秩亏自由网平差的GNSS控制网已知点兼容性检验

针对现有方法普遍存在的计算过程繁琐、计算量较大等问题,该文提出了一种基于秩亏自由网平差的全球导航卫星系统(GNSS)控制网已知点兼容性检验方法。该方法利用秩亏自由网平差中重心基准的唯一不变特性,通过对已知点平差坐标与已知坐标较差(即坐标残差)的比较分析,检查和判断各已知点坐标的精度及其兼容性,筛选出符合相应等级精度要求的起算点,简化了繁琐的计算过程,减小了计算工作量,避免对全部已知点不同组合的多次重复计算,提高了检验的效率和有效性。该方法简便易行,可在工程实践中推广应用。     

Automatic analysis of positional plausibility for points of interest in OpenStreetMap using coexistence patterns

In the past decade, Volunteered Geographic Information (VGI) has emerged as a new source of geographic information, making it a cheap and universal competitor to existing authoritative data sources. The growing popularity of VGI platforms, such as OpenStreetMap (OSM), would trigger malicious activities such as vandalism or spam. Similarly, wrong entries by unexperienced contributors adds to the complexities and directly impact the reliability of such databases. While there are some existing methods and tools for monitoring OSM data quality, there is still a lack of advanced mechanisms for automatic validation. This paper presents a new recommender tool which evaluates the positional plausibility of incoming POI registrations in OSM by generating near real-time validation scores. Similar to machine learning techniques, the tool discovers, stores and reapplies binary distance-based coexistence patterns between one specific POI and its surrounding objects. To clarify the idea, basic concepts about analysing coexistence patterns including design methodology and algorithms are covered in this context. Furthermore, the results of two case studies are presented to demonstrate the analytical power and reliability of the proposed technique. The encouraging results of this new recommendation tool elevates the need for developing reliable quality assurance systems in OSM and other VGI projects.     

机载激光雷达对地定位精度探讨

文章讨论了机载激光雷达系统的组成、航飞计划设计、数据采集及其预处理,最后通过相关软件结合航摄地标点和航飞影像数据来评定整个系统的对地定位精度。     

Addressing Integration Challenges of Interdisciplinary Research in Social-Ecological Systems

Abstract

Conducting research on coupled social-ecological systems (SESs) presents inherent challenges, such as coordination across disparate disciplines or integrating across multiple scales and levels of governance. To overcome these common challenges, we propose that structuring the research design itself according to SES principles provides for integrative execution of SES science. First, starting with pilot work, human and natural science researchers should work as a team to identify and access multi-level entry points (i.e. points of direct engagement) within the system, relative to the spatiotemporal scales under investigation. Second, teams should implement an adaptive process that begins with the proposed research design and uses shared experiences from pilot work to refine protocols prior to subsequent data collection. We provide examples of multi-level and multi-scale entry points, and show that adaptive management of research design through coordinated iteration allows for better research integration and applicable outcomes.     

基于可靠匹配点约束的遥感影像密集匹配

针对现有由稀到密的加密匹配算法中,初始匹配点可靠性低将导致迭代匹配拓展过程存在较多误匹配的问题,提出一种基于可靠匹配点约束的遥感影像密集匹配算法.首先,利用SIFT匹配点约束直线匹配获得的同名直线构建虚拟匹配点集,结合虚拟匹配点集和SIFT匹配点集建立初始匹配点集;然后,依次采用局部影像信息和局部几何约束对初始匹配点集...     

考虑区域水资源地震破坏后的信息管理模型设计

传统水资源信息管理模型采用GIS网络技术,对水资源信息进行优化配置,未对地震多发区域水资源管网进行综合规划,存在地震破坏后受污染水资源信息管理性能差的问题。设计考虑区域水资源地震破坏后污染的信息管理模型,模型包括受污染水资源信息规划设计模块、信息监测和采集模块、信息管理模块。3个模块分别实现对地震破坏后污染的水资源管网的合理规划、监测和采集以及污染信息的综合管理。实验结果表明,所设计模型对区域水资源地震破坏后污染的信息管理的平均时间达到1.38 s,且在管理过程中各项功能的评分都高于93.5分,具有较高的管理性能。     

短程红外测距仪周期误差检测中几个问题探讨

本文应用数理统计方法和误差理论,讨论了短程红外测距仪周期误差检测中的观测点数,并推导出数理统计显著性检验实用公式。同时,对呆用平台法检测周期误差的棱镜对点精度进行了分析。     

交会法测定水平位移的精度分析

对目前常用的几种典型交会测量方法进行了理论上的精度分析 ,并利用某大坝水平位移监测点的实测数据进行分析、验证 ,得出了一些有益的结论。     

一种基于SiftGPU的遥感影像匹配方法

针对已有的遥感影像匹配方法难以同时满足高精度、可靠性和高效率要求的问题,该文提出一种基于分块策略的尺度不变特征变换快速匹配方法。首先对两幅待匹配影像进行分块,根据影像的坐标信息建立参考影像与搜索影像上每个分块的对应关系,并进行量化级数转换;然后对每一对分块影像采用尺度不变特征变换算子进行匹配,同时采用GPU进行加速;最后对得到的所有匹配点进行误匹配点剔除。为验证该方法的有效性,采用经过正射纠正的ALOS影像和经过传感器校正的资源三号正视影像进行匹配实验。实验结果表明,该方法能够得到较多高精度的同名点,并且能在短时间内完成大数据量的处理。     

多尺度点云噪声检测的密度分析法

当前机载激光雷达数据和影像匹配得到的点云是密集点云数据的两类主要来源,但都不可避免存在着噪声点。本文提出一种新的点云去噪算法,可适用于这两类数据中所包含的噪声点的去除。算法主要包括两步:第1步利用多尺度的密度算法去除孤立噪声和小的簇状噪声;第2步利用三角网约束将第1步中误检测为噪声的点重新归为正常点。针对真实数据进行了剔噪试验,结果表明本文提出的基于密度分析的多尺度噪声检测算法对孤立噪声和簇状噪声都有较为效,且对于质量较差的影像匹配点云的检测也能有效处理。本文算法检测率达到97%以上。