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Species richness is a measure that is fundamental to many studies in ecology, and it is particularly important on sandy beaches, where it underlies patterns described by the broadly accepted swash exclusion hypothesis. However, its estimation in practice is problematic. This has led ecologists in other fields to adopt extrapolative estimators of species richness, which project the total number of species present in a habitat by adjusting upward the number of species observed by an amount related to the number of rare species encountered in the samples. In so doing, the species richness can be estimated, with confidence intervals, at any level of sampling effort. Despite the availability and advantages of these methods, beach ecologists have continued to use the observed species richness as a point estimate of biodiversity for beaches. Here, we employ a Monte Carlo resampling approach over a range of routine transect designs used to sample sandy beaches, and evaluate the performance of seven non-parametric extrapolative estimators for species richness relative to that of the more conventionally used observed species richness. We find that the first-order Jackknife estimator (Jack 1) is the least biased, most accurate and most consistent across sites. Employing this estimator would allow accurate estimation of species richness on short (tens of metres) stretches of beach without exceeding the acceptable levels of sampling effort (4–5 m2). Spreading this effort evenly over three across-shore transects, each with a minimum of 13 equally spaced levels seems appropriately efficient. Although a greater number of research studies is required to ascertain the generality of these results beyond the beaches we sampled, we tentatively recommend the application of our results in biodiversity surveys on sandy beaches.  相似文献   
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The sea level of Northeast Atlantic Ocean is calculated for the period between 1958 and 2001 using a state-of-the-art barotropic model with a grid size of 10′ × 15′ (long × lat). The model includes astronomic effects, considering seven components of the tide, and the meteorological effects of wind and atmospheric pressure, allowing obtaining the astronomic tide, the atmospheric residuals and the non-linear addition of both components of sea level.  相似文献   
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ABSTRACT

We designed a unique hyperspectral experiment from the Earth Observing One (EO-1) orbit change to evaluate solar illumination effects over tropical forests in Brazil. Ten nadir-viewing Hyperion images collected over a fixed site and period of the year (July to August) were selected for analysis. We evaluated variations in reflectance and in 16 narrowband vegetation indices (VIs) with increasing solar zenith angle (SZA) from the pre-drift (2004–2008) to the EO-1 drift period (2011–2016). To detect changes in reflectance and shadows, we applied spectral mixture analysis (SMA) and principal component analysis (PCA) and calculated the similarity spectral angle (θ) between the vegetation spectra measured with variable SZA. The magnitude of the illumination effects was also evaluated from change-point analysis and nonparametric Mann-Whitney U tests applied over the time series. Finally, we complemented our experiment using the PROSAIL model to simulate the VIs variation with increasing SZA resultant from satellite drift. The results showed significant changes in Hyperion reflectance and VIs, especially when the EO-1 crossed the study area at earlier times and larger SZA in 2015 (9:05 a.m.; SZA = 59°) and 2016 (8:30 a.m.; SZA = 67°). Compared to the pre-drift period (10:30 a.m.; SZA = 45°), the SZA differences of 14° (2015) and 22° (2016) increased the shade fractions and decreased the vegetation brightness. PCA separated the pre-drift and drift reflectance datasets, showing shifts in scores due to changes in brightness. θ increased with SZA, indicating changes in the shape of the vegetation spectra with drift. For most VIs, the change-point analysis indicated 2015 (SZA = 59°) as the predominant year of detected changes. Compared to the EO-1 original orbit, the Plant Senescence Reflectance Index (PSRI), Anthocyanin Reflectance Index (ARI) and Structure Insensitive Pigment Index (SIPI) presented the largest positive changes during drift, while the Photochemical Reflectance Index (PRI), Visible Atmospherically Resistant Index (VARI) and Enhanced Vegetation Index (EVI) had the largest negative changes. The effect size of the illumination geometry on these VIs was large, as indicated by increasing values of the Cohen’s r metric toward 2016. The anisotropy of the Hyperion VIs was generally consistent with that from PROSAIL in the simulated pre-drift and drift periods. Focusing on structural indices, it affected the relationships between VIs and simulated leaf area index (LAI) at large SZA.  相似文献   
16.
An audio-magnetotelluric investigation in Terceira Island (Azores)   总被引:2,自引:0,他引:2  
Ten audio-magnetotelluric soundings have been carried out along a profile crossing the Serra do Cume caldera in the eastern part of the Terceira Island (Azores). The main objectives of this investigation were to detect geoelectrical features related with tectonic structures and to characterize regional hydrological and hydrothermal aspects mainly those related to geothermal fluid dynamics.Three-dimensional numerical investigation showed that the data acquired at periods shorter than 1 s are not significantly affected by ocean effect. The data was analysed using the Smith's decomposition method in order to investigate possible distortions caused by superficial structures and to estimate a global regional strike. The results suggest that in general the soundings were not distorted. A regional N55°W strike was chosen for the two-dimensional data inversion.The low-resistivity zones (10–30 ohm-m) displayed in the central part of the 2-D geoelectrical model have been interpreted as caused by hydrothermal circulation. The low-resistivity anomalies at the ends of the profile might be attributed to alteration zones with interaction of seawater intrusion. High-resistivity (> 300 ohm-m) values have been related with less permeable zones in the SW of Cinco Picos and Guilherme Moniz caldera walls.  相似文献   
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Combined methods of fission track (FTM) and U–Pb in situ zircon dating were applied to sedimentary samples from the Vale do Rio do Peixe Formation, Bauru Basin, Brazil. Detrital zircons of nine samples were determined by the FTM, and the obtained ages varied from 239 Ma–825 Ma, which can be grouped into four main populations as the 230–300 Ma, 460–490 Ma, 500–650 Ma and 696–825 Ma groups. The U–Pb data show two clear source areas: the Early Paleozoic to Neoproterozoic zircons, ranging from 445 ± 14 to 708 ± 18 Ma, and the Paleoproterozoic zircons, ranging from 1879 ± 23 to 2085 ± 27 Ma. Subordinate occurrences of Early Neoproterozoic to Mesoproterozoic zircons (836 ± 15 and 1780 ± 38 Ma) were identified. The combined information allows us to characterize Early Brazilian, Brazilian and Rhyacian material as the main source for the zircons, which are areas situated to west of the Bauru Basin (e.g., Goiás Massif) that have been incorporated into the sedimentary cycles in the Phanerozoic (mainly in the Paraná Basin). FT zircon ages reflect the main denudation processes of the South American Plate from Neoproterozoic to Early Triassic as those related to orogenic cycles of Early Brazilian, Brazilian, Famatinian/Cuyanian and Gondwanide.  相似文献   
19.
Air pollution is usually driven by a complex combination of factors in which meteorology, physical obstacles, and interactions between pollutants play significant roles. Considering the characteristics of urban atmospheric pollution and its consequent impacts on human health and quality of life, forecasting models have emerged as an effective tool to identify and forecast air pollution episodes. The overall objective of the present work is to produce forecasts of pollutant concentrations with high spatio-temporal resolution and to quantify the uncertainty in those forecasts. Therefore, a new approach was developed based on a two-step methodology. Firstly, neural network models were used to generate short-term temporal forecasts based on air pollution and meteorology data. The accuracy of those forecasts was then evaluated against an independent set of historical data. Secondly, local conditional distributions of the observed values with respect to the predicted values were used to perform spatial stochastic simulations for the entire geographic area of interest. With this approach the spatio-temporal dispersion of a pollutant can be predicted, while accounting for both the temporal uncertainty in the forecast (reflecting the neural networks efficiency at each monitoring station) and the spatial uncertainty as revealed by the spatial variograms. Based on an analysis of the results, our proposed method offers a highly promising alternative for the characterization of urban air quality.  相似文献   
20.
Recently, the increasing demand for biofuels triggered a new phase for the sugar‐alcohol sector. In Brazil, as well as in other tropical countries, this process raised worries regarding the possible direct and indirect effects of the crop's expansion on the conversion of native vegetation coverings. Therefore, the modeling of spatial‐economic surfaces, representing the potential rent variation in its spatial component, for economic activities, may be a useful tool in the decision‐making process. Hence, here we propose and present the results of a combined framework composed of two modules using the modeling platform Dinamica EGO. The first module simulates sugarcane's growth, calculating the daily response of the crop to environmental conditions during the stages of the plant's development. The second module estimates rents for sugarcane cultivation in Brazil, identifying areas where this activity would bring higher economic return, looking at simulated productivity, production costs and selling prices in a way that is spatially explicit for Brazil. Two different scenarios for production costs were tested, and results ranged from negative values to maxima of R$/ha 929 and R$/ha 1176 for standard and efficient costs of production, respectively. The model successfully indicated non‐profitable and profitable areas, and regions where high expected economic return overlaps endangered ecosystems.  相似文献   
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