利用人工神经网络方法对牙形石鉴定中若干“模糊特征”的数字化研究

牙形石是一类在地层学研究中具有重要意义的古生物化石。但由于牙形石鉴定中存在诸多重要、却难以定量分析的“模糊特征”,使得牙形石的鉴定和分类工作长期依赖于古生物工作者的经验。利用数学中的非线性方程将这些“模糊特征”进行数学描述,并利用人工神经网络中的反向传播算法设计出一套多隐含层的前馈网络分类器,对这些“模糊特征”进行分类尝试,取得了良好的效果,为牙形石的进一步数值化研究奠定了基础。     

基于小波变换和中值滤波的InSAR干涉图像滤波方法

介绍小波分析的基本理论和利用小波分析对信号进行消除噪声的基本方法,以及In-SAR干涉相位图像中噪声的特点.针对目前普遍采用的均值滤波和中值滤波等方法对In-SAR干涉相位图像中噪声进行滤波的局限性,提出一种基于小波分析和中值滤波相结合的InSAR干涉相位图滤波算法以改善滤波效果.实验证明该算法的有效性.     

基于陆路交通网的空间通达性分析——以兰州-西宁城市区域为例

以兰州-西宁城市区域交通路网为例,基于空间句法模型、日常可达性模型和等时圈通过特征点算法,试图运用GIS技术将节点、轴线和域面结合起来对通达性进行全面阐述,多视角综合测度区域路网通达性的空间格局。研究结果表明:1.区域路网体系较为完善,路网线段集聚相对明显;线段式空间伸展格局呈"点-轴"状,轴线式空间伸展格局呈"干-枝"状,初步形成核心、过渡、外围三大等级圈层以及"X"字型路网骨架,区域交通运输与城镇发展水平表现出较强的共轭协同发展关系。2.等时圈沿国道、省道、县道扩散表现连续,沿封闭铁路、高速公路扩散出现跳跃,其等时圈空间特征多呈现"枝-叶"状。城镇日常可达性在较大程度上取决于区域中心性、周边路网发达程度和城镇密集程度,区域路网单中心极化现象比较明显,兰州市对整个区域路网的控制作用较为突出。3.区域通达度空间分布各异,核心板块破碎而外围板块连片。区域通达性差异极其显著,出现极高值区和极低值区;兰州与西宁通达度中高值区出现断裂,区域南部通达度极低值区连片成带。因此,应当构建兰州地区绕城高速和环状路网,实现路网交通的适度分流;加快兰州-西宁高等级快速交通建设,推进兰州-西宁区域一体化进程;建设兰成铁路和兰州至云南磨憨口岸高速通道,培育临夏为南部区域性中心城市。     

Finding shortest paths on real road networks: the case for A*

The problem of identifying the shortest path along a road network is a fundamental problem in network analysis, ranging from route guidance in a navigation system to solving spatial allocation problems. Since this type of problem is solved so frequently, it is important to craft an approach that is as efficient as possible. Based upon past research, it is generally accepted that several efficient implementations of the Dijkstra algorithm are the fastest at optimally solving the ‘one‐to‐one’ shortest path problem (Cherkassky et al. 1996 Cherkassky, B. V., Goldberg, A. V. and Radzik, T. 1996. Shortest paths algorithms: theory and experimental evaluation.. Mathematical Programming: Series A and B, 73: 129–174. [Crossref], [Web of Science ®] , [Google Scholar]). We show that the most efficient state‐of‐the‐art implementations of Dijkstra can be improved by taking advantage of network properties associated with GIS‐sourced data. The results of this paper, derived from tests of different algorithmic approaches on real road networks, will be extremely valuable for application developers and researchers in the GIS community.     

An adaptive approach to selecting a flow‐partition exponent for a multiple‐flow‐direction algorithm

Most multiple‐flow‐direction algorithms (MFDs) use a flow‐partition coefficient (exponent) to determine the fractions draining to all downslope neighbours. The commonly used MFD often employs a fixed exponent over an entire watershed. The fixed coefficient strategy cannot effectively model the impact of local terrain conditions on the dispersion of local flow. This paper addresses this problem based on the idea that dispersion of local flow varies over space due to the spatial variation of local terrain conditions. Thus, the flow‐partition exponent of an MFD should also vary over space. We present an adaptive approach for determining the flow‐partition exponent based on local topographic attribute which controls local flow partitioning. In our approach, the influence of local terrain on flow partition is modelled by a flow‐partition function which is based on local maximum downslope gradient (we refer to this approach as MFD based on maximum downslope gradient, MFD‐md for short). With this new approach, a steep terrain which induces a convergent flow condition can be modelled using a large value for the flow‐partition exponent. Similarly, a gentle terrain can be modelled using a small value for the flow‐partition exponent. MFD‐md is quantitatively evaluated using four types of mathematical surfaces and their theoretical ‘true’ value of Specific Catchment Area (SCA). The Root Mean Square Error (RMSE) shows that the error of SCA computed by MFD‐md is lower than that of SCA computed by the widely used SFD and MFD algorithms. Application of the new approach using a real DEM of a watershed in Northeast China shows that the flow accumulation computed by MFD‐md is better adapted to terrain conditions based on visual judgement.     

Forest Fire Alert System: a Geo Web GIS prioritization model considering land susceptibility and hotspots – a case study in the Carajás National Forest,Brazilian Amazon

To increase the monitoring potential of forest fires, an alert classification methodology using satellite-mapped hotspots has been established to help forest managers in the prioritization of which hotspot to be verified in the field, thus potentially improving the distribution of fire-fighting resources. A computer application was developed based on web-distributed geographical information technology whose main function is to interact automatically generated satellite hotspots and risk areas indicated in fire-susceptibility maps and classify them into five alert levels. The location of the hotspots is available continuously every 4 h, and a susceptibility map is produced daily through map algebra algorithm, which uses static (topography, vegetation and land use) and dynamic (weather) variables. Every process runs through automated geoprocessing routines. The methodology was tested during the dry period of 2007 in the Carajás National Forest, in the Brazilian Amazon, within an area of 400,000 ha. It is a critical area constantly threatened by fires caused by invasions and deforestation owing to intense agribusiness advances and mining activities in its surroundings. This situation results in observations of many hotspots inside the study area for the same day and almost the same time period, in places of extreme opposites, demanding complex rapid analysis and hindering the decision of the displacement of fire-fighting teams. Further, a major mining company operates within the National Forest area, maintaining actions of protection as part of its environmental mining license. Results are presented under three aspects: (i) the credibility of the daily susceptibility map (algorithm), which showed strong correlation between areas of greatest risks and the confirmed forest fires; (ii) the reliability of hotspots (alert levels), confirming 71% of fires; (iii) accuracy in the decision of which hotspot to be checked, which revealed the same number of verifications at different alert levels, 82% confirmed alert 5 hotspots (maximum) and only 50% from alert 1 (minimum), resulting in faster fire-fighting actions, minimizing burned areas and, in some cases, allowing fire control before its spreading. Therefore, the methodology demonstrated that GIS routines are able to determine the relationship between a reality-based, interpreted susceptibility map of the area and satellite-generated hotspots, highlighting the ones of highest hazard level through the alert classification, becoming an important tool to help decisions from the fire-control center, especially for high-risk regions. The methodology may be extrapolated to other forested areas.     

Sediment fingerprinting in fluvial systems： review of tracers,sediment sources and mixing models

Suspended sediments in fluvial systems originate from a myriad of diffuse and point sources, with the relative contribution from each source varying over time and space. The process of sediment fingerprinting focuses on developing methods that enable discrete sediment sources to be identified from a composite sample of suspended material. This review identifies existing methodological steps for sediment fingerprinting including fluvial and source sampling, and critically compares biogeochemical and physical tracers used in fingerprinting studies. Implications of applying different mixing models to the same source data are explored using data from 41 catchments across Europe, Africa, Australia, Asia, and North and South America. The application of seven commonly used mixing models to two case studies from the US （North Fork Broad River watershed） and France （Bldone watershed） with local and global （genetic algorithm） optimization methods identified all outputs remained in the acceptable range of error defined by the original authors. We propose future sediment fingerprinting studies use models that combine the best explanatory parameters provided by the modified Collins （using correction factors） and Hughes （relying on iterations involving all data, and not only their mean values） models with optimization using genetic algorithms to best predict the relative contribution of sediment sources to fluvial systems.     

中国东南屯溪-温州宽角地震资料去广角效应成像

由于长排列广角地震采集中必定存在超临界角的广角反射信息,广角反射信息相对临界角内反射信息存在随偏移距变化的时移现象.本文研究了去广角效应下的走时反演成像,并将其应用到东南屯溪—温州的宽角地震资料.通过拾取中国东南屯溪—温州剖面宽角实际地震资料中P波垂直分量拾取到的反射P波走时,继而使用遗传反演方法进行处理,得到了该区丰乐、新安江、松阳、青田以及洞头五炮去广角效应与未考虑广角效应情况下的一维速度深度曲线,并对比了去广角效应前后的地壳结构界面形态.结果表明,广角效应去除前后影响主要体现在壳内层速度差异,地壳浅层界面深度的广角效应明显强于深层界面.     

THE INFLUENCE OF SLOPE AND RAIN INTENSITY ON RUNOFF AND INFILTRATION / L'influence de l'inclinaison de terrain et de l'intensité de pluie sur l'écoulement et l'infiltration

Abstract

The design and construction of a special-purpose laboratory catchment and rainfall simulator is described. The equipment consists of a soil catchment area that can be inclined at various angles. Additional instrumentation then measures the flow of water across the surface of, and through, the soil bed. Precipitation is provided by a unit that simulates rainfall at particular rates with uniform distribution.

The equipment was used to examine infiltration, runoff and other hydrological properties of a number of soils under different rainfall intensities and with different catchment slopes. Correlations were obtained for these variables.     

甘东南流动台阵微震监测结果

利用高密度宽频带流动台阵资料,应用网格搜索地震定位方法对甘东南2009年11月-2011年11月期间的微震进行了重新定位.在研究区内有3个以上台站记录到的微震共3 014个,比常规台网记录多1 693个.重新定位结果显示:在各断裂带附近地震分布更加密集,沿断裂呈带状或簇集状分布;震源深度分布优势范围为5～20 km,其平均深度为11 km;地震深度分布与断裂的关系密切,地震条带与断裂构造可以较好的相对应.