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[en] Due to an oversight, four references were cited incorrectly in the reference list of the original publication as well as in the text of the publication. The first names were used instead of the last names of the authors. In addition some author names were omitted inadvertently. The correct presentation of these references is shown below.
[en] The article “Landslide susceptibility mapping of the Sera River Basin using logistic regression model,” written by Nussaïbah B. Raja, Ihsan Çiçek, Necla Türkoğlu, Olgu Aydin, and Akiyuki Kawasaki, was originally published Online First without open access.
[en] The sudden departure mechanism of high-speed landslides has always constituted a popular yet difficult research topic. Therefore, although a systematic classification of high-speed landslides is necessary, particularly since different types of landslides exhibit different mechanisms, an associated methodology has yet to be established. This paper investigates an easily overlooked phenomenon—landslide-quake, which is defined as a local ground vibration triggered by the sudden rupture of the locked segment of a high-speed landslide that occurs immediately prior to the departure of the landslide. This new concept is employed as a foundation for a new classification. The characteristics and formation conditions of landslide-quake are discussed, based upon which the high-speed landslides that occurred following the 2008 Wenchuan earthquake are classified into three different types. Subsequently, the sudden departure mechanism of each type of landslide is analyzed, thereby providing a new method for research on the sudden departure mechanism of high-speed landslides.
[en] Prediction on landslide displacement plays an important role in landslide early warning. Many models have been proposed for this purpose. However, the accuracy of the prediction results by these models often varies under different conditions. Rational evaluation and comprehensive consideration of these results still remain a scientific challenge. A new comprehensive combination model is proposed to predict the landslides displacement. The elementary displacement prediction is made by the support vector machine model, the exponential smoothing model, and the gray model (GM)(1,1). The results of the models are comprehensively evaluated by combining the results and introducing the accuracy matrix. The optimal weight in the evaluation work is obtained. A rational prediction result can be attained based on the so-called combination model. The proposed method has been tested by the application of Qinglong landslides in Guizhou Province, China. The comparison between the prediction results and in situ measurement shows that the prediction precision of the proposed model is satisfactory. The root-mean-square error (RMSE) of the combination model can be reduced to 1.4316 (monitoring site JCK2), 1.2623 (monitoring site JCK4), 2.3758 (monitoring site JCK6), 2.2704 (monitoring site JCK8), 1.4247 (monitoring site JCK11), and 0.9449 (monitoring site JCK12), which is much lower than the RMSE of the individual models.
[en] Highlights: • In Uganda, decentralised platforms are used as spatial tactics to centralise power for the ruling party. • Decentralised platforms may co-produce unequal risk through blame dissolution and scale jumping. • A problematic implementation of decentralised platforms prevents competent disaster governance. - Abstract: The international agenda for disaster risk reduction, through the Hyogo Framework for Action and the Sendai Framework for disaster risk reduction, promotes decentralised platforms as an indispensable strategy to achieve effective and efficient disaster risk management. Based on empirical data from the Rwenzori Mountains region, we question the implications of this type of network governance for disaster risk management. We embed our observations in an analytical framework that combines literature on network governance with insights from politics of disaster, notably scale and blame theories. In this study, we investigate the implications for disaster risk reduction through the analysis of three processes of scale structuration observed in contemporary West Uganda: (i) incomplete decentralisation, (ii) blame dissolution, and (iii) scale jumping. We argue that decentralised platforms in Uganda co-produce unequal risk, as they are used as spatial tactics to centralise power for the ruling party and enable blame dissolution and scale jumping. From our analysis we draw broader conclusions on drivers and implications of the implementation of disaster network governance in countries that are primarily governed hierarchically and that endorse the international frameworks of disaster risk reduction.
[en] Radon, as a chemical element of radioactivity, is widely used in the fields of earth-quake monitoring, prospecting mine and exploring resource. This paper discussed the theory of radon's separating out from the soil and the theory and means of surveying radon. It also relates the radon anomaly in the measuring process of soil radon, caused by the interferring of the environmental factors in measurement results. It further clarifies the wilde application of radon as a tracer in landslide forecast. (authors)
[en] We present an analysis of caldera evolution at Miyakejima in 2000. The caldera changed its structure from piston to funnel subsidence during its growth. The successive subsidence of the central block induced landslides at the caldera wall, which successively enlarged the diameter of the caldera.
[en] This paper investigates the spatial stationarity of the relationship between landslide susceptibility and associated factors in Three Gorges Reservoir area, a landslide-rich area in China. Two logistic regression (LR) models have been used: A global LR (LR) assumes that the regression coefficients remain constant over the whole region, whereas a geographically weighted LR (GWLR) allows the regression coefficients to differ at the local scale. In LR model, lithology seems to have positive influence on the location of landslides, as it has a positive regression coefficient (0.005), while the other factors all have negative effects on landslide susceptibility as they all have negative coefficients. However in GWLR model, lithology does not always keep positive influence, as its coefficients range from −0.533 to 0.695. These results indicate a degree of spatial variation in the relationship between landslide susceptibility and the influencing factors in the study area. Furthermore, six evaluation criteria, based on the fit and complexity of the models, were used to compare the two approaches: deviance, corrected Akaike’s information criterion (AICc), local percent deviance explained (pdev), receiver operating characteristic curve (ROC), Bayesian information criterion (BIC), and residual Moran’s I. The results suggest that GWLR model provides potential advantages in landslide susceptibility mapping and sheds new light on the spatial non-stationarity of the relationship between landslide susceptibility and its influencing factors.