多种再分析地表温度资料在中国区域的适用性分析

利用1979-2010年中国805个站点的逐日地表温度观测资料与ERA-Interim、ERA-Interim/Land、JRA-55、NCEP/NCAR和NCEP/DOE五种再分析地表温度资料, 对五种再分析地表温度资料在中国区域的适用性进行了比较与分析. 结果表明: 从空间分布特征来看, JRA-55资料与观测资料最为接近; 五种再分析地表温度资料在东部地区的适用性好于西部地区, 且均不能很好地模拟出青藏高原地区和西北西部地区的地表温度分布. 从地表温度的长期变化来看, 五种再分析地表温度资料虽然可以描述地表温度变化趋势, 但均存在低估现象, 且低估现象随着地表温度的增加变得更加严重. 在地表温度人工观测和自动观测交接的时间段, 可以使用再分析资料作为地表温度均一化的参考序列.     

Bayesian prediction of potential depressions in the Erlian Basin based on integrated geophysical parameters

In this study, we analyzed the geological, gravity, magnetic, and electrical characteristics of depressions in the Erlian Basin. Based on the results of these a...     

耕地保护与土地资源可持续利用研究--以广东省徐闻县为例

从可持续发展的角度,分析了广东省徐闻县土地资源利用的现状和耕地锐减的原因,并有针对性的提出了通过建立土地资源可持续利用机制和采用行政、经济、法律及技术等措施来保护耕地,实现土地资源的可持续利用.     

Distribution and phenogenetic diversity of Synechococcus in the Bohai Sea,China

Journal of Oceanology and Limnology - Synechococcus is one of the most abundant picocyanobacteria in marine ecosystem, and the absence of Prochlorococcus would make it indispensable as a primary...     

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Genetic diversity of wild barley (Hordeum vulgare ssp. spontaneum) and its utilization for barley improvement

Wild barley (Hordeum vulgare spp. spontaneum) is the undisputed progenitor of cultivated barley and offers considerable potential as a genetic resource for barley improvement. Naturally occurring populations are distributed primarily across the Fertile Crescent, but secondary areas of diversity are also found in central Asia and Tibet. The pattern of its genetic diversity is non-random, and is structured on a global, regional and local scale. On a global scale, diversity follows ecogeography, while on a regional and local scale, it is more strongly determined by ecology. Populations growing in areas where the climate is unreliable and/or the soil is heterogeneous tend to retain the most diversity. A large number of accessions are currently conserved ex situ, but a high proportion of these have originated from the Fertile Crescent. Given the likelihood of future climate change, conserving germplasm both in situ and ex situ in the various regions where the species’ currently existing is a research priority. The value of H. vulgare spp. spontaneum for the improvement of cultivated barley lies largely in its potential contribution to the levels of attainable pathogen resistance and abiotic stress tolerance.     

全球陆地年降水量与ENSO关系的初步研究

用全球陆地月降水资料（PREC／L）,研究了1948－2000年期间的ENSO事件与全球陆地年降水量的关系,对全盛分析的结果进行了蒙特卡洛模拟经验。结果表明,暖事件年全球陆地年降水量大范围地明显减小,显著的地区是：赤道西太平洋区,中国的华北,赤道中美洲区,孟加拉湾北部及尼泊尔,东澳大利亚区,印度西部及巴基斯坦南部,勒拿河以东地区,西欧及南极的威尔克斯等区域。在暖事件年,陆地年降水量增加地区不多,主要是南美的智利和阿根廷,东非索马里,肯尼亚和坦桑亚,中东的土耳其,伊拉克及伊朗,北非的利比亚和阿尔及利亚,西南非的纳米比亚及非洲南部的博茨瓦纳和津巴布韦。统计检验表明,暖事件年全球陆地年降水量减少的面积比降水量增加的面积要大,而且更为显著,将本文结果与早期的研究结果进行了比较,研究还指出,ENSO的年代际变化对上述地区降水的年代际变化影响不明显。但是80年代以后的暖事件对东澳大利亚干旱,中国的华北的干旱的影响比80年代前的影响更大。     

ADAPT数字遥测地震台网中传递函数的辨识

Adapt系统可以利用脉冲标定波形得到系统的传递函数,它将复杂的传递函数计算过程简化了,用户可以将传递函数的测定作为一种日常工作来做。     

Semantic segmentation of high spatial resolution images with deep neural networks

Availability of reliable delineation of urban lands is fundamental to applications such as infrastructure management and urban planning. An accurate semantic segmentation approach can assign each pixel of remotely sensed imagery a reliable ground object class. In this paper, we propose an end-to-end deep learning architecture to perform the pixel-level understanding of high spatial resolution remote sensing images. Both local and global contextual information are considered. The local contexts are learned by the deep residual net, and the multi-scale global contexts are extracted by a pyramid pooling module. These contextual features are concatenated to predict labels for each pixel. In addition, multiple additional losses are proposed to enhance our deep learning network to optimize multi-level features from different resolution images simultaneously. Two public datasets, including Vaihingen and Potsdam datasets, are used to assess the performance of the proposed deep neural network. Comparison with the results from the published state-of-the-art algorithms demonstrates the effectiveness of our approach.