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51.
Chang-Jo F. Chung 《Mathematical Geology》1993,25(7):851-865
Multivariate statistical analyses have been extensively applied to geochemical measurements to analyze and aid interpretation of the data. Estimation of the covariance matrix of multivariate observations is the first task in multivariate analysis. However, geochemical data for the rare elements, especially Ag, Au, and platinum-group elements, usually contain observations the below detection limits. In particular, Instrumental Neutron Activation Analysis (INAA) for the rare elements produces multilevel and possibly extremely high detection limits depending on the sample weight. Traditionally, in applying multivariate analysis to such incomplete data, the observations below detection limits are first substituted, for example, each observation below the detection limit is replaced by a certain percentage of that limit, and then the standard statistical computer packages or techniques are used to obtain the analysis of the data. If a number of samples with observations below detection limits is small, or the detection limits are relatively near zero, the results may be reasonable and most geological interpretations or conclusions are probably valid. In this paper, a new method is proposed to estimate the covariance matrix from a dataset containing observations below multilevel detection limits by using the marginal maximum likelihood estimation (MMLE) method. For each pair of variables, sayY andZ whose observations containing below detection limits, the proposed method consists of three steps: (i) for each variable separately obtaining the marginal MLE for the means and the variances,
,
,
, and
forY andZ: (ii) defining new variables by
and
and lettingA=C+D andB=C–D, and obtaining MLE for variances,
and
forA andB; (iii) estimating the correlation coefficient YZ by
and the covariance
YZ
by
. The procedure is illustrated by using a precious metal geochemical data set from the Fox River Sill, Manitoba, Canada. 相似文献
52.
Many stochastic process models for environmental data sets assume a process of relatively simple structure which is in some sense partially observed. That is, there is an underlying process (Xn, n 0) or (Xt, t 0) for which the parameters are of interest and physically meaningful, and an observable process (Yn, n 0) or (Yt, t 0) which depends on the X process but not otherwise on those parameters. Examples are wide ranging: the Y process may be the X process with missing observations; the Y process may be the X process observed with a noise component; the X process might constitute a random environment for the Y process, as with hidden Markov models; the Y process might be a lower dimensional function or reduction of the X process. In principle, maximum likelihood estimation for the X process parameters can be carried out by some form of the EM algorithm applied to the Y process data. In the paper we review some current methods for exact and approximate maximum likelihood estimation. We illustrate some of the issues by considering how to estimate the parameters of a stochastic Nash cascade model for runoff. In the case of k reservoirs, the outputs of these reservoirs form a k dimensional vector Markov process, of which only the kth coordinate process is observed, usually at a discrete sample of time points. 相似文献
53.
Stephanie de Villiers 《中国地球化学学报》2006,25(B08):146-146
Acidification is considered the most important one of the primary chemical stress factors that impact on freshwater ecosystems. In unpolluted freshwater systems, the primary controls on the degree of acidification are factors such as the geological substrate of the catchment area, the presence of organic acids secreted by vegetation in the river system, and equilibrium exchange of carbon dioxide with the atmosphere. Anthropogenic factors that can impact on the degree of acidification of freshwater systems include agricultural, mining and industrial activities, either through direct runoff into river systems or through deposition of atmospheric pollutants from these sources. The capacity factors alkalinity and acidity, which represent the acid- and base-neutralizing capacity (ANC and BCN) of an aqueous system, have been used as more reliable measures of the acidic character of freshwater systems than pH. Unlike pH, ANC and BNC are not affected by parameters such as temperature and pressure. Therefore, ANC has been employed as a predictor of biological status in critical load assessments. Freshwater systems with ANC's eq/L isμeq/L are considered sensitive to acidification, ANC=0 μbelow 150 commonly used as the predictor for fish species such as trout in lakes, and an eq/L as more realistic for streams. Acid-neutralizing capacity μANC value of 40 (ANC) can be determined by titration with a strong acid to a preselected equivalence point. Alternatively, it can be calculated as the difference between base cations ([BC]) and strong acid anions ([SAA]): ANC=[BC]- [SAA]=[Ca^2+]+[Mg^2+]+[Na^+]+[K^+]-[SO4^2-]-[NO3^-]-[Cl^-] To date, there has been no attempt to establish the ANC of South Africa's freshwater ecosystems or variability therein, despite the fact that long-term water quality monitoring data exist for all the parameters needed to calculate it according to the above equations. As a result, the relationship between the acid neutralizing capacity of freshwater ecosystems in South Africa and biodiversity factors, such as fish status, is unknown. Results of the first comprehensive (country-wide scale) evaluation of the acid neutralizing capacity of river systems in South Africa will be presented. Long-term monitoring data obtained from the Department of Water Affairs and Forestry (DWAF) from most of South Africa's river systems were used to establish geographic and temporal variabilities in ANC. The results show that the Berg and Breede River systems are most susceptible to acidification, and that geological substrate appears to explain most of the geographic variabilities observed. 相似文献
54.
Habib Ben Hassine 《Comptes Rendus Geoscience》2006,338(5):329-340
The cereal soils of the Northwest of Tunisia derive most of the time, from alluvial deposits or altered remains of carbonated and clayey rocks. Extraction of the clayey fraction permitted to reveal the presence of the following clayey minerals: kaolinite, illite, smectite, chlorite, as well as an illite–smectite interstratified layer, which is present in the deep horizons of the vertisol and in the isohumic soil. The presence of such types of clays shows that the evolution mechanism of soils is weathering of primary minerals inherited from the sedimentary rocks of the Northwest of Tunisia. These clays ensure to soils most of their cationic exchange capacity. Thanks to these clays, which have Ca++, Mg++ and K+ as exchangeable cations, the chemical fertility of these soils is ensured. It may be improved by increasing contents of organic matter, which is naturally few abundant in these soils. To cite this article: H. Ben Hassine, C. R. Geoscience 338 (2006). 相似文献
55.
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57.
基于RS和GIS的青藏高原草地生态系统土壤水分保持功能及其经济价值评估——以生长季为例 总被引:2,自引:0,他引:2
根据生态系统服务功能理论,利用RS和G IS技术,以土壤含水量为基础因子,对青藏高原区草地生态系统的土壤水分保持功能及其价值的动态变化过程进行有效评价,以直接的货币形式反映出青藏高原主要草地类型的土壤水分保持功能的大小。通过计算和分析发现:(1)由于草地类型分布面积、单位面积保持量的影响,各种类型草地提供的土壤水分保持功能及其价值贡献率有较大差异,按照大小依次为:高寒草原类、高寒草甸类,高寒荒漠类、高寒草甸草原类和温性山地草甸类;(2)草地对土壤水分保持量及其价值呈现出较强的阶段性变化过程;(3)由于各种草地类型所处地理区域不同、草地本身各种自然特点和整体生态功能的不同,青藏高原草地生态系统提供的土壤水分保持功能及其经济价值呈现出明显的地域分布规律:自西北至东南逐渐降低。应该说,由于青藏高原地域、地理和独特气候等原因所致,本文计算得出的青藏高原草地生态系统土壤水分保持功能及其价值的具体数值不一定十分准确,但是能在一定程度上反映出土壤水分保持功能的强大及其在生长季中随时间变化的动态过程和基本规律(这种规律性结论与前人研究结论一致),这是一种在区域尺度上揭示草地生态系统土壤水分保持功能及其价值动态变化过程的方法尝试,这也是对动态评估生态服务功能的一种有益尝试。 相似文献
58.
A new earthquake catalogue for central, northern and northwestern Europe with unified Mw magnitudes, in part derived from chi-square maximum likelihood regressions, forms the basis for seismic hazard calculations
for the Lower Rhine Embayment. Uncertainties in the various input parameters are introduced, a detailed seismic zonation is
performed and a recently developed technique for maximum expected magnitude estimation is adopted and quantified. Applying
the logic tree algorithm, resulting hazard values with error estimates are obtained as fractile curves (median, 16% and 84%
fractiles and mean) plotted for pga (peak ground acceleration; median values for Cologne 0.7 and 1.2 m/s2 for probabilities of exceedence of 10% and 2%, respectively, in 50 years), 0.4 s (0.8 and 1.5 m/s2) and 1.0 s (0.3 and 0.5 m/s2) pseudoacclerations, and intensity (I0 = 6.5 and 7.2). For the ground motion parameters, rock foundation is assumed. For the area near Cologne and Aachen, maps
show the median and 84% fractile hazard for 2% probability of exceedence in 50 years based on pga (maximum median value about
1.5 m/s2), and 0.4 s (>2 m/s2) and 1.0 s (about 0.8 m/s2) pseudoaccelerations, all for rock. The pga 84% fractile map also has a maximum value above 2 m/s2 and shows similarities with the median map for 0.4 s. In all maps, the maximum values fall within the area 6.2–6.3° E and
50.8–50.9° N, i.e., east of Aachen. 相似文献
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