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21.
颗粒物粒径分布(Particle Size Distribution, PSD)代表了颗粒物浓度与颗粒物粒径之间的关系, 影响着海洋生态环境和水体光学特性等。文章基于2016年夏季航次调查的生物光学剖面数据, 研究了南海海盆海域PSD的分布特征。研究发现, 幂律函数可以较好地拟合南海海盆区域的PSD, 对数空间中的实测的PSD与模拟的PSD平均决定系数高达0.95。PSD斜率(ξ)的分布范围为[1.27, 7.65], 均值为3.93±0.56。南海海盆区域表层水体的ξ均值与全球大洋表层水体的ξ均值相近, 但高于海湾等表层水体的ξ均值。ξ能较好地表征颗粒物平均粒径DA的大小, 两者存在明显负相关关系, 即ξ值越高, DA越小; 反之, DA越大。通过分析T1断面的生物光学剖面数据及总体平均的PSD剖面数据, 发现PSD剖面分布特征如下: 1)表层水体的ξ值相对较高, 且DA值相对较低, 推测可能是由于微微型藻类为主导颗粒物所致; 2) ξ值极小值层出现在次表层叶绿素浓度极大值层(Subsurface Chlorophyll Maximum Layer, SCML)中, 并伴随DA极大值层的出现, 其原因可能是SCML中的大粒径浮游植物占比显著增加; 3)弱光层中的ξ值较SCML中的高, 但略低于表层的ξ值, 而DA则位于表层与SCML的DA之间, 这可能与浮游植物及其碎屑的絮凝、分解、沉降等过程相关。PSD特征影响着海水的固有光学特性, 分析发现: 由于SCML中的叶绿素浓度增加, 颗粒物散射系数(bp(532))和颗粒物后向散射系数(bbp(532))也相应呈现显著增加的趋势。弱光层中的平均bp(532)与平均bbp(532)最小。ξ与颗粒物衰减光谱斜率之间呈高分散性, Boss 等(2001b)的模型适合用于粗略估算区域性的ξ分布范围及均值。  相似文献   
22.
印度尼西亚北苏拉威西蓝碧海峡浮游动物种类组成及分布   总被引:1,自引:0,他引:1  
Based on oceanographic survey data in June 2012 in the Lembeh Strait, the zooplankton ecological characteristics such as species composition, individual abundance, dominant species and distribution were analyzed. The results showed that 183 species(including 4 sp.) had been recognized, most of them belonged to copepoda.Cnidaria followed with 43 species(including 1 sp.) were identified. The average abundance of zooplankton was(150.47±58.91) ind./m~3. As to the horizontal distribution, the abundance of the zooplankton was higher in the southern waters than in the northern waters. The dominant species in the study area were Lensia subtiloides,Sagitta enflata, Lucifer intermedius, Oikopleura rufescens, Diphyes chamissoni, Creseis acicula, Subeucalanus subcrassus, Temora discaudata, Aglaura hemistoma, Doliolum denticulatum, Canthocalanus pauper, Oikopleura longicauda and Nanomia bijuga. Zooplankton biodiversity indexes were higher in study area than previous study in the other regions. The findings from this study provide important baseline information for future research and monitoring programs.  相似文献   
23.
邹晓梅  林广发  陈志彪 《海洋科学》2018,42(11):110-117
赤潮是海洋生态系统异常的重要指标。本文收集1986~2017年闽三角海域的赤潮事件,基于GIS技术分析赤潮的时空分布特征。结果表明:32年来,闽三角海域赤潮发生98次,赤潮高发区在厦门西海域、同安湾和泉州湄洲湾海域;闽三角海域赤潮年际发生次数呈波动变化,一年中赤潮高发期集中在5~8月;中肋骨条藻、角毛藻及旋链角毛藻是闽三角海域的赤潮优势种,具有一定的区域分布特征;有毒赤潮事件发生频率有增加趋势。本文系统性地总结了闽三角海域赤潮时空特征,为该区域的赤潮风险分析和预防提供依据。  相似文献   
24.
Whereas the data on mesozooplankton in the epipelagic offshore Mediterranean Sea are extensive, less information is available about plankton in the deeper layers. The present study aims to describe the vertical and horizontal structure and distribution of mesozooplankton species and their associations down to 1,200 m in the water of the Southern Adriatic Sea. Zooplankton were sampled using a Nansen net of 200‐μm mesh size during two cruises in the winters of 2015 and 2016, extending from the coast to the open sea. In total, 203 zooplankton taxa were identified. The community was dominated by copepods, representing between 67% and 91% of the total abundance. The highest total densities were recorded in the upper layers where a high proportion (up to 36%) of appendicularians was also observed in the first sampled year. Five groups of samples were determined based on their community structure. In 2015 communities were distinct between the 0 and 50 m layer and the underlying one (50–100 m), whereas in 2016 epipelagic waters were inhabited by a more uniform mesozooplankton community. The mesopelagic and deep‐water fauna, especially copepods, showed a relatively stable composition in both sampling years Overall, our study confirms the oligotrophic character of the Southern Adriatic, with occasional density outbreaks of appendicularians under favourable conditions.  相似文献   
25.
Accepting the concept of standardization introduced by the standardized precipitation index, similar methodologies have been developed to construct some other standardized drought indices such as the standardized precipitation evapotranspiration index (SPEI). In this study, the authors provided deep insight into the SPEI and recognized potential deficiencies/limitations in relating to the climatic water balance it used. By coupling another well‐known Palmer drought severity index (PDSI), we proposed a new standardized Palmer drought index (SPDI) through a moisture departure probabilistic approach, which allows multi‐scalar calculation for accurate temporal and spatial comparison of the hydro‐meteorological conditions of different locations. Using datasets of monthly precipitation, temperature and soil available water capacity, the moisture deficit/surplus was calculated at multiple temporal scales, and a couple of techniques were adopted to adjust corresponding time series to a generalized extreme value distribution out of several candidates. Results of the historical records (1900–2012) for diverse climates by multiple indices showed that the SPDI was highly consistent and correlated with the SPEI and self‐calibrated PDSI at most analysed time scales. Furthermore, a simple experiment of hypothetical temperature and/or precipitation change scenarios also verified the effectiveness of this newly derived SPDI in response to climate change impacts. Being more robust and preferable in spatial consistency and comparability as well as combining the simplicity of calculation with sufficient accounting of the physical nature of water supply and demand relating to droughts, the SPDI is promising to serve as a competent reference and an alternative for drought assessment and monitoring. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   
26.
Historically, observing snow depth over large areas has been difficult. When snow depth observations are sparse, regression models can be used to infer the snow depth over a given area. Data sparsity has also left many important questions about such inference unexamined. Improved inference, or estimation, of snow depth and its spatial distribution from a given set of observations can benefit a wide range of applications from water resource management, to ecological studies, to validation of satellite estimates of snow pack. The development of Light Detection and Ranging (LiDAR) technology has provided non‐sparse snow depth measurements, which we use in this study, to address fundamental questions about snow depth inference using both sparse and non‐sparse observations. For example, when are more data needed and when are data redundant? Results apply to both traditional and manual snow depth measurements and to LiDAR observations. Through sampling experiments on high‐resolution LiDAR snow depth observations at six separate 1.17‐km2 sites in the Colorado Rocky Mountains, we provide novel perspectives on a variety of issues affecting the regression estimation of snow depth from sparse observations. We measure the effects of observation count, random selection of observations, quality of predictor variables, and cross‐validation procedures using three skill metrics: percent error in total snow volume, root mean squared error (RMSE), and R2. Extremes of predictor quality are used to understand the range of its effect; how do predictors downloaded from internet perform against more accurate predictors measured by LiDAR? Whereas cross validation remains the only option for validating inference from sparse observations, in our experiments, the full set of LiDAR‐measured snow depths can be considered the ‘true’ spatial distribution and used to understand cross‐validation bias at the spatial scale of inference. We model at the 30‐m resolution of readily available predictors, which is a popular spatial resolution in the literature. Three regression models are also compared, and we briefly examine how sampling design affects model skill. Results quantify the primary dependence of each skill metric on observation count that ranges over three orders of magnitude, doubling at each step from 25 up to 3200. Whereas uncertainty (resulting from random selection of observations) in percent error of true total snow volume is typically well constrained by 100–200 observations, there is considerable uncertainty in the inferred spatial distribution (R2) even at medium observation counts (200–800). We show that percent error in total snow volume is not sensitive to predictor quality, although RMSE and R2 (measures of spatial distribution) often depend critically on it. Inaccuracies of downloaded predictors (most often the vegetation predictors) can easily require a quadrupling of observation count to match RMSE and R2 scores obtained by LiDAR‐measured predictors. Under cross validation, the RMSE and R2 skill measures are consistently biased towards poorer results than their true validations. This is primarily a result of greater variance at the spatial scales of point observations used for cross validation than at the 30‐m resolution of the model. The magnitude of this bias depends on individual site characteristics, observation count (for our experimental design), and sampling design. Sampling designs that maximize independent information maximize cross‐validation bias but also maximize true R2. The bagging tree model is found to generally outperform the other regression models in the study on several criteria. Finally, we discuss and recommend use of LiDAR in conjunction with regression modelling to advance understanding of snow depth spatial distribution at spatial scales of thousands of square kilometres. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   
27.
稀土元素是现代科技、新能源、特种制造的关键性材料, 以其不可替代性和稀缺性, 而备受关注, 很多国家将其列为关键资源或战略资源。地球化学是研究稀土分布和发现稀土矿床的有效方法。本文利用“化学地球”大科学计划获得的全国15个稀土元素地球化学基准数据以及“一带一路”的中蒙边境、中缅老越边境地区地球化学填图数据为基础, 阐述中国稀土地球化学背景和圈定远景区。获得全国岩石和汇水域沉积物15个稀土元素、轻稀土(ΣLREE)、重稀土(ΣHREE)和总稀土(ΣREE)背景值。全国岩石背景值分别为: ΣLREE 121 μg/g, ΣHREE 35.0 μg/g, ΣREE 157 μg/g, 轻重稀土比值为3.5。全国汇水域沉积物背景值分别为: ΣLREE 134.0 μg/g, ΣHREE 38.5 μg/g, 和ΣREE 173 μg/g, 轻重稀土比值为3.5。总体上汇水域沉积物与岩石一致, 但含量略高于岩石。全国共圈定稀土地球化学异常区35处, 其中有26处异常与已知稀土矿或稀土成矿带相吻合, 新发现稀土超富集中心的稀土异常9处, 分别位于内蒙白云鄂博以西的乌拉特中旗—乌拉特后旗、华南异常富集中心、松潘—甘孜—攀西地区、云南红河州—中越边境、三江南段—中缅边境、雅鲁藏布江东段、西藏札达地区、中塔边境、黔东正安—荔波地区。这些异常显示, 是具有寻找白云鄂博型、碱性岩型、离子吸附型、花岗伟晶岩型、磷块岩型和泥岩型稀土矿的有利地区。  相似文献   
28.
宜人气候可以分为避暑型和避寒型两种类型,但现有研究鲜有关注国内两类气候的分布特征及差异。本文采用1981—2010年2132个国家气象观测站数据,基于温湿指数、风寒指数和着衣指数计算各个气象站点的气候综合舒适指数,结合协同克里金空间插值方法对全国避暑型和避寒型宜人气候的分布特征进行了研究,并对两类气候的地域差异进行了分析。结果表明:① 中国避暑型气候区包括40°N以北的西北边疆和东北地区、西北中部地区及西南地区三大集中分布区。中国避寒型气候区集中分布在北回归线以南的低纬地区。② 国内夏冬两季的气候不舒适地域广阔,包括环渤海、长三角等经济发达、人口稠密地区,避暑型与避寒型气候资源的开发潜力显著。③ 两类宜人气候呈现明显的地域分离特征,拥有避暑和避寒双重属性的地方极少。④ 国内避寒型气候是稀缺资源,具有垄断性特征;而避暑型气候相对分布广泛,是一种相对遍在性资源。本文不仅丰富了宜人气候分布特征研究的理论成果,而且可为地方气候资源的旅游开发提供科学依据。  相似文献   
29.
传统卡尔曼滤波算法要求噪声模型符合高斯分布,在UWB室内定位中,由于载体本身的机制等干扰,观测噪声不仅仅是白噪声,也存在有色噪声的情况,而粒子滤波可以处理有色噪声的问题。本文通过增加似然分布自适应调整来改进粒子滤波用于目标跟踪的精度,同时研究在白噪声、有色噪声下似然分布自适应调整粒子滤波和拓展卡尔曼滤波在UWB中的优势与不同。试验结果表明:观测噪声为白噪声时,拓展卡尔曼滤波和粒子滤波均可以较好地实现对行人的定位跟踪;观测噪声为有色噪声时,自适应粒子滤波定位效果优于粒子滤波、拓展卡尔曼滤波。  相似文献   
30.
2001-2015年中国植被覆盖人为影响的时空格局   总被引:3,自引:0,他引:3  
基于MODIS-NDVI和气温、降水数据,使用基于变异系数的人为影响模型定量计算了2001-2015年中国植被覆盖人为影响,辅以趋势分析、Hurst指数等方法探讨了中国植被覆盖人为影响的时空变化特征及未来演变趋势。研究发现:① 2001-2015年,中国植被覆盖人为影响由南向北空间分异愈发明显,年均值为-0.0102,植被覆盖在人类活动影响下轻微减少,负影响面积占51.59%,略大于正影响面积。② 中国植被覆盖人为影响年际变化特征明显,整体呈负影响波动减少趋势,降速为0.5%/10a,其中正影响、负影响均呈增大趋势,正影响增速(0.3%/10a)远大于负影响(0.02%/10a)。③ 2001-2015年间,中国植被覆盖人为正影响重心向东北方向移动,负影响重心向西南方向移动,东北部植被覆盖在人为影响下不断改善,西南部人类活动对植被破坏程度不断增大。④ 中国植被覆盖人为影响主要呈负影响减少和正影响增大趋势,面积占比分别为28.14%和25.21%,生态环境趋于改善。⑤ Hurst指数分析表明,中国植被覆盖人为影响未来演变趋势的反向特征强于正向特征,主要呈人为负影响先减少后增大趋势,面积占比15.59%。  相似文献   
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