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121.
结合中尺度数值模式 WRF 预报数据和 ERA5 再分析资料,利用机器学习方法对 WRF 预报场的风场、温度、气压进行预报订正。采用 ERA5 作为真值,与原始 WRF 预报相比,利用随机森林模型可以将预报结果整体均方根误差降低 44%以 上,利用深度神经网络模型可以将预报结果整体均方根误差降低 34%以上。通过随机森林模型实验得到不同输入特征对预报要素的影响程度,分析了关键的预报订正因子。  相似文献   
122.
Gravel road surfaces can be a major source of fine sediment to streams, yet their contribution to channel reach sediment balances remains poorly documented. To quantify the input of road surface material and to compare this input with natural sediment sources at the reach scale, suspended sediment dynamics was examined and a 16‐month sediment balance was developed for a ~35 channel‐width (approx. 425 m) reach of the Honna River, a medium‐size, road‐affected stream located in coastal British Columbia. Of the 105 ± 33 t of suspended material passing through the reach, 18 ± 6% was attributed to the road surface. The high availability of sediment on the road surface appears to limit hysteresis in road run‐off. During rainstorms that increase streamflow, road surface material composed 0.5–15% of sediment inputs during relatively dry conditions from April to the end of September and 5–70% through wetter conditions from October to the end of March, but our data do not show evidence of major sediment accumulation on the riverbed in the reach. A comparison of modelled sediment production on the road surface with observed yields from drainage channels suggests that (1) during low intensity rainfall, ditches and drainage channels may trap sediment from road run‐off, which is subsequently released during events of greater intensity, and/or (2) production models do not effectively describe processes, such as deposition or erosion of sediment in ditches, which control sediment transport and delivery. Our findings further emphasize the risk of unpaved roads in polluting river systems and highlight the continued need for careful road design and location away from sensitive aquatic environments. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   
123.
The study of water fluxes is important to better understand hydrological cycles in arid regions. Data-driven machine learning models have been recently applied to water flux simulation. Previous studies have built site-scale simulation models of water fluxes for individual sites separately, requiring a large amount of data from each site and significant computation time. For arid areas, there is no consensus as to the optimal model and variable selection method to simulate water fluxes. Using data from seven flux observation sites in the arid region of Northwest China, this study compared the performance of random forest (RF), support vector machine (SVM), back propagation neural network (BPNN), and multiple linear regression (MLR) models in simulating water fluxes. Additionally, the study investigated inter-annual and seasonal variation in water fluxes and the dominant drivers of this variation at different sites. A universal simulation model for water flux was built using the RF approach and key variables as determined by MLR, incorporating data from all sites. Model performance of the SVM algorithm (R2 = 0.25–0.90) was slightly worse than that of the RF algorithm (R2 = 0.41–0.91); the BPNN algorithm performed poorly in most cases (R2 = 0.15–0.88). Similarly, the MLR results were limited and unreliable (R2 = 0.00–0.66). Using the universal RF model, annual water fluxes were found to be much higher than the precipitation received at each site, and natural oases showed higher fluxes than desert ecosystems. Water fluxes were highest during the growing season (May–September) and lowest during the non-growing season (October–April). Furthermore, the dominant drivers of water flux variation were various among different sites, but the normalized difference vegetation index (NDVI), soil moisture and soil temperature were important at most sites. This study provides useful insights for simulating water fluxes in desert and oasis ecosystems, understanding patterns of variation and the underlying mechanisms. Besides, these results can make a contribution as the decision-making basis to the water management in desert and oasis ecosystems.  相似文献   
124.
在对极化干涉SAR森林树高反演的DEM差值算法、相干相位-幅度综合反演算法进行分析的基础上,对基于极化干涉相干优化方法的改进算法进行了探讨。利用黑龙江大兴安岭地区的一对ALOS全极化干涉SAR数据进行实验,并对比分析各算法的反演结果。结果表明,在使用改进的算法进行森林树高反演时可以获取精度较高的反演结果,并且在一定程度上提高了森林树高反演的稳定性,为森林树高反演工作的业务化运行提供一定的依据。  相似文献   
125.
随机蕨算法由于其简单高效,实时性好的特点,在计算机视觉领域得到了广泛的应用。但是其在构造二值特征过程中采用的基于像素点灰度值比较的方法对图像变形的适应性较差。本文基于方向梯度直方图对光照变化,图像变形鲁棒性较好的特点,利用统计方向梯度直方图取代像素灰度值进行比较,以此构造特征点二值特征。基于改进的随机蕨算法,本文设计了一种将增强现实技术(AR)应用于GIS的框架模型。实验结果表明,经过改进的随机蕨算法对目标识别的正确率得到了有效提升,且算法的实时性较好,适用于GIS的增强现实应用。  相似文献   
126.
Using the NASA Earth Exchange platform, the North American Forest Dynamics (NAFD) project mapped forest history wall-to-wall, annually for the contiguous US (1986–2010) using the Vegetation Change Tracker algorithm. As with any effort to identify real changes in remotely sensed time-series, data gaps, shifts in seasonality, misregistration, inconsistent radiometry and cloud contamination can be sources of error. We discuss the NAFD image selection and processing stream (NISPS) that was designed to minimize these sources of error. The NISPS image quality assessments highlighted issues with the Landsat archive and metadata including inadequate georegistration, unreliability of the pre-2009 L5 cloud cover assessments algorithm, missing growing-season imagery and paucity of clear views. Assessment maps of Landsat 5–7 image quantities and qualities are presented that offer novel perspectives on the growing-season archive considered for this study. Over 150,000+ Landsat images were considered for the NAFD project. Optimally, one high quality cloud-free image in each year or a total of 12,152 images would be used. However, to accommodate data gaps and cloud/shadow contamination 23,338 images were needed. In 220 specific path-row image years no acceptable images were found resulting in data gaps in the annual national map products.  相似文献   
127.
Fire disturbance in many tropical forests, including peat swamps, has become more frequent and extensive in recent decades. These fires compromise a variety of ecosystem services, among which mitigating global climate change through carbon storage is particularly important for peat swamps. Indonesia holds the largest amount of tropical peat carbon globally, and mean annual CO2 emissions from decomposition of deforested and drained peatlands and associated fires in Southeast Asia have been estimated at ∼2000 Mt y-1. A key component to understanding and therefore managing fire in the region is identifying the land use/land cover classes associated with fire ignitions. We assess the oft-asserted claim that escaped fires from oil palm concessions and smallholder farms near settlements are the primary sources of fire in a peat-swamp forest area in Central Kalimantan, Indonesia, equivalent to around a third of Kalimantan's total peat area. We use the MODIS Active Fire product from 2000 to 2010 to evaluate the fire origin and spread on the land use/land cover classes of legal, industrial oil palm concessions (the only type of legal concession in the study area), non-forest, and forest, as well as in relation to settlement proximity. We find that most fires (68–71%) originate in non-forest, compared to oil palm concessions (17%–19%), and relatively few (6–9%) are within 5 km of settlements. Moreover, most fires started within oil palm concessions and in close proximity to settlements stay within those boundaries (90% and 88%, respectively), and fires that do escape constitute only a small proportion of all fires on the landscape (2% and 1%, respectively). Similarly, a small proportion of fire detections in forest originate from oil palm concessions (2%) and within close proximity to settlements (2%). However, fire ignition density in oil palm (0.055 ignitions km−2) is comparable to that in non-forest (0.060 km-2 ignitions km-2), which is approximately ten times that in forest (0.006 ignitions km−2). Ignition density within 5 km of settlements is the highest at 0.125 ignitions km−2. Furthermore, increased anthropogenic activity in close proximity to oil palm concessions and settlements produces a detectable pattern of fire activity. The number of ignitions decreases exponentially with distance from concessions; the number of ignitions initially increases with distance from settlements, and, around from 7.2 km, then decreases with distance from settlements. These results refute the claim that most fires originate in oil palm concessions, and that fires escaping from oil palm concessions and settlements constitute a major proportion of fires in this study region. However, there is a potential for these land use types to contribute substantially to the fire landscape if their area expands. Effective fire management in this area should therefore target not just oil palm concessions, but also non-forested, degraded areas where ignitions and fires escaping into forest are most likely to occur.  相似文献   
128.
高建筑对周围建筑雷击保护距离的模拟   总被引:1,自引:1,他引:0       下载免费PDF全文
在已有先导连接参数化方案的基础上,选取近地面层为研究区域,保持方案中其他基本参量不变,通过改变闪电的空间形态,在同一建筑分布的背景下进行多次闪电模拟。研究多个建筑之间的屏蔽作用以及建筑雷击保护距离与建筑相关特征参数之间的关系,结果表明:高建筑对矮建筑具有屏蔽作用,并存在一个临界保护距离,当高、矮建筑高度分别为190 m和165 m,宽度均为20 m时,建筑之间的距离在12 m以内,矮建筑受高建筑完全保护不遭受雷击;建筑之间的距离超过12 m,矮建筑遭雷击次数明显增多。  相似文献   
129.
从几何角度对随机变量显著相关可传递性质进行了分析,得出了样本容量为n(n≥3)随机变量显著相关可传递性质的概率的几何表达式。用Monte-Carlo方法验证了几何分析的合理性,并对此问题展开了一定的讨论。  相似文献   
130.
王建强  张飞 《测绘科学》2016,41(9):20-24
针对在七参数坐标转换过程中,控制点本身含有的各种误差会对坐标转换的结果产生影响的问题,该文探讨了随机误差对七参数转换模型的影响:以七参数坐标转换模型为研究对象,模拟不同尺度范围的空间直角坐标,给定七参数数值求解另一组空间直角坐标,然后加入不同幅度的随机误差,利用最小二乘准则求解参数,从数值角度分析随机误差对七参数数值以及坐标转换结果的影响。实验结果显示,大范围的七参数模型解算的稳定性优于小范围的模型解算,以及X、Y、Z方向某一方向上的误差对另两个方向的解算结果影响较小。  相似文献   
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