Kyungduck Min

Probabilistic landslide hazard mapping using GIS and remote sensing data at Boun, Korea

The aim of this study is to evaluate the hazard of landslides at Boun, Korea, using a Geographic Information System (GIS) and remote sensing. Landslide locations were identified in the Boun area from interpretation of aerial photographs and field surveys. The topographic, soil, forest, geologic, lineament and land cover data were collected, processed and constructed into a spatial database using GIS and remote sensing data. The factors that influence landslide occurrence, such as slope, aspect and curvature of the topography, were calculated from the topographic database. Texture, material, drainage and effective soil thickness were extracted from the soil database, and type, age, diameter and density of timber were extracted from the forest database. The lithology was extracted from the geological database and lineaments were detected from Indian Remote Sensing (IRS) satellite images. The land cover was classified based on the Landsat Thematic Mapper (TM) satellite image. Landslide hazard areas were analysed and mapped, using the landslide-occurrence factors, by the probability–likelihood ratio method. The results of the analysis were verified using actual landslide location data. The validation results showed satisfactory agreement between the hazard map and the existing data on landslide locations.

Landslide susceptibility mapping by correlation between topography and geological structure: the Janghung area, Korea

The purpose of this study is to develop and apply the technique for landslide susceptibility analysis using geological structure in a Geographic Information System (GIS). In the study area, the Janghung area of Korea, landslide locations were detected from Indian Remote Sensing (IRS) satellite images by change detection, where the geological structure of foliation was surveyed and analysed. The landslide occurrence factors (location of landslide, geological structure and topography) were constructed into a spatial database. Then, strike and dip of the foliation and the aspect and slope of the topography were compared and the results, which were verified using landslide location data, show that foliation of gneiss has a geometrical relation to the joint or fault that leads to a landslide. Using the geometrical relations, the landslide susceptibility was assessed and verified. The verification results showed satisfactory agreement between the susceptibility map and the landslide location data.

Application of L‐band differential SAR interferometry to subsidence rate estimation in reclaimed coastal land

The subsidence rate in a reclaimed coastal land has been estimated by using JERS‐1 L‐band SAR two‐pass differential interferometry. Measurement of subsidence rate during reclamation is difficult to obtain as a two‐dimensional subsidence map based on sparsely distributed field measurements is required. Owing to the severe temporal decorrelation induced by frequent soil loading and intense deformation gradients, the L‐band was found to be effective for observing subsidence in reclaimed land. We evaluated the accuracy of the estimated subsidence rate using field measurements obtained by a magnetic probe extensometer from 42 ground stations. A two‐dimensional subsidence map was generated from seven qualified pairs. The correlation coefficient R between the two‐dimensional radar measurements and the in situ data was 0.87 with a rms error of 1.42 cm. Two interferometric pairs obtained from an adjoining JERS‐1 path were also used to verify the results. Independent estimations from the two different JERS‐1 paths correlated each other with correlation coefficients R of 0.97 and 0.80. The main sources of the error were the reference DEM errors and additional phase noises calculated from phase fluctuation at stable points. The error from these two sources was ±1.27 cm. The estimated maximum subsidence was about 60 cm over 352 days. The results demonstrate that L‐band differential SAR interferometry is a useful tool in geological engineering applications.

Development of two artificial neural network methods for landslide susceptibility analysis

The purpose of this study is to develop landslide susceptibility analysis techniques using artificial neural networks and to apply the newly developed techniques for assessment of landslide susceptibility to the study area of Yongin in Korea. Landslide locations were identified in the study area from interpretation of aerial photographs, field survey data, and a spatial database of the topography, soil type and timber cover were constructed The landslide-related factors such as topographic slope, topographic curvature, soil texture, soil drainage, soil effective thickness, timber age, and timber diameter were extracted from the spatial database. Using those factors, landslide susceptibility and weights of each factor were analyzed by two artificial neural network methods. In the first method, the landslide susceptibility index was calculated by the back propagation method, which is a type of artificial neural network method. Then, the susceptibility map was made with a GIS program. The results of the landslide susceptibility analysis were verified using landslide location data. The verification results show satisfactory agreement between the susceptibility index and existing landslide location data. In the second method, weights of each factor were determinated. The weights, relative importance of each factor, were calculated using importance-free characteristics method of artificial neural networks. After the calculating of the weight, the slope had the highest value.

Development and application of landslide susceptibility analysis techniques using geographic information system (GIS)

The purpose of this study is to develop landslide susceptibility analysis techniques using a geographic information system (GIS) and to apply the newly developed techniques for assessment of landslide susceptibility to two study areas of Yongin and Janghung, Korea. Landslide locations detected from interpretation of aerial photo and field survey, and topographic, soil, forest, and geological maps of the study area, Yongin, were collected. The data on the locations of landslide, topography, soil, forest and geology were constructed into a spatial database using GIS and landslide related 14 factors were extracted from the databases. Finally landslide susceptibility was analyzed using the landslide related factors by probability, logistic regression and neural network methods. In the other study area, Janghung, landslide locations were detected from IRS satellite images by change detection technique, and geological structure of foliation were surveyed and analyzed. As the landslide occurrence factors, location of landslide, geological structure and topography were constructed into spatial database using GIS. With the landslide occurrence factors, landslide susceptibility was assessed by the relation analysis between strike and dip of the foliation, and aspect and slope of the topography. The results of the analysis were verified using the landslide location data. The validation results showed satisfactory agreement between the susceptibility map and landslide location data.

Observing coal mining subsidence from JERS-1 permanent scatterer analysis

Ground subsidence that occurred in an abandoned coal mining area, Gaeun Korea, is observed by using 25 JERS-1 SAR interferograms from November 1992 to October 1998. We estimate the subsidence on a subset of image corresponding to point-wise permanent scatterers by exploiting a 6-year temporal series of interferometric phases. The SAR measured subsidence rate represents only an average subsidence rate during a period of image acquisition, and complex nonlinear displacements such as an abrupt collapse are excluded. The obtained results are compared with the degree of crack levels obtained by field survey in 1997. The mean line-of-sight subsidence rate was 0.61 cm/yr in the area where the crack level was the most severe, and the largest radar measured subsidence was 11.2 cm. The degree of crack level correlates closely with ground subsidence. A twodimensional subsidence map is also presented and generally complied with crack levels measured by field surveys. Keywords-component; SAR interferometry, mining subsidence, JERS-1, permanent scatterer, crack level.

Wavenumber correlation analysis of radar interferogram

The quality of a radar interferogram can be characterized by wavenumber correlation coefficient. The wavenumber correlation analysis exploits the unique characteristics of the radar interferogram in which in-phase and quadrature-phase terms are highly correlated. One can easily distinguish the signal components from the noise components of the radar interferogram in the wavenumber domain, and consequently this method can be utilized to design a post filter to enhance the interferogram. The wavenumber correlation analysis can also be applied to an amplitude coregistration of a master and slave pair. Test results demonstrate the effectiveness of the proposed approach.