Heavy metal pollution in sediments of a typical mariculture zone in South China

The heavy metal inventory and the ecological risk of the estuarine sediments in Hailing Bay, an important maricultural zone along the southern coast of China, were investigated. Results show that the surface sediments were mainly polluted by As (2.17-20.34 mg/kg), Ni (1.37-42.50mg/kg), Cu (1.21-58.84 mg/kg) and Zn (11.69-219.22 mg/kg). Furthermore, the aquafarming zone was significantly more polluted than the non-aquafarming zone, and cluster analysis suggested additional sources of heavy metal input in the aquafarming zone. As, Cr, Cu, Ni, Pb and Zn were mainly present in the non-bioavailable residual form in the surface sediments, whereas Cd was predominantly in the highly mobile acid soluble and reducible fractions. The ecological risk of the polluted sediments stemmed mainly from Cd, and from As, Cu and Pb to less degrees. The highest potential risks occurred near the aquaculture base, indicating the need to control heavy metal inputs from aquafarming activities.     

Soil bentonite wall protects foundation from thrust faulting: analyses and experiment

When seismic thrust faults emerge on the ground surface,they are particularly damaging to buildings,bridges and lifelines that lie on the rupture path.To protect a structure founded on a rigid raft,a thick diaphragm-type soil bentonite wall(SBW) is installed in front of and near the foundation,at sufficient depth to intercept the propagating fault rupture.Extensive numerical analyses,verified against reduced–scale(1 g) split box physical model tests,reveal that such a wall,thanks to its high deformability and low shear resistance,"absorbs" the compressive thrust of the fault and forces the rupture to deviate upwards along its length.As a consequence,the foundation is left essentially intact.The effectiveness of SBW is demonstrated to depend on the exact location of the emerging fault and the magnitude of the fault offset.When the latter is large,the unprotected foundation experiences intolerable rigid-body rotation even if the foundation structural distress is not substantial.     

圣安德烈斯断层的强度

在过去25年里,对沿加利福尼亚州的圣安德烈斯断层系的运动速率和长期地震记录的认识已显著提高了。这些认识使得对地震发生概率,尤其是30年周期概率的长期估计成为可能(Working Group on California Earthquake Probabilities,1999)。但是,我们对断裂产生的物理过程的了解仍然非常不足——关于短期预报的可行性问题、一个断层产生地震是否会增加另一断层     

Massive sedimentation of fine sediment with organic matter and enhanced benthic-pelagic coupling by an artificial dyke in semi-enclosed Chonsu Bay, Korea

To assess the impact of an artificial dyke in Chonsu Bay (CBD) on the organic carbon (C(org)) cycle, we measured excess (210)Pb activities, C(org) and nitrogen content in sediment cores. The C(org) oxidation rates (C(ox)) on the surface sediment and benthic nutrient fluxes were also quantified with an in situ benthic chamber. The higher excess (210)Pb inventory, C(org) and nitrogen in cores near the CBD indicated lateral transport and local, massive deposition of particulate matter due to tidal circulation altered by artificial dyke construction. The C(ox) in sediment near the CBD was about twice as high as that out of the bay, suggesting the importance of benthic remineralization of organic matter. The benthic fluxes of dissolved inorganic nitrogen and phosphate were four to six times higher than those outside the bay, corresponding to 141% and 131% respectively, of the requirements for primary production.     

基于GIS的陕西省人口空间分布模式

借助空间自相关分析方法分析了陕西省人口的空间分布模式和空间关联关系。结果表明,陕西省人口分布呈现显著的空间集聚现象,在整体上具有较强的正相关性。在西安市附近存在几个非常明显的"高-高"集聚;同时,延安市和安康市分别出现"低-低"集聚。陕西省人口重心从2002年的礼泉县移动至2009年的泾阳县,向东北移动约3.3 km。     

Approaches for delineating landslide hazard areas using different training sites in an advanced artificial neural network model

The current paper presents landslide hazard analysis around the Cameron area, Malaysia, using advanced artificial neural networks with the help of Geographic Information System (GIS) and remote sensing techniques. Landslide locations were determined in the study area by interpretation of aerial photographs and from field investigations. Topographical and geological data as well as satellite images were collected, processed, and constructed into a spatial database using GIS and image processing. Ten factors were selected for landslide hazard including: 1) factors related to topography as slope, aspect, and curvature; 2) factors related to geology as lithology and distance from lineament; 3) factors related to drainage as distance from drainage; and 4) factors extracted from TM satellite images as land cover and the vegetation index value. An advanced artificial neural network model has been used to analyze these factors in order to establish the landslide hazard map. The back-propagation training method has been used for the selection of the five different random training sites in order to calculate the factor’s weight and then the landslide hazard indices were computed for each of the five hazard maps. Finally, the landslide hazard maps (five cases) were prepared using GIS tools. Results of the landslides hazard maps have been verified using landslide test locations that were not used during the training phase of the neural network. Our findings of verification results show an accuracy of 69%, 75%, 70%, 83% and 86% for training sites 1, 2, 3, 4 and 5 respectively. GIS data was used to efficiently analyze the large volume of data, and the artificial neural network proved to be an effective tool for landslide hazard analysis. The verification results showed sufficient agreement between the presumptive hazard map and the existing data on landslide areas.     

多光谱图象数据的无损压缩

使用标准无损图象压缩技术，能满足空间相关的需要．当处理多光谱函象数据时，在光谱相关方面也取得了少许进步．在本文中，我们提供一些新的无损压缩技术。它以简单和精巧的方式获取的光谱相关同空间相关同样地好．这些方法是基于构造树概念，它将图象划分为没有因果关系的构造模型．我们提供出自适应还原技术和自适应压缩技术。然后，又给出了相似于自适应还原技术的有效的计算方法．模拟成果说明，对于高分辨率多光谱图象，使用多光谱相关以及空间相关能有效地节省存储空间。还有，为此所付出的代价是很小的。