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排序方式: 共有1204条查询结果,搜索用时 31 毫秒
51.
Analysis of the Chiufengershan landslide triggered by the 1999 Chi-Chi earthquake in Taiwan 总被引:18,自引:0,他引:18
A disastrous earthquake rocked Taiwan on September 21, 1999, with magnitude ML=7.3 and an epicenter near the small town of Chi-Chi in central Taiwan. The Chi-Chi earthquake triggered landslide on the dip slope at the Chiufengershan. In this study, a review of the topography and geology of this area was followed by field investigations. Laboratory testing was applied to understand the geomaterial composing the slope. Then, based on a series of limit equilibrium analyses, the failure mechanism of this landslide and the risk of the residual slope were studied.
According to the stability analyses, the pre-quake slope is quite stable, with factor of safety of 1.77 (dry) to 1.35 (full groundwater level); explaining why there is no written record of a landslide here for the past 100 years. In contrast, a back analysis shows that the Chi-Chi earthquake-induced dynamic loading is far more than the dip slope can sustain, due in part to the short distance to the epicenter. A Monte Carlo type probability analysis suggests that the residual slope is more dangerous than the pre-quake slope and needs more attention. 相似文献
52.
Spatial probabilistic modeling of slope failure using an integrated GIS Monte Carlo simulation approach 总被引:4,自引:0,他引:4
Spatial probabilistic modeling of slope failure using a combined Geographic Information System (GIS), infinite-slope stability model and Monte Carlo simulation approach is proposed and applied in the landslide-prone area of Sasebo city, southern Japan. A digital elevation model (DEM) for the study area has been created at a scale of 1/2500. Calculated results of slope angle and slope aspect derived from the DEM are discussed. Through the spatial interpolation of the identified stream network, the thickness distribution of the colluvium above Tertiary strata is determined with precision. Finally, by integrating an infinite-slope stability model and Monte Carlo simulation with GIS, and applying spatial processing, a slope failure probability distribution map is obtained for the case of both low and high water levels. 相似文献
53.
54.
Validation of Landslide Susceptibility Maps; Examples and Applications from a Case Study in Northern Spain 总被引:9,自引:3,他引:9
Remondo Juan González Alberto De Terán José Ramón Díaz Cendrero Antonio Fabbri Andrea Chung Chang-Jo F. 《Natural Hazards》2003,30(3):437-449
A procedure for validating landslide susceptibility maps wasapplied in a study area in northern Spain and the results obtained compared. Validationwas used to carry out sensitivity analysis for individual variables and combinationsof variables. The validity of different map-making methods was tested, as well as theutility of different types of Favourability Functions. The results obtained show thatvalidation is essential to determine the predictive value of susceptibility maps. Italso helps to better select the most suitable function and significant variables, thus improving the efficiency of the mapping process. Validation based on a temporal strategy makes it possible to derive hazard maps from susceptibility maps. 相似文献
55.
斜向坡变形破坏机制的数值模拟研究 总被引:3,自引:0,他引:3
本文讨论了斜向坡的旋转式变形和破坏机制,用有限元法计算了此种斜坡中的剩余下滑力的分布方式,并以此来解释在滑动过程中发生一定旋转的原因;论文还运用离散元法,模拟了此种滑坡的滑动过程。 相似文献
56.
某滑坡区滑带土工程地质特性研究 总被引:5,自引:0,他引:5
本文论述了某滑坡滑带土的工程地质特性及其滑坡稳定性的影响,为滑坡的合理整治提供了依据。 相似文献
57.
滑坡时间预报的费尔哈斯反函数模型法 总被引:7,自引:0,他引:7
费尔哈斯模型是德国生物学家费尔哈斯1937年提出的一种生物增长模型。本文利用这一模型的反函数来拟合和描述边坡变形特征,建立了滑坡时间的预报判据和预报模型。 相似文献
58.
边坡变形系统失稳控制因素研究 总被引:3,自引:0,他引:3
通过对顺层变形几何非线性和连续变形物理非线性边坡模型的讨论,建立了边坡为形系统失稳的条件,找出影响系统稳定性的控制变量,并就控制变量的因素进行探讨,提出了人为调整控制变量,来防止边坡系统失稳措施的设想。 相似文献
59.
Data driven bivariate landslide susceptibility assessment using geographical information systems: a method and application to Asarsuyu catchment, Turkey 总被引:27,自引:0,他引:27
In the last decades, landslide hazard assessment has attracted many researchers' attention. A number of parameters are suggested to be responsible to quantitatively explain the mechanism of landslides; many of these parameters are very important and factual. However, some data types and models are site-specific and could not be applied to different locations. Furthermore, the data stored in continuous parameter maps are divided into a number of classes arbitrarily, depending on the vision of the expert. Basically, this division controls the result of bivariate analysis. Besides, the responsible portion of the parameter map controlling the mechanism is also weighted arbitrarily. Based on these two facts, the class boundaries put a prejudice on the produced susceptibility/hazard maps, which result in dependence on the knowledge of the user rather than being dependent on the data and the fact itself. The aim of this study is to refine the previously defined methods in a more data-dependent trend. To achieve this goal, two new concepts: seed cells and percentile maps are introduced. Seed cells are the zones that are considered to represent the best undisturbed morphological decision rules (conditions before landslide occurs) and would be achieved by adding a buffer zone to the crown and flank areas of the landslide. To quantitatively classify the input parameter maps, the data distributions of seed cells in the parameter maps are divided into a number of classes on the basis of their distribution's percentile break-points upon which the parameter maps are directly dependent on the seed cell distributions, hence to the data itself. 相似文献
60.
Determination and application of the weights for landslide susceptibility mapping using an artificial neural network 总被引:38,自引:0,他引:38
The purpose of this study is the development, application, and assessment of probability and artificial neural network methods for assessing landslide susceptibility in a chosen study area. As the basic analysis tool, a Geographic Information System (GIS) was used for spatial data management and manipulation. Landslide locations and landslide-related factors such as slope, curvature, soil texture, soil drainage, effective thickness, wood type, and wood diameter were used for analyzing landslide susceptibility. A probability method was used for calculating the rating of the relative importance of each factor class to landslide occurrence. For calculating the weight of the relative importance of each factor to landslide occurrence, an artificial neural network method was developed. Using these methods, the landslide susceptibility index (LSI) was calculated using the rating and weight, and a landslide susceptibility map was produced using the index. The results of the landslide susceptibility analysis, with and without weights, were confirmed from comparison with the landslide location data. The comparison result with weighting was better than the results without weighting. The calculated weight and rating can be used to landslide susceptibility mapping. 相似文献