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21.
航空伽马能谱地形改正新方法及应用 总被引:5,自引:2,他引:5
针对航空伽马能谱测量特点,推导了基于二维地形影响系数的航空伽马能谱测量地形逐点改正的理论公式。通过模型试验,总结了不同地形上不同飞行方式时的航空放射性异常特征,给出实测数据处理与野外异常查证对比结果,地形改正效果较好。 相似文献
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伴随模式同化系统在修正模式地形中的应用 总被引:7,自引:1,他引:7
任何模式都只是实际大气的一种近似模拟,存在误差。鉴于传统的四维资料伴随模式同化系统都是假设模式完全正确仅对初始场进行修正。将伴随模式同化系统应用于修正模式地形误差,通过对不同初始地形的修正试验表明,MM5伴随模式同化系统能很好地对地形误差进行修正,能够反演出与初始气象要素场分辨率相匹配、与模式更协调的地形场,为伴随模式同化系统的广泛应用提供了一种新的思路。 相似文献
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基于DEM的地形简化方法对比分析 总被引:4,自引:0,他引:4
地形简化作为一门重要的数据压缩技术已广泛应用于DEM。在大量简化算法中,地形简化指标作为地形简化的核心环节,其好坏直接关系到地形简化的好坏。本文对基于局部误差、曲率和法向量的五个地形简化指标进行了分析评价,用离散的高斯合成曲面来模拟真实DEM,以解析得到的高斯曲率作为地形简化指标“真值”,对比研究了在离散高斯曲面上得到的五个简化指标与解析所得“真值”,通过对各个指标“保特征性”可信度的分析,获得了对这五个指标的整体评价,最后,实例验证了本文结论的正确性。 相似文献
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1 INTRODUCTION There were many flood disasters in China in recent years. When the water level in a river is very high, weak parts of its dike may be destroyed resulted in the submersion of the protected land and properties. It is of significance for decision-makers to exactly predict the processes of flood propagation during flood control. There are many modes of dike bursting, such as seepage destroying by overflow on top of dike caused by dike body sinking induced by piping and soil fl… 相似文献
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The growing availability of digital topographic data and the increased reliability of precipitation forecasts invite modelling efforts to predict the timing and location of shallow landslides in hilly and mountainous areas in order to reduce risk to an ever‐expanding human population. Here, we exploit a rare data set to develop and test such a model. In a 1·7 km2 catchment a near‐annual aerial photographic coverage records just three single storm events over a 45 year period that produced multiple landslides. Such data enable us to test model performance by running the entire rainfall time series and determine whether just those three storms are correctly detected. To do this, we link a dynamic and spatially distributed shallow subsurface runoff model (similar to TOPMODEL) to an in?nite slope model to predict the spatial distribution of shallow landsliding. The spatial distribution of soil depth, a strong control on local landsliding, is predicted from a process‐based model. Because of its common availability, daily rainfall data were used to drive the model. Topographic data were derived from digitized 1 : 24 000 US Geological Survey contour maps. Analysis of the landslides shows that 97 occurred in 1955, 37 in 1982 and ?ve in 1998, although the heaviest rainfall was in 1982. Furthermore, intensity–duration analysis of available daily and hourly rainfall from the closest raingauges does not discriminate those three storms from others that did not generate failures. We explore the question of whether a mechanistic modelling approach is better able to identify landslide‐producing storms. Landslide and soil production parameters were ?xed from studies elsewhere. Four hydrologic parameters characterizing the saturated hydraulic conductivity of the soil and underlying bedrock and its decline with depth were ?rst calibrated on the 1955 landslide record. Success was characterized as the most number of actual landslides predicted with the least amount of total area predicted to be unstable. Because landslide area was consistently overpredicted, a threshold catchment area of predicted slope instability was used to de?ne whether a rainstorm was a signi?cant landslide producer. Many combinations of the four hydrological parameters performed equally well for the 1955 event, but only one combination successfully identi?ed the 1982 storm as the only landslide‐producing storm during the period 1980–86. Application of this parameter combination to the entire 45 year record successfully identi?ed the three events, but also predicted that two other landslide‐producing events should have occurred. This performance is signi?cantly better than the empirical intensity–duration threshold approach, but requires considerable calibration effort. Overprediction of instability, both for storms that produced landslides and for non‐producing storms, appears to arise from at least four causes: (1) coarse rainfall data time scale and inability to document short rainfall bursts and predict pressure wave response; (2) absence of local rainfall data; (3) legacy effect of previous landslides; and (4) inaccurate topographic and soil property data. Greater resolution of spatial and rainfall data, as well as topographic data, coupled with systematic documentation of landslides to create time series to test models, should lead to signi?cant improvements in shallow landslides forecasting. Copyright © 2003 John Wiley & Sons, Ltd. 相似文献
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