利用快速反应码的矢量空间数据盲水印算法

针对传统的字符编码没有容错功能的缺陷,文章提出了基于快速反应(QR)码的矢量空间数据盲水印算法。该方法对要嵌入的字符应用QR码编码,生成QR码二值图像,并应用Logistic混沌系统对该QR码图像进行混沌置乱,对处理后的水印图像按位嵌入矢量空间数据的空域部分,水印被多次嵌入。实验结果表明,该方法不仅能够在裁剪后的部分数据中解码出字符,而且具有很好的不可见性,水印嵌入引起的矢量空间数据的误差很小,水印算法对常见的多种攻击具有较好的鲁棒性。     

From taxonomies to ontologies: formalizing generalization knowledge for on-demand mapping

Automation of the cartographic design process is central to the delivery of bespoke maps via the web. In this paper, ontological modeling is used to explicitly represent and articulate the knowledge used in this decision-making process. A use case focuses on the visualization of road traffic accident data as a way of illustrating how ontologies provide a framework by which salient and contextual information can be integrated in a meaningful manner. Such systems are in anticipation of web-based services in which the user knows what they need, but do not have the cartographic ability to get what they want.     

An automated algorithm for mapping building impervious areas from airborne LiDAR point-cloud data for flood hydrology

Buildings, as impervious surfaces, are an important component of total impervious surface areas that drive urban stormwater response to intense rainfall events. Most stormwater models that use percent impervious area (PIA) are spatially lumped models and do not require precise locations of building roofs, as in other applications of building maps, but do require accurate estimates of total impervious areas within the geographic units of observation (e.g. city blocks or sub-watershed units). Two-dimensional mapping of buildings from aerial imagery requires laborious efforts from image analysts or elaborate image analysis techniques using high spatial resolution imagery. Moreover, large uncertainties exist where tall, dense vegetation obscures the structures. Analyzing LiDAR point-cloud data, however, can distinguish buildings from vegetation canopy and facilitate the mapping of buildings. This paper presents a new building extraction approach that is based on and optimized for estimating building impervious areas (BIA) for hydrologic purposes and can be used with standard GIS software to identify building roofs under tall, thick canopy. Accuracy assessment methods are presented that can optimize model performance for modeling BIA within the geographic units of observation for hydrologic applications. The Building Extraction from LiDAR Last Returns (BELLR) model, a 2.5D rule-based GIS model, uses a non-spatial, local vertical difference filter (VDF) on LiDAR point-cloud data to automatically identify and map building footprints. The model includes an absolute difference in elevation (AdE) parameter in the VDF that compares the difference between mean and modal elevations of last-returns in each cell.

The BELLR model is calibrated for an extensive inner-city, highly urbanized small watershed in Columbia, South Carolina, USA that is covered by tall, thick vegetation canopy that obscures many buildings. The calibration of BELLR used a set of building locations compiled by photo-analysts, and validation used independent building reference data. The model is applied to two residential neighborhoods, one of which is a residential area within the primary watershed and the other is a younger suburban neighborhood with a less-well developed tree canopy used as a validation site. Performance results indicate that the BELLR model is highly sensitive to concavity in the lasboundary tool of LAStools® and those settings are highly site specific. The model is also sensitive to cell size and the AdE threshold values. However, properly calibrated the BIA for the two residential sites could be estimated within 1% error for optimized experiments.

To examine results in a hydrologic application, the BELLR estimated BIAs were tested using two different types of hydrologic models to compare BELLR results with results using the National Land Cover Database (NLCD) 2011 Percent Developed Imperviousness data. The BELLR BIA values provide more accurate results than the use of the 2011 NLCD PIA data in both models. The VDF developed in this study to map buildings could be applied to LiDAR point-cloud filtering algorithms for feature extraction in machine learning or mapping other planar surfaces in more broad-based land-cover classifications.     

基于光谱滤波器的混合像元分析

提出一种利用光谱滤波器进行遥感图像混合像元全约束分解的新算法。该算法利用端元光谱中与背景光谱正交的光谱成分构建光谱滤波器,滤除混合像元中的背景干扰成分,直接获取信号光谱的丰度。采用该光谱滤波器多次迭代分解,修正单个混合像元的端元光谱空间,获取其确切的端元光谱配置,保证了分解时各端元丰度的非负性,实现混合像元的全约束分解。多光谱数据仿真实验证明,与全约束最小二乘法(FCLS)和正交投影(OSP)分解法相比,该方法虽然在时间方面略逊一点,但其分解结果与实际结果的相关系数高,均方根误差小,具有很高的分解精度,在遥感定量分析方面具有重要的应用潜力。最后给出了该算法在真实的高光谱图像中进行混合像元分析的结果。     

面向智能化测绘的城市地物三维提取

精准有效的三维时空信息是新型基础设施建设、实景三维中国、自然资源管理与监测等国家重大需求不可或缺的重要支撑。测绘装备的快速发展提升了点云和影像获取的便捷性,为智能化测绘提供了一种全新技术手段。然而,如何从点云、影像中智能地提取三维时空信息仍然面临诸多困境。本文围绕城市场景中地物目标智能化提取的需求,重点阐述点云位置精度改善、点云与全景影像融合、部件级典型地物要素精细提取、软件研发与工程实践4个方面的关键技术与研究进展,为实景三维中国建设等提供关键支持。     

Bringing GPS into harsh environments for fully automated deformation monitoring

Engineering projects that require deformation monitoring frequently utilize geodetic sensors to measure displacements of target points located in the deformation zone. In situations where control stations and targets are separated by a kilometer or more, GPS can offer higher precision position updates at more frequent intervals than can normally be achieved using total station technology. For large-scale deformation projects requiring the highest precision, it is therefore advisable to use a combination of the two sensors. In response to the need for high precision, continuous GPS position updates in harsh deformation monitoring environments, a software has been developed that employs triple-differenced carrier-phase measurements in a delayed-state Kalman filter. Two data sets were analyzed to test the capabilities of the software. In the first test, a GPS antenna was displaced using a translation stage to mimic slow deformation. In the second test, data collected at a large open pit mine were processed. It was shown that the delayed-state Kalman filter developed could detect millimeter-level displacements of a GPS antenna. The actual precision attained depends upon the amount of process noise infused at each epoch to accommodate the antenna displacements. Higher process noise values result in quicker detection times, but at the same time increase the noise in the solutions. A slow, 25 mm displacement was detected within 30 min of the full displacement with sigma values in E, N and U of ±10 mm or better. The same displacement could also be detected in less than 5 h with sigma values in E, N and U of ±5 mm or better. The software works best for detecting long period deformations (e.g., 20 mm per day or less) for which sigma values of 1–2 mm are attained in all three solution components. It was also shown that the triple-differenced carrier-phase observation can be used to significantly reduce the effects of residual tropospheric delay that would normally plague double-differenced observations in harsh GPS environments.

A geospatial search engine for discovering multi-format geospatial data across the web

The volume of publically available geospatial data on the web is rapidly increasing due to advances in server-based technologies and the ease at which data can now be created. However, challenges remain with connecting individuals searching for geospatial data with servers and websites where such data exist. The objective of this paper is to present a publically available Geospatial Search Engine (GSE) that utilizes a web crawler built on top of the Google search engine in order to search the web for geospatial data. The crawler seeding mechanism combines search terms entered by users with predefined keywords that identify geospatial data services. A procedure runs daily to update map server layers and metadata, and to eliminate servers that go offline. The GSE supports Web Map Services, ArcGIS services, and websites that have geospatial data for download. We applied the GSE to search for all available geospatial services under these formats and provide search results including the spatial distribution of all obtained services. While enhancements to our GSE and to web crawler technology in general lie ahead, our work represents an important step toward realizing the potential of a publically accessible tool for discovering the global availability of geospatial data.     

利用GML模式映射屏蔽地理空间数据源的异构性

本文分析了地理空间数据源的异构性以及GML模式的异构性;提出以GML模式对地理空间要素进行建模,构建适合空间信息共享的GML基本地物规范模式;通过应用模式的结构去屏蔽不同数据源结构的异构性,通过对应物属性去屏蔽编码语义的异构性,使空间信息的共享与互操作有统一的语义基础。     

二维哈希算法在地理空间数据批量分幅中的应用

分幅地理空间数据坐标转换后,还需在新坐标系下重新分幅.对于其中的批量数据,在新旧图幅重叠判断时需要大量的检索操作,快速查找算法能够提高查找效率.本文在建立新旧图幅关联关系、确定重叠判断方法和分割要素的文件存储方式后,提出了一种以新图幅中心点坐标为关键字的二维哈希表索引构建和重叠图幅查找的算法;给出了算法设计思路,并以实...     

A new Likelihood Ratio for supervised classification of fully polarimetric SAR data: An application for sea ice type mapping

One of the potential applications of polarimetric Synthetic Aperture Radar (SAR) data is the classification of land cover, such as forest canopies, vegetation, sea ice types, and urban areas. In contrast to single or dual polarized SAR systems, full polarimetric SAR systems provide more information about the physical and geometrical properties of the imaged area. This paper proposes a new Bayes risk function which can be minimized to obtain a Likelihood Ratio (LR) for the supervised classification of polarimetric SAR data. The derived Bayes risk function is based on the complex Wishart distribution. Furthermore, a new spatial criterion is incorporated with the LR classification process to produce more homogeneous classes. The application for Arctic sea ice mapping shows that the LR and the proposed spatial criterion are able to provide promising classification results. Comparison with classification results based on the Wishart classifier, the Wishart Likelihood Ratio Test Statistic (WLRTS) proposed by Conradsen et al. (2003) and the Expectation Maximization with Probabilistic Label Relaxation (EMPLR) algorithm are presented. High overall classification accuracy of selected study areas which reaches 97.8% using the LR is obtained. Combining the derived spatial criterion with the LR can improve the overall classification accuracy to reach 99.9%. In this study, fully polarimetric C-band RADARSAT-2 data collected over Franklin Bay, Canadian Arctic, is used.     

MapSafe: A complete tool for achieving geospatial data sovereignty

Sensitive geographic data are invaluable assets for the people to whom they belong and their disclosure should be decided by the sovereign data owner (SDO). Due to several high-profile data breaches and business models that commercialize user data, the need for new approaches to geoprivacy and data sovereignty has grown. We propose MapSafe, a client web application that first obfuscates datasets using donut masking or hexagonal binning, separately, and thereafter implements a multi-level encryption scheme that permits SDOs to share the final encrypted volume containing the geospatial information when they choose and at a level of detail which they are comfortable. The authenticity verification of the volume is facilitated by storing the hash value corresponding to the encrypted volume immutably on the Blockchain as a public record. Our approach places geoprivacy under data guardians'’ control, and its integration capabilities promote its adoption in existing and future geospatial web systems.     

煤矿地质成图中多边形快速生成算法

针对煤矿地质成图中左转算法生成多边形在复杂的二维图形条件下应用效率低的问题,该文提出了一种新的基于左转算法的多边形快速选取及自动生成算法,实现了2D图形环境中多边形的快速选取及自动生成。通过在进行多边形选取时的起始点,起始方向的选择和对悬挂点、线进行处理,解决了复杂图形下多边形选取及自动生成过程中存在的重复生成、效率低下和搜索回退问题。基于GeoMS3D实现该算法,实验结果表明:该算法逻辑简单、结构清晰,在实际的应用中表现出了较高的运算效率。     

一种新的车载低成本MEMS陀螺仪快速初始对准算法

车载导航系统常用惯性测量元件(IMU)与全球卫星导航系统(GNSS)技术组合以提高系统的稳定性。由于车载导航系统的应用场景限制,对初始对准速度有着较高要求。为了提高传统车载组合导航系统中低成本微机电系统(MEMS)陀螺仪的初始对准速度,降低初始对准过程中的计算量,本文提出了一种适用于任意失准角下的基于网络RTK辅助与无损Kalman滤波(UKF)的MEMS陀螺仪初始对准算法。同时针对车载系统的特点,简化了IMU系统误差方程,分析了简化带来的误差。在诺瓦泰ProPak6和诺瓦泰IMU-IGM-S1组成的导航系统中验证了本文提出的算法。试验结果表明,在以诺瓦泰双天线GNSS输出航向角为"真值"的情况下,本文提出的算法基本可以在5 s内完成陀螺仪的初始对准,对准精度达0.3°。     

道路边桩自动绘制算法实现及应用

道路边桩是用来控制道路宽度的一个道路要素,边桩分为道路征地红线边桩和实际道路设计宽度边桩.在内业处理过程中需要将这些边桩及其相关的边桩距离、中桩绘制在设计图上.为了将这些数据按照成果提交要求快速准确绘制,本文提出了一套绘制算法,并鉴于设计数据格式为AutoCAD格式,利用ObjectArx组件技术对算法编程实现,实现了...     

一种矢量线数据零水印算法

为了满足矢量地理空间数据高精度和零扰动的实用性需要,该文提出一种零水印算法。首先利用Logistic混沌映射置乱原始水印图像;然后对原始矢量线数据进行离散傅里叶变换,获得离散傅里叶变换后的相位值,并将相位值由弧度值转换为角度值;接着随机选取均匀分布的角度值,向下取整后转换为相应的二进制形式,得到二值矩阵;最后将置乱后的水印图像与由相位值构成的二值矩阵进行异或操作,从而构造出零水印图像。实验结果表明,该算法能够抵抗常见的平移、缩放等几何攻击,并且对数据格式转换攻击、投影变换攻击具有较好的鲁棒性。     

A novel mathematical morphology based algorithm for shoreline extraction from satellite images

Abstract

Shoreline extraction is fundamental and inevitable for several studies. Ascertaining the precise spatial location of the shoreline is crucial. Recently, the need for using remote sensing data to accomplish the complex task of automatic extraction of features, such as shoreline, has considerably increased. Automated feature extraction can drastically minimize the time and cost of data acquisition and database updating. Effective and fast approaches are essential to monitor coastline retreat and update shoreline maps. Here, we present a flexible mathematical morphology-driven approach for shoreline extraction algorithm from satellite imageries. The salient features of this work are the preservation of actual size and shape of the shorelines, run-time structuring element definition, semi-automation, faster processing, and single band adaptability. The proposed approach is tested with various sensor-driven images with low to high resolutions. Accuracy of the developed methodology has been assessed with manually prepared ground truths of the study area and compared with an existing shoreline classification approach. The proposed approach is found successful in shoreline extraction from the wide variety of satellite images based on the results drawn from visual and quantitative assessments.     

An automated algorithm for extracting road edges from terrestrial mobile LiDAR data

Terrestrial mobile laser scanning systems provide rapid and cost effective 3D point cloud data which can be used for extracting features such as the road edge along a route corridor. This information can assist road authorities in carrying out safety risk assessment studies along road networks. The knowledge of the road edge is also a prerequisite for the automatic estimation of most other road features. In this paper, we present an algorithm which has been developed for extracting left and right road edges from terrestrial mobile LiDAR data. The algorithm is based on a novel combination of two modified versions of the parametric active contour or snake model. The parameters involved in the algorithm are selected empirically and are fixed for all the road sections. We have developed a novel way of initialising the snake model based on the navigation information obtained from the mobile mapping vehicle. We tested our algorithm on different types of road sections representing rural, urban and national primary road sections. The successful extraction of road edges from these multiple road section environments validates our algorithm. These findings and knowledge provide valuable insights as well as a prototype road edge extraction tool-set, for both national road authorities and survey companies.     

地理空间数据访问控制威胁模型及应对策略

针对由于缺少对地理空间数据访问控制安全威胁因素的详细分析使得现有的地理空间访问控制模型不够完善的问题,该文提出了地理空间数据访问控制安全威胁模型——STALE模型。该模型结合空间关系、多尺度、属性等地理空间数据特征,详细描述了地理空间数据文件与数据库在访问控制中存在的安全威胁。在此基础上,针对模型中各类威胁因素,提出了应对策略,并进行了实验验证,证明了STALE模型的实用性。     

Fundamental aspects of access control for geospatial data

Abstract

In recent years, geographical information systems have been employed in a wide variety of application domains, and as a result many research efforts are being devoted to those upcoming problems. Geospatial data security, especially access control, has attracted increased research interests within the academic community. The tendency towards sharing and interoperability of geospatial data and applications makes it common to acquire and integrate geospatial data from multiple organisations to accomplish a complex task. Meanwhile, many organisations have the requirement for securing access to possessed sensitive or proprietary geospatial data. In this heterogeneous and distributed environment, consistent access control functionality is crucial to promote controlled accessibility. As an extension of general access control mechanisms in the IT domain, the mechanism for geospatial data access control has its own requirements and characteristics of granularity and geospatial logic. In this paper, we address several fundamental aspects concerning the design and implementation of an access control system for geospatial data, including the classification, requirements, authorisation models, storage structures and management approaches for authorisation rules, matching and decision-making algorithms between authorisation rules and access requests, and its policy enforcement mechanisms. This paper also presents a system framework for realising access control functionality for geospatial data, and explain access control procedures in detail.