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331.
The city of Catania (Italy) in the South-Eastern Sicily has been affected in past times by several destroying earthquakes with high values of estimated magnitude. The seismogenic area to the south of Volcano Etna, known as Iblean Area, is placed between the African and the Euro-Asiatic plates on the west of the Ibleo-Maltese escarpment, to the south of the Graben of the Sicilian channel and on the east of the overlapping front of Gela. Basing on the seismic history of Catania, the following earthquake scenarios have been considered: the “Val di Noto” earthquake of January 11, 1693 (with intensity X-XI on MCS scale, magnitude MW=7.41 and epicentral distance of about 13 km); the “Etna” earthquake of February 20, 1818 (with intensity IX on MCS scale, magnitude MW=6.23 and epicentral distance of about 10 km). The soil response analysis at the surface, in terms of time history and response spectra, has been obtained by 1-D equivalent linear models for about 1200 borings location available in the data-bank of the central area of Catania of about 50 km2, using deterministic design scenario earthquakes as input at the conventional bedrock.Seismic microzoning maps of the city of Catania have been obtained in terms of different peak ground acceleration at the surface and in terms of amplification ratios for given values of frequency. 相似文献
332.
An earthquake measuring 5.1 on the Richter scale struck Wen'an county,Hebei Province on July 4,2006. No casualties have been reported,with only slight damage. The disaster level of this event is the slightest on the M4.9~5.1 events record tally since the CCDSN (China Center of Digital Seismic Network) was built in 1999. The epicenter intensity of this earthquake was low,while in areas like Beijing,which is 100km far away,abnormal high intensity zones appeared. This article discusses the reasons behind this abnormal phenomenon,with the diagrams of intensity isolines drawn by the intense seismic stations and networks in the capital circle area as references,as well as the seismogenic mechanism in the source,the seismic histories,the geological structures and the ray pathways of seismic waves in areas within 150km around the epicenter. It was concluded that the special dynamic and geological situations were the main causes for the lower intensity degree and slight damage in the epicenter area,but higher intensity in the surrounding areas. 相似文献
333.
The Anqing MS4.8 earthquake occurred on January 19, 2011, with the epicenter lying in the foreland deformation belt along the Yangtze River of the lower Yangtze block. After the earthquake, the field work team surveyed and collected building damage data, calculating and obtaining more accurate intensity distributions. The focal mechanism of the main shock was calculated tentatively using digital seismic wave data from provincial digital seismic networks using the FOCMEC program and the first motions of P, SV and SH waves with their amplitude ratios. Using the location results of the main shock and aftershocks by the Anhui seismic network, combining the three-dimensional crust velocity structure imaging results of the focal region by seismic tomography, and referring on intensity distribution of the elliptic major axis’ predominant direction, we conclude by comprehensive analysis that the NE-trending Susong-Zongyang fault is possibly the causative fault of the Anqing earthquake. 相似文献
334.
335.
《地震研究进展(英文)》2023,3(1):100184
The 2022 MS 6.8 Luding earthquake is the strongest earthquake in Sichuan Province, Western China, since the 2017 MS 7.0 Jiuzhaigou earthquake. It occurred on the Moxi fault in the southeastern segment of the Xianshuihe fault, a tectonically active and mountainous region with severe secondary earthquake disasters. To better understand the seismogenic mechanism and provide scientific support for future hazard mitigation, we summarize the preliminary results of the Luding earthquake, including seismotectonic background, seismicity and mainshock source characteristics and aftershock properties, and direct and secondary damage associated with the mainshock. The peak ground displacements in the NS and EW directions observed by the nearest GNSS station SCCM are ~35 mm and ~55 mm, respectively, resulting in the maximum coseismic dislocation of 20 mm along the NWW direction, which is consistent with the sinistral slip on the Xianshuihe fault. Back-projection of teleseismic P waves suggest that the mainshock rupture propagated toward south-southeast. The seismic intensity of the mainshock estimated from the back-projection results indicates a Mercalli scale of VIII or above near the ruptured area, consistent with the results from instrumental measurements and field surveys. Numerous aftershocks were reported, with the largest being MS 4.5. Aftershock locations (up to September 18, 2022) exhibit 3 clusters spanning an area of 100 km long and 30 km wide. The magnitude and rate of aftershocks decreased as expected, and the depths became shallower with time. The mainshock and two aftershocks show left-lateral strike-slip focal mechanisms. For the aftershock sequence, the b-value from the Gutenberg-Richter frequency-magnitude relationship, h-value, and p-value for Omori’s law for aftershock decay are 0.81, 1.4, and 1.21, respectively, indicating that this is a typical mainshock-aftershock sequence. The low b-value implies high background stress in the hypocenter region. Analysis from remote sensing satellite images and UAV data shows that the distribution of earthquake-triggered landslides was consistent with the aftershock area. Numerous small-size landslides with limited volumes were revealed, which damaged or buried the roads and severely hindered the rescue process. 相似文献
336.
《New Astronomy》2024
A huge collection of solar images to visualize sunspot are acquired by various solar observatories spread across the globe. This necessitates efficient tools for detecting and analyzing the sunspots encompassing diverse solar features. One such contribution is delivered in this work by exploiting the intrinsic intensity variations of solar images associated with sunspots and their attributes. The presented mechanism initially, pre-processes the acquired solar images by correcting the intensity variations introduced while profiling from the sun center to the limb followed by smoothening using a localized window. The resultant is then differenced from the global threshold that is obtained as a result of the statistical analysis computed over the probability distribution function of the input image. This arrangement offers higher discerning variations concerned with the local contextual structures related to sunspot, umbra, and penumbra. Also, it captures the major gradient variation between these regions that adds to the pixel heterogeneity surrounding them to finally render an automatic sunspot detection mechanism distinguishing the diverse solar regions. Receiver Operating Characteristics (ROC) investigation on annual solar images in Flexible Image Transport System (FITS) format reveals the presented method’s efficacy. Also, Pearson correlation analysis of the evaluated sunspot numbers from the detected sunspots with the solar catalog reveals the scheme’s detection closeness. Moreover, the model’s simplicity analyzed along the time and space dimensions affirms its extension to real-time analysis 相似文献