A block-based selection method for road network generalization

Abstract

When road symbols are shown in a size proportionate to the reduced scale, several problems of legibility may arise concerning the urban blocks. By the method proposed in this paper, in order to overcome these problems, urban block areas are enlarged through amalgamation and the intervening roads in the amalgams are eliminated. This method includes two new approaches for computation of threshold used in determination of important roads based on the connectivity measure, and for definition of minimum block space and area requirements based on graphic limits. A block life cycle was designed for amalgamation of blocks. For the amalgamation process, a new algorithm was developed. The experimental testing indicates that important roads and the roads surrounding the urban area have been preserved. A simpler and more legible road network has been acquired. This method can be described as a more holistic approach as the buildings are taken into account. The problems arising in the experimental testing indicate that the cartographic selection/elimination process is not sufficient by itself for road network generalization, which can be assumed as one of the integral parts of Digital Earth. As well as the selection/elimination, processes such as displacement and caricaturizing are also needed.     

Enrichment of topographic road database for the purpose of routing and navigation

With growing demand on multi-purpose or multi-modal navigation, the route calculation needs to traverse semantically enriched road networks for different transportation modes. Currently, operational route planning algorithms reveal rather limited performances or their potential for comprehensive applications are constrained by the unavailable or insufficient interoperation among the underlying geo-data that are separately maintained in different spatial databases. To overcome this limitation, a novel approach has been proposed to integrate the routing-relevant information from different data sources, which involves three processes: (1) automatic matching to identify the corresponding road objects between different datasets; (2) interaction to refine the automatic matching result; and (3) transferring the routing-relevant information from one data-set to another. In process (1), the Delimited Stroke Oriented algorithm is employed to achieve the automatic data matching between different datasets, which has revealed a high matching rate and certainty. However uncertain matching problems occur in areas where topological conditions are too complicated or inconsistent. The remaining unmatched or wrongly matched objects are treated in process (2), with the help of a series of interaction tools. On the basis of refined matching results after the interaction, process (3) is dedicated to automatic integration of the routing-relevant information from different data sources.     

A rule-based parameter aided with object-based classification approach for extraction of building and roads from WorldView-2 images

Roads and buildings constitute a significant proportion of urban areas. Considerable amount of research has been done on the road and building extraction from remotely sensed imagery. However, a few of them have been concentrating on using only spectral information. This study presents a comparison between three object-based models for urban features’ classification, specifically roads and buildings, from WorldView-2 satellite imagery. The three applied algorithms are support vector machines (SVMs), nearest neighbour (NN) and proposed rule-based system. The results indicated that the proposed rules in this study, despite the spectral complexity of land cover types, performed a satisfactory output with an overall accuracy of 92.92%. The advantages offered by the proposed rules were not provided by other two applied algorithms and it revealed the highest accuracy compared to SVM and NN. The overall accuracy for SVM was 76.76%, which is almost similar to the result achieved by NN (77.3%).     

高空西北气流下铜仁东部特大暴雨的预报分析及思考

利用贵州省预报业务常规、地面自动站加密观测资料、NCEP/FNL1°×1°再分析资料、业务数值预报模式,分析2020年6月29日铜仁市东部高空西北气流影响下的特大暴雨环境场特征、地面中小尺度场特征以及3家数值预报模式检验,初步分析产生此次特大暴雨的可能成因是在副高东南退、东北冷涡槽后高空西北气流维持、低层冷平流下传西输、地面辐合维持增强为涡旋、地面东路弱冷空气侵入、能量锋区斜压性增强;短临监测发现雷达回波有列车效应、低层辐合高层辐散的共轭配置、中层气旋式辐合;初步得出了西北气流影响下弱天气尺度环境场的铜仁市东部暴雨的预报着眼点。     

东莞市城市现状路网调查与建库

阐述了东莞市城市现状路网调查与建库项目的背景及项目内容,剖析了项目采用的技术路线和工作步骤,最后对项目成果的精度的分析结果表明,成果精度能够满足城乡规划的使用需要。     

超基性岩红土风化壳中镍的表生富集规律及矿化结构研究 ——以印尼苏拉威西岛Kolonodale矿区为例

文章选取印尼苏拉威西岛Kolonodale红土型镍矿区为研究区,对201个浅井剖面共采取3 161件风化壳样品,进行了w(Ni)值的测试,以揭示超基性岩红土风化壳中Ni的表生富集规律及矿化结构特征。研究结果表明,在平面上,矿区内风化壳的w(Ni)平均值的高低与地形地貌关系密切。斜坡带、坡脚堆积带的风化壳为含镍高值区,其w(Ni)值为0.8%~1.8%;山顶平台区、山脊的风化壳为含镍低值区,其w(Ni)值为0.7%~1.4%。在垂向上,风化产物的w(Ni)值的高低与取样深度及样品属性密切相关。w(Ni)值随着红土带→腐岩带→基岩带的变化出现低值(0.85%~1.55%)→高值(1.15%~4.75%)→低值(≤0.55%)的波动变化规律。矿层的产状(分布、深度、厚度)与风化壳产状之间表现出明显的正相关关系。矿区内的低品位矿层〔1.5%≤w(Ni)≤2.0%〕和高品位矿层〔w(Ni)≥2.0%〕单独或组合发育,产出"正常型双层矿化"、"倒置型双层矿化"、"低品位单层矿化"、"高品位单层矿化"和"叠层矿化"等5种矿化结构类型。综合分析认为,富镁及中等程度蛇纹石化的超基性岩母岩、热带雨林气候环境是矿区内发育富镍红土风化壳的首要条件。吸附、离子交换以及次生沉淀等3种成矿作用的共同发育,导致了红土风化壳中Ni表生矿化的连续性、矿石类型的多样性及特高品位矿石的形成。矿床中矿化结构类型的多样化是区域构造背景、地形地貌、构造发育、水文条件等诸多因素耦合作用的结果。文章指出,在今后的红土型镍矿床的找矿勘查过程中,需要综合考虑各类内、外生控矿因素对矿床发育的影响,总结矿区尺度的矿化结构规律,可有效地指导矿床勘查工作。     

枪马金矿金品位统计分布特征及其地质意义

地质变量的变化与地质体的特征密切相关,通过地质变量的研究可以揭示地质体某一特征的规律性。多次地质事件的数理统计特征表现为多个总体叠加的混合分布,因此通过研究混合分布和单一分布的特征,对矿床的矿化成因、矿化过程和矿化特征认识有指导意义。研究发现,枪马金矿的金品位主要由2个对数正态分布总体叠加而成,并对应于本区2次主要的成矿事件。对金的特征参数垂直空间上的研究表明,金矿化强度向深部逐渐增高,深部找矿远景很大。     

膨胀系数可调的Balloon Snake方法在道路轮廓提取中的应用

以条带检测的结果初始化道路轮廓,利用balloon snake方法提取道路轮廓.在初始道路轮廓存在缺失的情况下,balloon snake的膨胀作用可以找回丢失的道路片段,提高道路提取的完整性.基于图像梯度和轮廓曲率调节膨胀系数,降低道路提取效果对膨胀系数的敏感,并加快道路轮廓的扩张,减少迭代次数.通过多幅道路图像的试...     

GeoEye-1立体像对在公路勘测中的应用研究

高分辨率遥感影像获取公路沿线空间地理信息速度快、信息丰富,其立体像对可定位测图。对基于0.5 m分辨率GeoEye-1立体像对在公路勘测中的应用技术进行了研究,给出了利用GeoEye-1立体模型制作公路数字高程模型和大比例尺测图的流程,采用GPSRTK布设地面控制点,通过空三平差消除RPC模型系统误差,实验结果表明可提高GeoEye-1立体像对定位测量精度。对GeoEye-1立体像对在公路勘测设计中的产品类型和应用模式进行了探讨和展望。     

线实体候选匹配集的优化方法研究

地图数据合并是地理空间数据集成的基本途径,同名实体匹配是其中的重点与难点。本文根据线实体的形状将其分为简单线实体与复杂线实体,提出针对前者以线实体端点与中点为发生元生成的Voronoi图所得到的邻近对应关系为依据、针对后者以基于线实体缓冲区重叠度构造的相似性测度指标为依据优化候选匹配集的思路,并设计与实现了相关算法。实证研究表明,该算法能够适应不同比例尺与不同时相的城市道路网地图数据同名实体匹配。