• Title/Summary/Keyword: topographic curvature

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The Development of Topographic Feature Extraction Method by use of the Seafloor Curvature Measurement (곡률 계산에 의한 해저면 지형요소 추출 기법 개발)

  • Kim, Hyun-Sub;Jung, Mee-Sook;Park, Cheong-Kee
    • Geophysics and Geophysical Exploration
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    • v.10 no.3
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    • pp.163-172
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    • 2007
  • A seafloor curvature measurement method was developed to extract redundant topographic features from the multi-beam bathymetry data, and then applied to the data of abyssal plain area in the Pacific. Any seafloor might be modeled to a quadratic surface determined in a linear least squares sense, and its curvature could be derived from the eigen values related with quadratic model parameters. The curvature's magnitude as well as polarity showed distinct relationship with geometric characteristics of the seafloor like as ridge and valley. From the investigation of curvature's variation with the number of data in the quadratic surface, the optimal size of data aperture could be applied to real bathymetry data. The application to real data also required the determination of the accompanying threshold values to cope with corresponding topographic features. The calculation method of previous studies were reported to be sensitive to the background noise. The improved curvature measurement method, incorporating the sum of eigen values has reduced unwanted artifacts and enhanced ability to extract lineament features along strike direction. The result of application shows that the curvature measurement method is effective tool for the estimation of a possible mining area in the seamount free abyssal hill area.

Analysis of Topographical Factors in Woomyun Mountain Debris Flow Using GIS (GIS를 이용한 우면산 토석류 지형인자 분석)

  • Lee, Hanna;Kim, Gihong
    • Journal of the Korean Society of Industry Convergence
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    • v.23 no.5
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    • pp.809-815
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    • 2020
  • A number of investigations and studies have been conducted in various fields regarding the sediment disasters of Mt. Woomyeon that occurred in July 2011. We collected and compared the topographic information of the general points where debris flows did not occur and the collapse points where the debris flow occurred in order to find out the characteristics of the collapse points in Woomyeon mountain. The collected topographic information is altitude, curvature, slope, aspect and TPI(topographic position index). As a result of comparison, there were relatively many collapse points at an altitude of 210m to 250m, and at a slope of 30° to 40°. In addition, the risk of collapse was low in a cell where the curvature was close to 0, and the risk was higher in concave terrain than in convex terrain. In the case of TPI, there was no statistical difference between the general points and the collapse points when the analysis radius was larger than 200m, and there was a correlation with the curvature when the analysis radius was smaller than 50m. In the case of debris flows that are affected by artificial structures or facilities, there is a possibility of disturbing the topographic analysis results. Therefore, if a research on debris flow is conducted on a mountain area that is heavily exposed to human activities, such as Woomyeon mountain, diversified factors must be considered to account for this impact.

Application of a weight-of-evidence model to landslide susceptibility analysis Boeun, Korea

  • Moung-Jin, Lee;Yu, Young-Tae
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2003.04a
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    • pp.65-70
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    • 2003
  • The weight-of-evidence model one of the Bayesian probability model was applied to the task of evaluating landslide susceptibility using GIS. Using the location of the landslides and spatial database such as topography, soil, forest, geology, land use and lineament, the weight-of-evidence model was applied to calculate each factor's rating at Boun area in Korea where suffered substantial landslide damage fellowing heavy rain in 1998, The factors are slope, aspect and curvature from the topographic database, soil texture, soil material, soil drainage, soil effective thickness, and topographic type from the soil database, forest type, timber diameter, timber age and forest density from the forest map, lithology from the geological database, land use from Landsat TM satellite image and lineament from IRS satellite image. Tests of conditional independence were performed for the selection of the factors, allowing the 43 combinations of factors to be analyzed. For the analysis, the contrast value, W$\^$+/and W$\^$-/, as each factor's rating, were overlaid to map laudslide susceptibility. The results of the analysis were validated using the observed landslide locations, and among the combinations, the combination of slope, curvature, topographic, timber diameter, geology and lineament show the best results. The results can be used for hazard prevention and planning land use and construction

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APPLICATION OF LOGISTIC REGRESSION MODEL AND ITS VALIDATION FOR LANDSLIDE SUSCEPTIBILITY MAPPING USING GIS AND REMOTE SENSING DATA AT PENANG, MALAYSIA

  • LEE SARO
    • Proceedings of the KSRS Conference
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    • 2004.10a
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    • pp.310-313
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    • 2004
  • The aim of this study is to evaluate the hazard of landslides at Penang, Malaysia, using a Geographic Information System (GIS) and remote sensing. Landslide locations were identified in the study area from interpretation of aerial photographs and from field surveys. Topographical and geological data and satellite images were collected, processed, and constructed into a spatial database using GIS and image processing. The factors chosen that influence landslide occurrence were: topographic slope, topographic aspect, topographic curvature and distance from drainage, all from the topographic database; lithology and distance from lineament, taken from the geologic database; land use from TM satellite images; and the vegetation index value from SPOT satellite images. Landslide hazardous area were analysed and mapped using the landslide-occurrence factors by logistic regression model. The results of the analysis were verified using the landslide location data and compared with probabilistic model. The validation results showed that the logistic regression model is better prediction accuracy than probabilistic model.

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Topographic Analysis of Landslides in Umyeonsan (우면산 산사태 발생 지점의 지형분석)

  • Ko, Suk Min;Lee, Seung Woo;Yune, Chan-Young;Kim, Gihong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.32 no.1
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    • pp.55-62
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    • 2014
  • In this study, we investigated the landslides area which occurred in Umyeonsan in 2011 and collected landslide location data. Using this field data with aerial photos and LiDAR data which is obtained before and after disaster event, we analyzed the landslide occurrence frequency per unit area about various topographic characteristics. In case of slope, we compared two kind of slopes which are calculated with Neighborhood algorithm and maximum slope algorithm. Also we used aspect, elevation, profile curvature and planform curvature in topographic analysis of landslide occurrence locations. As a result, the region of which maximum slope is $40^{\circ}-45^{\circ}$ is relatively hazardous in landslide. If the perpendicular surface to the direction of the maximum slope is concave, it is more hazardous than other case.

Weight Determination of Landslide Factors Using Artificial Neural Networks (인공신경 망을 이용한 산사태 발생요인의 가중치 결정)

  • 류주형;이사로;원중선
    • Economic and Environmental Geology
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    • v.35 no.1
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    • pp.67-74
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    • 2002
  • The purpose of this study is to determine the weights of the factors for landslide susceptibility analysis using artificial neural network. Landslide locations were identified from interpretation of aerial photographs, field survey data, and topography. The landslide-related factors such as topographic slope, topographic curvature, soil drainage, soil effective thickness, soil texture, wood age and wood diameter were extracted from the spatial database in study area, Yongin. Using these factors, the weights of neural networks were calculated by backpropagation training algorithm and were used to determine the weight of landslide factors. Therefore, by interpreting the weights after training, the weight of each landslide factor can be ranked based on its contribution to the classification. The highest weight is topographic slope that is 5.33 and topographic curvature and soil texture are 1 and 1.17, respectively. Weight determination using backprogpagation algorithms can be used for overlay analysis of GIS so the factor that have low weight can be excluded in future analysis to save computation time.

Evaluation of Soil Compaction Using Gravity Field Interpretation and UAV-based Remote Sensing Information (중력 데이터 해석과 드론원격정보를 이용한 지반의 다짐도 평가)

  • Kim, Sung-Wook;Choi, Sungchan;Choi, Eun-Kyoung;Lee, Yeong-Jae;Go, Daehong;Lee, Kyu-Hwan
    • The Journal of Engineering Geology
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    • v.31 no.3
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    • pp.283-293
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    • 2021
  • The homogeneity of the compacted ground was analyzed using drone-based remote terrain and gravity field data. Among the topographic elements calculated by the hydrological algorithm, the topographic curvature effectively showed the shape of the surface that occurred during the compaction process, and the non-uniformly compacted area could be identified. The appropriate resolution of the digital topography requires a precision of about 10 cm. Gravity field Interpretation was performed to analyze the spatial density change of the compacted ground. In the distribution of residual bouguer gravity anomaly, the non-homogeneously compacted area showed a different magnitude of gravity than the surrounding area, and the difference in compaction was identified through gravity-density modeling. From the results, it is expected that the topographic element and gravitational field analysis method can be used to evaluate the homogeneity of the compacted ground.

APPLICATION OF LIKELIHOOD RATIO MODEL FOR LANDSLIDE SUSCEPTIBILITY MAPPING USING GIS AT LAI CHAU, VIETNAM

  • LEE SARO;DAN NGUYEN TU
    • Proceedings of the KSRS Conference
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    • 2004.10a
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    • pp.314-317
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    • 2004
  • The aim of this study was to evaluate the susceptibility from landslides in the Lai Chau region of Vietnam, using Geographic Information System (GIS) and remote sensing data, focusing on the relationship between tectonic fractures and landslides. Landslide locations were identified from an interpretation of aerial photographs and field surveys. Topographic and geological data and satellite images were collected, processed, and constructed into a spatial database using GIS data and image processing techniques, and a scheme of the tectonic fracturing of the crust in the Lai Chau region was established. In this scheme, Lai Chau was identified as a region with low crustal fractures, with the grade of tectonic fracture having a close relationship with landslide occurrence. The factors found to influence landslide occurrence were: topographic slope, topographic aspect, topographic curvature, distance from drainage, lithology, distance from a tectonic fracture and land cover. Landslide prone areas were analyzed and mapped using the landslide occurrence factors employing the probability-likelihood ratio method. The results of the analysis were verified using landslide location data, and these showed a satisfactory agreement between the hazard map and existing landslide location data.

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PROBABILISTIC LANDSLIDE SUSCEPTIBILITY AND FACTOR EFFECT ANALYSIS

  • LEE SARO;AB TALIB JASMI
    • Proceedings of the KSRS Conference
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    • 2004.10a
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    • pp.306-309
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    • 2004
  • The susceptibility of landslides and the effect of landslide-related factors at Penang in Malaysia using the Geographic Information System (GIS) and remote sensing data have been evaluated. Landslide locations were identified in the study area from interpretation of aerial photographs and from field surveys. Topographical and geological data and satellite images were collected, processed, and constructed into a spatial database using GIS and image processing. The factors chosen that influence landslide occurrence were: topographic slope, topographic aspect, topographic curvature and distance from drainage, all from the topographic database; lithology and distance from lineament, taken from the geologic database; land use from Landsat TM (Thermatic Mapper) satellite images; and the vegetation index value from SPOT HRV (High Resolution Visible) satellite images. Landslide hazardous areas were analysed and mapped using the landslide-occurrence factors employing the probability-frequency ratio method. To assess the effect of these factors, each factor was excluded from the analysis, and its effect verified using the landslide location data. As a result, land 'cover had relatively positive effects, and lithology had relatively negative effects on the landslide susceptibility maps in the study area. In addition, the landslide susceptibility maps using the all factors showed the relatively good results.

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ROC Analysis of Topographic Factors in Flood Vulnerable Area considering Surface Runoff Characteristics (지표 유출 특성을 고려한 홍수취약지역 지형학적 인자의 ROC 분석)

  • Lee, Jae Yeong;Kim, Ji-Sung
    • Ecology and Resilient Infrastructure
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    • v.7 no.4
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    • pp.327-335
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    • 2020
  • The method of selecting an existing flood hazard area via a numerical model requires considerable time and effort. In this regard, this study proposes a method for selecting flood vulnerable areas through topographic analysis based on a surface runoff mechanism to reduce the time and effort required. Flood vulnerable areas based on runoff mechanisms refer to those areas that are advantageous in terms of the flow accumulation characteristics of rainfall-runoff water at the surface, and they generally include lowlands, mild slopes, and rivers. For the analysis, a digital topographic map of the target area (Seoul) was employed. In addition, in the topographic analysis, eight topographic factors were considered, namely, the elevation, slope, profile and plan curvature, topographic wetness index (TWI), stream power index, and the distances from rivers and manholes. Moreover, receiver operating characteristic analysis was conducted between the topographic factors and actual inundation trace data. The results revealed that four topographic factors, namely, elevation, slope, TWI, and distance from manholes, explained the flooded area well. Thus, when a flood vulnerable area is selected, the prioritization method for various factors as proposed in this study can simplify the topographical analytical factors that contribute to flooding.