Journal•ISSN: 1226-4806
Geosciences Journal
Springer Science+Business Media
About: Geosciences Journal is an academic journal published by Springer Science+Business Media. The journal publishes majorly in the area(s): Groundwater & Geology. It has an ISSN identifier of 1226-4806. Over the lifetime, 1273 publications have been published receiving 15872 citations.
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TL;DR: In this article, a revised terrane classification based on Vendian-Cambrian geodynamic units and evolution of terranes is described. And reactivated suture zones along the terrane boundaries are proposed, which suggest the important role of strike-slip deformations in the formation of mosaic block structure of Central Asia.
Abstract: The paper reviews and integrates new results on the evolution of the Paleo-Asian Ocean and its related geodynamics and geology of Altai-Sayan Region (ASR) in Central Asia. A revised terrane classification based on Vendian-Cambrian geodynamic units and evolution of terranes is described. Reactivated suture zones along the terrane boundaries are proposed. The obtained data suggest the important role of strike-slip deformations in the formation of mosaic-block structure of Central Asia. Those complicated and multi-stage deformations resulted from the Late Devonian-Early Carboniferous collision of Gondwana-derived terranes. The deformations reached their peak in the Late Carboniferous-Permian due to the collision of the Kazakhstan and Siberian continents. A system of sinistral strike-slip faults formed ASR along the margin of the Siberian continent as a result of the Late Carboniferous-Permian collision. The intrusion of granites occurred in East Kazakhstan and northwestern Gorny Altai in the Late Carboniferous and Permian. This resulted in the formation of the Northern Eurasia continent. Geodynamic evolution of the Paleo-Asian ocean and paleotectonics of ASR allow to recognize in the region the following five geodynamic stages: Vendian-Early Cambrian, Early Ordovician, Early-Middle Devonian, Late-Devonian-Early Carboniferous and Late Carboniferous-Early Permian times.
273 citations
TL;DR: In this article, the authors reviewed the recent advances and the state-of-the-art in the essential components of the landslide hazard assessment, such as landslide susceptibility analysis, runout modeling, landslide monitoring and early warning, were reviewed.
Abstract: Landslide is one of the repeated geological hazards during rainy season, which causes fatalities, damage to property and economic losses in Korea. Landslides are responsible for at least 17% of all fatalities from natural hazards worldwide, and nearly 25% of annual casualties caused by natural hazards in Korea. Due to global climate change, the frequency of landslide occurrence has been increased and subsequently, the losses and damages associated with landslides also have been increased. Therefore, accurate prediction of landslide occurrence, and monitoring and early warning for ground movements are very important tasks to reduce the damages and losses caused by landslides. Various studies on landslide prediction and reduction in landslide damage have been performed and consequently, much of the recent progress has been in these areas. In particular, the application of information and geospatial technologies such as remote sensing and geographic information systems (GIS) has greatly contributed to landslide hazard assessment studies over recent years. In this paper, the recent advances and the state-of-the-art in the essential components of the landslide hazard assessment, such as landslide susceptibility analysis, runout modeling, landslide monitoring and early warning, were reviewed. Especially, this paper focused on the evaluation of the landslide susceptibility using probabilistic approach and physically based method, runout evaluation using volume based model and dynamic model, in situ ground based monitoring techniques, remote sensing techniques for landslide monitoring, and landslide early warning using rainfall and physical thresholds.
213 citations
TL;DR: In this paper, a landslide susceptibility analysis at Al-Hasher area, Jizan, KSA, using two statistical models: frequency ratio and index of entropy models with the aid of GIS tools and remote sensing data.
Abstract: Mountain areas in the southern western corner of the Kingdom of Saudi Arabia frequently suffer from various types of landslides due to rain storms and anthropogenic activities. To resolve the problem related to landslides, landslide susceptibility map is important as a quick and safe mitigation measure and to help making strategic planning by identifying the most vulnerable areas. This paper summarizes findings of landslide susceptibility analysis at Al-Hasher area, Jizan, KSA, using two statistical models: frequency ratio and index of entropy models with the aid of GIS tools and remote sensing data. The landslide locations (inventory map) were identified in the study area using historical records, interpretation of high-resolution satellite images that include Geo-Eye in 2.5 m and Quickbird in 0.6m resolution, topographic maps of 1:10,000 scale, and multiple field investigations. A total of 207 landslides (80% out of 257 detected landslides) were randomly selected for model training, and the remaining 50 landslides (19%) were used for the model validation. Ten landslide conditioning factors including slope angle, slope-aspect, altitude, curvature, lithology, distance to lineaments, normalized difference vegetation index (NDVI), distance to roads, precipitation, and distance to streams, were extracted from spatial database. Using these conditioning factors and landslide locations, landslide susceptibility and weights of each factor were analyzed by using frequency ratio and index of entropy models. Our findings showed that the existing landslides of high and very high susceptibility classes cover nearly 80.4% and 79.1% of the susceptibility maps produced by frequency ratio and index of entropy models respectively. For verification, receiver operating characteristic (ROC) curves were drawn and the areas under the curve (AUC) were calculated for success and prediction rates. For success rate the results revealed that for the index of entropy model (AUC = 77.9%) is slightly lower than frequency ratio model (AUC = 78.8%). For the prediction rate, it was found that the index of entropy model (AUC = 74.9%) is slightly lower than the frequency ratio model (AUC = 76.7%). The landslide susceptibility maps produced from this study could help decision makers, planners, engineers, and urban areas developers to make suitable decisions.
195 citations
TL;DR: In this article, the authors proposed the subdivision of the Cambrian System into four series representing subequal spans of time, the lower two series correspond approximately to the traditional Lower Cambrian, the third series corresponds approximately to a traditional Middle Cambrian and the fourth series corresponds roughly to an Upper Cambrian.
Abstract: Important steps have been made toward global subdivision of the Cambrian System. The consensus of opinion is that the system should be subdivided into four series representing subequal spans of time. The lower two series will correspond approximately to the traditional Lower Cambrian, the third series will correspond approximately to the traditional Middle Cambrian, and the fourth series corresponds approximately to the traditional Upper Cambrian. The fourth series, called the Furongian Series, has been ratified by the International Union of Geological Sciences (IUGS). Selection of horizons representing evolutionary events that can be correlated on a global scale, and which can be used as stage or series boundaries, is much more difficult for the lower two series intervals of the Cambrian than it is for the upper two series intervals of the Cambrian. The most practical concept for subdividing the system into stages involves the establishment of two stages each for the first and second series, and establishment of three stages each for the third and fourth series. The lowermost stage of the Furongian, called the Paibian Stage, has been ratified by the IUGS, and the International Subcommission on Cambrian Stratigraphy (ISCS) is nearing decisions on the levels that will used to mark the bases of the upper two stages of the Furongian. Concerning stage boundaries within the proposed third series of the Cambrian, the ISCS is close to decisions on two levels that will be used to mark boundaries.
163 citations
TL;DR: In this article, a landslide inventory was partitioned into three groups as various training and test datasets to identify the most appropriate method for creating a landslide susceptibility map, and a total of fifteen landslide susceptibility maps were produced using frequency ratio, logistic regression, decision tree, weights of evidence and artificial neural network models, and the results were assessed using existing test landside points and areas under the relative operative characteristic curve.
Abstract: For the purpose of comparing susceptibility mapping methods in Mizunami City, Japan, the landslide inventory was partitioned into three groups as various training and test datasets to identify the most appropriate method for creating a landslide susceptibility map. A total of fifteen landslide susceptibility maps were produced using frequency ratio, logistic regression, decision tree, weights of evidence and artificial neural network models, and the results were assessed using existing test landside points and areas under the relative operative characteristic curve (AUC). The validation results indicated that the logistic regression model could provide the highest AUC value (0.865), and a relatively high percentage of landslide points fell in the high and very high landslide susceptibility classes in this study. Furthermore, the paper also suggested that the model performances would be increased if appropriate landslide points were used for the calculation.
153 citations