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Leo Šeparović Adelina Alexandru René Laprise Andrey Martynov Laxmi Sushama Katja Winger Kossivi Tete Michel Valin 《Climate Dynamics》2013,41(11-12):3167-3201
The fifth-generation Canadian Regional Climate Model (CRCM5) was used to dynamically downscale two Coupled Global Climate Model (CGCM) simulations of the transient climate change for the period 1950–2100, over North America, following the CORDEX protocol. The CRCM5 was driven by data from the CanESM2 and MPI-ESM-LR CGCM simulations, based on the historical (1850–2005) and future (2006–2100) RCP4.5 radiative forcing scenario. The results show that the CRCM5 simulations reproduce relatively well the current-climate North American regional climatic features, such as the temperature and precipitation multiannual means, annual cycles and temporal variability at daily scale. A cold bias was noted during the winter season over western and southern portions of the continent. CRCM5-simulated precipitation accumulations at daily temporal scale are much more realistic when compared with its driving CGCM simulations, especially in summer when small-scale driven convective precipitation has a large contribution over land. The CRCM5 climate projections imply a general warming over the continent in the 21st century, especially over the northern regions in winter. The winter warming is mostly contributed by the lower percentiles of daily temperatures, implying a reduction in the frequency and intensity of cold waves. A precipitation decrease is projected over Central America and an increase over the rest of the continent. For the average precipitation change in summer however there is little consensus between the simulations. Some of these differences can be attributed to the uncertainties in CGCM-projected changes in the position and strength of the Pacific Ocean subtropical high pressure. 相似文献
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Wen-geng Cao Yu Fu Qiu-yao Dong Hai-gang Wang Yu Ren Ze-yan Li Yue-ying Du 《China Geology》2023,81(3):409-419
Landslide is a serious natural disaster next only to earthquake and flood, which will cause a great threat to people’s lives and property safety. The traditional research of landslide disaster based on experience-driven or statistical model and its assessment results are subjective , difficult to quantify, and no pertinence. As a new research method for landslide susceptibility assessment, machine learning can greatly improve the landslide susceptibility model’s accuracy by constructing statistical models. Taking Western Henan for example, the study selected 16 landslide influencing factors such as topography, geological environment, hydrological conditions, and human activities, and 11 landslide factors with the most significant influence on the landslide were selected by the recursive feature elimination (RFE) method. Five machine learning methods [Support Vector Machines (SVM), Logistic Regression (LR), Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Linear Discriminant Analysis (LDA)] were used to construct the spatial distribution model of landslide susceptibility. The models were evaluated by the receiver operating characteristic curve and statistical index. After analysis and comparison, the XGBoost model (AUC 0.8759) performed the best and was suitable for dealing with regression problems. The model had a high adaptability to landslide data. According to the landslide susceptibility map of the five models, the overall distribution can be observed. The extremely high and high susceptibility areas are distributed in the Funiu Mountain range in the southwest, the Xiaoshan Mountain range in the west, and the Yellow River Basin in the north. These areas have large terrain fluctuations, complicated geological structural environments and frequent human engineering activities. The extremely high and highly prone areas were 12043.3 km2 and 3087.45 km2, accounting for 47.61% and 12.20% of the total area of the study area, respectively. Our study reflects the distribution of landslide susceptibility in western Henan Province, which provides a scientific basis for regional disaster warning, prediction, and resource protection. The study has important practical significance for subsequent landslide disaster management. 相似文献
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泾川地区位于鄂尔多斯盆地西南缘,烃源岩发育情况尚不明确。通过野外地质调查和钻井岩心观察,结合烃源岩测试及元素地球化学资料,对长10—长7烃源岩进行评价,在环境分析的基础上研究影响烃源岩发育的主要因素。结果表明:研究区延长组烃源岩以长73泥页岩为最好,有机质类型以Ⅰ型和Ⅱ1为主,TOC为 0.42%~29%;长10—长7泥岩有机质以Ⅱ2型为主,平均TOC含量低于 2%;Ro为 0.47%~1.08%,有机质基本已成熟。长10—长7烃源岩形成于温暖潮湿的环境,弱还原弱氧化的淡水介质条件,水深相对较浅。古生产力、沉积速率及水介质环境影响烃源岩发育。热水活动促进了古生物的繁盛,P、Cu含量及 P/Ti值越高,有机质 TOC含量越高。(La/Yb)N值越高,沉积速率越低,有机质越富集。Cu/Zn值越高,V/Cr值越高,Th/U值越低,水体还原性越好,有机质丰度越高。总之,热水活动提高了古生产力水平,相对较低的沉积速率有利于有机质的富集,还原性较强的水介质条件可使有机质得到良好的保存。陇县一带烃源岩因受陆源植物输入的影响,且形成环境不利,烃源岩品质相对较差。 相似文献
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冠岩洞穴特征与游览开发设计研究 总被引:4,自引:7,他引:4
冠岩是桂林地区空间规模最大的洞穴系统之一,开放3年多以来获得了显著的经济与社会效益,成为我国目前为数不多开发成功的旅游洞穴之一。冠岩开发成功的一个关键原因是重视科学,尤其是洞穴科学研究,并能根据其基本洞穴特征(包括空间结构、形态及洞穴水文特征等) ,按高起点、高水平、高标准进行游览开发规划设计。 相似文献
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本文对东平原狭蚌虫外壳的组织结构进行了研究。外壳由内外角质层、内外上皮层和皮下结缔组织共同组成。外角质层厚,较规则。上皮细胞有柱状细胞和具有胞突的锥形细胞两种形态。同侧及相对两侧的上皮胞突相连接,构成了许多具有血细胞的血腔隙。 相似文献
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