• 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.

• Proceedings of the Korea Water Resources Association Conference
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• 1999.05a
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• pp.262-267
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• 1999

• Proceedings of the Korea Water Resources Association Conference
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• 1999.05a
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• pp.307-312
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• 1999

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.507-514
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• 2018

TSI (TPI-Slope Index) which is the combination of TPI (Topographic Position Index) and slope was newly proposed for landslide and applied to a landslide susceptibility model. To do this, we first compared the TPIs with various scale factors and found that TPI350 was the best fit for the study area. TPI350 was combined with slope to create TSI. TSI was evaluated using logistic regression. The evaluation showed that TSI can be used as a landslide factor. Then a logistic regression model was developed to assess the landslide susceptibility by adding other topographic factors, geological factors, and forestial factors. For this, landslide-related factors that can be extracted from DEM (Digital Elevation Model), soil map, and forest type map were collected. We checked these factors and excluded those that were highly correlated with other factors or not significant. After these processes, 8 factors of TSI, elevation, slope length, slope aspect, effective soil depth, tree age, tree density, and tree type were selected to be entered into the regression analysis as independent variables. Three models through three variable selection methods of forward selection, backward elimination, and enter method were built and evaluated. Selected variables in the three models were slightly different, but in common, effective soil depth, tree density, and TSI was most significant.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2004.09a
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• pp.147-150
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• 2004

Firstly, the precipitation data have to be interpolated for the estimation of water resources. For this purpose, the correlative analysis is made between the topographic variables, which, influence the precipitation phenomena, are classified by elevation(ELEV), slope(SLOPE), distance to the sea(SEA), obstacle (OBST), barrier(BAR), and roughness index(SHIELD), using TOVA(Topographic Variables Extraction Program) and events precipitation during the periods from january the 1st 2000 to December 31 2002. The coefficients of determination show that each event has different topographic influence and ELEV, SLOPE and OBST to the South-West, and SHIELD of every direction have close relationship with the precipitation. The multiple regression model explains 96% of the spatial variation of precipitation.

• Journal of Korea Water Resources Association
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• v.33 no.3
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• pp.279-288
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• 2000

The impact of land slope to the degree of flow divergence was considered employing distributional applications of slope exponents in the now directlOn algoriUnns. Lmear, exponential and ]X)wer law of distributional functIons were employed to address the variation of slope exponents m a terrain analysis. Dongok subwatershed at Wichun test watershed was selected as a study area. Digital Elevation Models of 20m, 30m, 40m and 50m grid size were made to perfonn the analysis. Various calcualtion methodologies of topographic index and the impact of grid sizes were investigated in terms of statistical and spatial aspects. DIstributional applications of slope e.xponents made it possible to represent the flow divergence and convergence about the ten-ain characteristics. The Monte~Carlo method was used to simulate six runoff events to check the impact of topographic factor in the runoff simulation.

• Korean Journal of Agricultural Science
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• v.45 no.4
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• pp.749-760
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• 2018

In Korea, the largest agricultural lands are paddy fields which have poor infiltration and drainage properties. Recently, the Korean government has pursued cultivating upland crops in paddy fields to reduce overproduced rice in Korea. For this policy to succeed, it is critical to understand the topographic information of paddy fields and its effects on upland crops cultivated in the soils of paddy fields. The objective of this study was to characterize the growth properties of sesame and perilla from paddy fields with three soil topographic features and soil water effects which were induced by the topographic features of the sesame and perilla. The crops were planted in paddy fields located in Miryang, Gyeongnam with different topographies: mountain foot slope, local valley and alluvial plain. Soil water contents and groundwater levels were measured every hour during the growing season. The paddy field of the mountain foot slope was significantly effective in alleviating wet injury for the sesame and perilla in the paddy fields. The paddy field of the mountain foot slope had a decreased average soil water content and groundwater level during cultivation. Stress day index (SDI) from the alluvial plain paddy field had the greatest values from both crops and the smallest from the ones from the paddy field of the mountain foot slope. This result means that sesame and perilla had the smallest stress from the soil water content of the paddy field on the mountain foot slope and the greatest stress from the soil water content of the alluvial plain. It is important to consider the topography of paddy fields to reduce wet injury and to increase crop yields.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.573-575
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• 2003

In satellite spectra, Though the magnitude varies with intensity of sunstroke, dip angle of land so on, the shape is less deformed with these effects. from this point of view, we have developed a spectral shape-dependent analysis utilizing a normalization procedure by the spectral integral and applied it to Landsat/TM spectra. Inevitable topographic and atmospheric effects can be suppressed. The correction algorithm is very simple and timesaving and the suppression of topographic effects is especially effective. Normalized band 4 is almost linear to NDVI values, and is available to the vegetation index.

• 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.

• Journal of the Korean Geographical Society
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• v.44 no.3
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• pp.207-223
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• 2009

The TOPMODEL Topographic Index (TI) is widely used to predict the spatial distribution of soil moisture contents, The TI is one of terrain indices which are frequently used in spatially distributed environmental modelings. There have been studies on the evaluation and improvement of the TI. Most of them. however, have focused on only the modified multiple flow direction algorithm and algorithms for slope calculation have been paid little attention, In this research, we attempted to improve the TI by utilizing the infinitive flow direction (Dinf) algorithm and Horn slope algorithm. Then we attempt to analyze and evaluate the influence of the improved TI on hydrological responses of the TOPMODEL As a result. our approaching using the infinitive flow direction (Dinf) and Horn slope algorithm made the TI better than the multiple flow direction (MD8) - the multiple descent slope (MDS) algorithm. However, the model efficiency of discharges at the outlet was not increased. Our research may provide an insight to choose appropriate algorithms for calculating flow direction and slope in spatially distributed environmental modelings.