형 TOPMODEL 개발)

  • Bae, Deg-Hyo;Kim, Jin-Hoon
    • Journal of Korea Water Resources Association
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    • v.38 no.10 s.159
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    • pp.895-906
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    • 2005
  • The diversity of observed hydrologic data and the development of geographic information system leads significant progress for developing distributed runoff models in the world. One of the typical examples is TOPMODEL, but the spatial coverage of its application Is limited on small headwater basins. The purpose of this study attempts to overcome its limitation and consequently develops a semi-distributed TOPMODEL. The developed model is composed of two components: a watershed runoff component for a lumped representation of hydrologic runoff process on the catchment scale and a kinematic wave type hydraulic channel routing component lot routing the catchment outflows. The application basin is the $2,703km^2$ upper Soyang dam site and several daily and hourly events are selected for model calibrations and verifications. The model parameters are estimated on 1990 daily event. The model performance on correlation coefficient between observed and computed flows are above 0.90 for the verification events. It is concluded that the developed model in this study can be used for flood analysis in large drainage basins.

The Distribution Characteristics Analysis of Block Stream and Talus Landform by Using GIS-based Likelihood Ratio in the Honam Region (GIS 기반 우도비를 이용한 호남지역 암괴류와 애추지형의 분포 특성 분석)

  • JANG, Dong-Ho;Kim, ChanSoo
    • Journal of The Geomorphological Association of Korea
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    • v.25 no.2
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    • pp.1-14
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    • 2018
  • The main objective of this paper is to classify properties of the locational environment for each debris type by calculating likelihood ratio based on the correlation between the distributions for each type of debris landform. A total of 8 thematic maps, like as elevation, slope, aspect, curvature, topographic wetness index (TWI), soil drainage, geology, and landcover including with GIS spatial information generally used in this type of debris landform analysis. The results of this study showed that the block stream had a high likelihood ratio compared to talus in areas with relatively high elevation; and concerning slope, the block stream had a high likelihood ratio in a relatively low region than talus. Concerning aspect, a clear correlation could not be analyzed for each debristype, and concerning curvature, the block stream displayed a developed slope on the more concave valley than the talus. Analysis concerning TWI, the block stream displayed a higher likelihood ratio in wider sections than talus, and concerning soil drainage, the talus and block stream both displayed a high likelihood ratio in regions with well-drained soil. The talus displayed a high likelihood ratio in the order of metamorphic rocks, sedimentary rocks, and granite, while the block stream displayed a high likelihood ratio in the order of volcanic rocks, granite, and sedimentary rocks. In addition, concerning landcover, the likelihood ratio had the most concentrated distributed compared to natural bare land only concerning talus. Based on the likelihood ratio result, it can be used as basic data for extracting the possible areas of distribution for each debris type through the GIS spatial integration method.

Landslide Risk Assessment of Cropland and Man-made Infrastructures using Bayesian Predictive Model (베이지안 예측모델을 활용한 농업 및 인공 인프라의 산사태 재해 위험 평가)

  • Al, Mamun;Jang, Dong-Ho
    • Journal of The Geomorphological Association of Korea
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    • v.27 no.3
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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.

Mapping Landslide Susceptibility Based on Spatial Prediction Modeling Approach and Quality Assessment (공간예측모형에 기반한 산사태 취약성 지도 작성과 품질 평가)

  • Al, Mamun;Park, Hyun-Su;JANG, Dong-Ho
    • 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.

Life Risk Assessment of Landslide Disaster in Jinbu Area Using Logistic Regression Model (로지스틱 회귀분석모델을 활용한 평창군 진부 지역의 산사태 재해의 인명 위험 평가)

  • Rahnuma, Bintae Rashid Urmi;Al, Mamun;Jang, Dong-Ho
    • 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.

Development of a Distribution Prediction Model by Evaluating Environmental Suitability of the Aconitum austrokoreense Koidz. Habitat (세뿔투구꽃의 서식지 환경 적합성 평가를 통한 분포 예측 모형 개발)

  • Cho, Seon-Hee;Lee, Kye-Han
    • Journal of Korean Society of Forest Science
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    • v.110 no.4
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    • pp.504-515
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    • 2021
  • To examine the relationship between environmental factors influencing the habitat of Aconitum austrokoreense Koidz., this study employed the MexEnt model to evaluate 21 environmental factors. Fourteen environmental factors having an AUC of at least 0.6 were found to be the age of stand, growing stock, altitude, topography, topographic wetness index, solar radiation, soil texture, mean temperature in January, mean temperature in April, mean annual temperature, mean rainfall in January, mean rainfall in August, and mean annual rainfall. Based on the response curves of the 14 descriptive factors, Aconitum austrokoreense Koidz. on the Baekun Mountain were deemed more suitable for sites at an altitude of 600 m or lower, and habitats were not significantly affected by the inclination angle. The preferred conditions were high stand density, sites close to valleys, and distribution in the northwestern direction. Under the five-age class system, the species were more likely to be observed for lower classes. The preferred solar radiation in this study was 1.2 MJ/m2. The species were less likely to be observed when the topographic wetness index fell below the reference value of 4.5, and were more likely observed above 7.5 (reference of threshold). Soil analysis showed that Aconitum austrokoreense Koidz. was more likely to thrive in sandy loam than clay. Suitable conditions were a mean January temperature of - 4.4℃ to -2.5℃, mean April temperature of 8.8℃-10.0℃, and mean annual temperature of 9.6℃-11.0℃. Aconitum austrokoreense Koidz. was first observed in sites with a mean annual rainfall of 1,670- 1,720 mm, and a mean August rainfall of at least 350 mm. Therefore, sites with increasing rainfall of up to 390 mm were preferred. The area of potential habitats having distributive significance of 75% or higher was 202 ha, or 1.8% of the area covered in this study.

Enhancing the Stability of Slopes Located below Roads, Based on the Case of Collapse at the Buk-sil Site, Jeongseon Area, Gangwon Province (강원도 정선지역 북실지구 깎기비탈면 붕괴 사례를 통한 도로 하부 비탈면 안정성 확보에 관한 고찰)

  • Kim, Hong-Gyun;Bae, Sang-Woo;Kim, Seung-Hyun;Koo, Ho-Bon
    • The Journal of Engineering Geology
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    • v.22 no.1
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    • pp.83-94
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    • 2012
  • Slopes are commonly formed both above and below roads located in mountainous terrain and along riversides. The Buk-sil site, a cut slope formed below the road, collapsed in October, 2010. A field investigation determined the causes of failure as improper drainage of valley water from the slope above the road and direct seepage of road-surface water. These factors may have accelerated the collapse via complex interaction between water and sub-surface structures such as bedding. Projection analysis of the site showed the possible involvement of plane, wedge, and toppling failure. Safety factors calculated by Limit Equilibrium Analysis for plane and wedge failure were below the standard for wet conditions. The wetness index, analyzed using topographic factors of the study area, was 9.0-10.5, which is high compared with the values calculated for nearby areas. This finding indicates a high concentration of water flow. We consider that water-flow control on the upper road is crucial for enhancing slope stability at the Buk-sil site.