综合物探在东罗（坑口）火电厂灰渣堆置场勘察中的应用

东罗火电厂灰渣堆置场的选址，以场地堆置灰渣后是否对客兰水库造成污染为前提。广西地质测井中心利用综合物探方法对场地的水文地质、工程地质和环境地质进行勘察评价。经工作，圈定了第四系土层和七条岩溶发育带，确定了一正断层位置，在四个钻孔中充电确定了地下水的流速和流向（主要为北西向和正北方向）。最后认为，场地堆置弃渣后，对位于南南东方向的客兰水库没有造成污染，为选址决策和施工设计提供了依据     

湘南晚泥盆世佘田桥期碳酸盐块状流沉积特征

湘南晚泥盆世佘田桥期表现为东西两侧高而中部低陷的古地理面貌。两侧为碳酸盐台地,中间为深水台盆。在台盆、台地之间斜坡地带和台盆边缘,堆积了类型繁多的碳酸盐块状流沉积物。它们由两类在成因和分布上有密切联系的沉积体系组成,一类为重力崩落或滑移体系,包括岩崩、滑动和滑塌沉积,另一类为重力流体系,包括碎屑流、浊流和颗粒流沉积。在层序上它们虽作有规律的组合层序,但并不是完整的类型,而出现较大的变异性。已发现的组合层序有①滑塌沉积—碎屑流沉积,②碎屑流—高密度浊流—低密度浊流沉积,③变密度颗粒流—浊流沉积。它们沿近南北向的台盆的两侧边缘呈条带状分布,东侧位于临武香花岭至桂阳莲塘一带,重力流厚度可达150m左右,西侧位于道县虎岩坝至双牌县城一带,重力流厚只30—50m,反映了台盆边缘两侧构造活动强度不一致,东侧强,西侧弱。     

河南灵宝小秦岭金矿带矿化特征及富集规律研究

本文简述了河南灵宝小秦岭金矿带矿化特征，提出了全区金矿化富集的层位性、分带性、主从性、方向性及似等距性，同时探讨了工业矿脉内金矿化的若干局部富集规律。     

RecNet: a deep neural network for personalized POI recommendation in location-based social networks

How to exploit various features of users and points of interest (POIs) for accurate POI recommendation is important in location-based social networks (LBSNs). In this paper, a novel POI recommendation framework, named RecNet, is proposed, which is developed based on a deep neural network (DNN) to incorporate various features in LBSNs and learn their joint influence on user behavior. More specifically, co-visiting, geographical and categorical influences in LBSNs are exploited to alleviate the data sparsity issue in POI recommendation and are converted to feature vector representations of POIs and users via feature embedding. Moreover, the embedded POIs and users are fed into a DNN pairwise to adaptively learn high-order interactions between features. Our method is evaluated on two publicly available LBSNs datasets and experimental results show that RecNet outperforms state-of-the-art algorithms for POI recommendation.     

一种由粗到精的光学与SAR遥感图像配准算法

由于光学遥感图像和SAR图像具有明显的非线性强度差异,且SAR图像存在斑点噪声,使得其配准存在较大难度。为此,本文结合基于特征和基于区域图像配准方法的优点,并组合为混合模型,提出一种由粗到精的自动配准算法。以光学遥感图像和SAR图像分别为参考图像和待配准图像,先以基于特征点的SAR-SIFT完成粗配准,再以基于区域的ROEWA-HOG完成精配准。① 采用SAR-SIFT算法进行特征点检测和特征匹配来计算图像的仿射变换模型,以消除参考图像和待配准图像之间明显的旋转、尺度和平移差异,至此完成图像粗配准;② 在此基础上利用分块Harris角点检测在参考图像上获得特征点,并根据特征点确定待配准图像上的同名点搜索区域;③ 计算图像的ROEWA梯度,构造以特征点为中心的模板区域内的HOG特征向量,以SSD作为相似性测度搜索待配准图像上的同名点,完成高精度的图像配准;④ 进行图像配准实验,对配准结果进行目视检查和精度评估。经过多组光学与SAR图像配准实验,验证本文算法能够结合基于特征和基于区域的图像配准方法的优点,较好地抵抗光学与SAR图像之间的非线性强度、旋转、尺度、平移差异和SAR图像的噪声影响,并逐步提高配准精度,最终配准精度达到1个像素左右,实现了光学与SAR图像的高精度自动配准,能够满足光学与SAR图像后续综合应用。     

基于空间相似性的面实体匹配算法研究

同一地物在不同来源的地图上通常存在着差异,其识别或匹配对于不同数据源的地图编制来说很关键。面状地物要素在很多地图表示中都占有很大的比例。基于人眼综合已有信息来识别同名实体的思想,本文提出了基于空间相似性的面实体匹配算法。该算法将面实体作为一个整体看待,采用加权平均法来综合面实体的位置、形状、大小等特征的相似度,进而根据获得的总相似度大小确定匹配实体。算法在确定位置相似度时选择形状中心点对面实体进行惟一标识;采用形状描述函数来计算形状相似度,不容易受各种干扰而影响精度,避免了形状信息的丢失;面实体的大小通过其覆盖面积来度量。实验结果表明该方法具有良好的稳定性和可靠性。     

Sinkhole hazard assessment in Minnesota using a decision tree model

An understanding of what influences sinkhole formation and the ability to accurately predict sinkhole hazards is critical to environmental management efforts in the karst lands of southeastern Minnesota. Based on the distribution of distances to the nearest sinkhole, sinkhole density, bedrock geology and depth to bedrock in southeastern Minnesota and northwestern Iowa, a decision tree model has been developed to construct maps of sinkhole probability in Minnesota. The decision tree model was converted as cartographic models and implemented in ArcGIS to create a preliminary sinkhole probability map in Goodhue, Wabasha, Olmsted, Fillmore, and Mower Counties. This model quantifies bedrock geology, depth to bedrock, sinkhole density, and neighborhood effects in southeastern Minnesota but excludes potential controlling factors such as structural control, topographic settings, human activities and land-use. The sinkhole probability map needs to be verified and updated as more sinkholes are mapped and more information about sinkhole formation is obtained.     

Spatial operations in a GIS-based karst feature database

This paper presents the spatial implementation of the karst feature database (KFD) of Minnesota in a GIS environment. ESRI’s ArcInfo and ArcView GIS packages were used to analyze and manipulate the spatial operations of the KFD of Minnesota. Spatial operations were classified into three data manipulation categories: single layer operation, multiple layer operation, and other spatial transformation in the KFD. Most of the spatial operations discussed in this paper can be conducted using ArcInfo, ArcView, and ArcGIS. A set of strategies and rules were proposed and used to build the spatial operational module in the KFD to make the spatial operations more efficient and topographically correct.     

顾及纹理特征的航空影像自适应密集匹配方法

半全局匹配实质是在视差连续性假设下的离散优化方法。为克服视差断裂带影响,依赖一组参数控制视差不一致性。若参数过小,在平面内难以保证视差连续性,产生明显噪声,导致凹凸不平现象;若参数过大,将致使物体表面过于平滑,难以保留视差断裂等重要特征。为克服上述问题,本文提出了一种顾及纹理特征的自适应密集匹配方法:首先,检测影像纹理特征并定量表达纹理丰富性程度;其次,依据纹理丰富程度与视差差异存在正相关的规则知识,实现匹配参数依据纹理信息的自适应选择;最后,采用上述参数进行自适应的半全局匹配。通过ISPRS基准数据集和国产SWDC-5获取的倾斜影像进行试验分析证明,本文方法能够有效减少低纹理区域匹配噪声,同时更有效保留边缘特征。