This paper presents an procedure for purifying training data sets （i.e., past occurrences of slope failures） for inverse estimation on unobserved trigger factors of ＂different types of simultaneous slope failures＂...This paper presents an procedure for purifying training data sets （i.e., past occurrences of slope failures） for inverse estimation on unobserved trigger factors of ＂different types of simultaneous slope failures＂. Due to difficulties in pixel-by-pixel observations of trigger factors, as one of the measures, the authors had proposed an inverse analysis algorithm on trigger factors based on SEM （structural equation modeling）. Through a measurement equation, the trigger factor is inversely estimated, and a TFI （trigger factor influence） map can be also produced. As a subsequence subject, a purification procedure of training data set should be constructed to improve the accuracy of TFI map which depends on the representativeness of given training data sets of different types of slope failures. The proposed procedure resamples the matched pixels between original groups of past slope failures （i.e., surface slope failures, deep-seated slope failures, landslides） and classified three groups by K-means clustering for all pixels corresponding to those slope failures. For all cases of three types of slope failures, the improvement of success rates with respect to resampled training data sets was confirmed. As a final outcome, the differences between TFI maps produced by using original and resampled training data sets, respectively, are delineated on a DIF map （difference map） which is useful for analyzing trigger factor influence in terms of ＂risky- and safe-side assessment＂ sub-areas with respect to ＂different types of simultaneous slope failures＂.展开更多
This paper presents a comparative visualization strategy of slope failure susceptibility maps for analyzing different types of simultaneous occurrences of slope failures. Through the SEM （structural equation modeling...This paper presents a comparative visualization strategy of slope failure susceptibility maps for analyzing different types of simultaneous occurrences of slope failures. Through the SEM （structural equation modeling）, slope failure susceptibility maps are produced by using causal factors （i.e., geographical information, satellite remotely sensed data）. As for a conventional pair-wise comparative procedure, the differences between susceptibility maps are delineated on difference maps, that can be, however, applied for evaluating differences only between pairs of susceptibility maps. One of the strong requirements from specialists working on slope stability evaluation is a comparative and visualization strategy of susceptibility maps with respect to ＂different types of simultaneous slope failures＂, for which the discussion is insufficient in the previous research activities for constructing the quantitative models for slope failure hazard mapping. As a measure, a color composite map based on susceptibility maps has been produced. The combination of assigning susceptibility maps to RGB-color planes is determined based on an index of ＂NCCT （normalized correlated color temperature）＂ which represents the relationship between chromaticity and human visual perception. Through the cases examined, the result indicates that the proposed color composite map, as a heuristic visualization strategy, is useful for simultaneously evaluating the hazardous areas affected by ＂different types of slope failures＂.展开更多
文摘This paper presents an procedure for purifying training data sets （i.e., past occurrences of slope failures） for inverse estimation on unobserved trigger factors of ＂different types of simultaneous slope failures＂. Due to difficulties in pixel-by-pixel observations of trigger factors, as one of the measures, the authors had proposed an inverse analysis algorithm on trigger factors based on SEM （structural equation modeling）. Through a measurement equation, the trigger factor is inversely estimated, and a TFI （trigger factor influence） map can be also produced. As a subsequence subject, a purification procedure of training data set should be constructed to improve the accuracy of TFI map which depends on the representativeness of given training data sets of different types of slope failures. The proposed procedure resamples the matched pixels between original groups of past slope failures （i.e., surface slope failures, deep-seated slope failures, landslides） and classified three groups by K-means clustering for all pixels corresponding to those slope failures. For all cases of three types of slope failures, the improvement of success rates with respect to resampled training data sets was confirmed. As a final outcome, the differences between TFI maps produced by using original and resampled training data sets, respectively, are delineated on a DIF map （difference map） which is useful for analyzing trigger factor influence in terms of ＂risky- and safe-side assessment＂ sub-areas with respect to ＂different types of simultaneous slope failures＂.
文摘This paper presents a comparative visualization strategy of slope failure susceptibility maps for analyzing different types of simultaneous occurrences of slope failures. Through the SEM （structural equation modeling）, slope failure susceptibility maps are produced by using causal factors （i.e., geographical information, satellite remotely sensed data）. As for a conventional pair-wise comparative procedure, the differences between susceptibility maps are delineated on difference maps, that can be, however, applied for evaluating differences only between pairs of susceptibility maps. One of the strong requirements from specialists working on slope stability evaluation is a comparative and visualization strategy of susceptibility maps with respect to ＂different types of simultaneous slope failures＂, for which the discussion is insufficient in the previous research activities for constructing the quantitative models for slope failure hazard mapping. As a measure, a color composite map based on susceptibility maps has been produced. The combination of assigning susceptibility maps to RGB-color planes is determined based on an index of ＂NCCT （normalized correlated color temperature）＂ which represents the relationship between chromaticity and human visual perception. Through the cases examined, the result indicates that the proposed color composite map, as a heuristic visualization strategy, is useful for simultaneously evaluating the hazardous areas affected by ＂different types of slope failures＂.
