Semantic Expansion of Geographic Web Queries Based on Natural Language Positioning Expressions

The need for better Web search tools is getting increasing attention nowadays. About 20% of the queries currently submitted to search engines include geographic references. Thus, it is particularly important to work with the semantics of such queries, both by understanding the terminology and by recognizing geographic references in natural language text. In this paper, we explore the use of natural language expressions, which we call positioning expressions, to perform geographic searches on the Web, without resorting to geocoded data or gazetteers. Such positioning expressions denote the location of a subject of interest with respect to a landmark. Our approach leads to a query expansion technique that can be explored by virtually any keyword‐based search engine. Results obtained in our experiments show an expressive improvement over the traditional keyword‐based search and a potential path for tackling many kinds of common geographic queries.     

An environment for content-based image retrieval from large spatial databases

In this paper, we address the problem of content-based image retrieval using queries on shape and topology. We focus on the particularities of image databases encountered in typical topographic applications and present the development of a spatial data management system that enables such queries. The query requires user-provided sketches of the shape and spatial configuration of the object (or objects) which should appear in the images to be retrieved. The objective of the search is to retrieve images that contain a configuration of objects sufficiently similar to the one specified in the query. Our approach combines the design of an integrated database with the development of a feature library and the necessary matching tools. In this paper, we present our overall scheme, introduce some individual database components, and provide some implementation results.     

球面菱形离散格网正二十面体剖分法

基于菱形单元的球面离散格网具有结构简单和方向性一致等优点,使得其适用于全球多尺度空间数据建模与分析.本文提出一种球面菱形离散格网正二十面体剖分法.首先根据地球的主要地理特征确定正二十面体各个顶点在球面上的位置;其次针对南北两极处的极点奇异性,建立了球面经纬度坐标与三维直角坐标之间的转换关系,在此基础上提出球面菱形离散格网层次递归剖分算法,并从菱形格网单元面积、长短轴比两方面对剖分结果进行几何形变分析;最后验证了本文方法的可行性,试验结果表明,该方法可有效地构建基于正二十面体的球面菱形离散格网,其总体几何特性明显优于基于正八面体构建的球面菱形离散格网.     

一种R树与格网结合的海量地铁隧道点云管理方法

为满足海量地铁隧道点云的高效处理需求,提出了一种R树与格网结合的海量地铁隧道点云管理方法。针对隧道点云的空间分布特点,在全局将大范围点云划分到格网中,并使用R树管理非空网格;在局部使用八叉树与四叉树混合的索引方法管理单个网格内的点云。为了提高点云的渲染效果,提出了基于网格面积的多细节层次结构（levels of detail,LOD）回溯构建方法,并采用高效的单文件存储方式存储点云。实验结果证明了所提出的方法在海量隧道点云的管理和可视化方面优于传统方法。     

Mobile Space-Time Envelopes for Location-Based Services

The convergence and miniaturisation of a range of information and communication technologies, together with increasing bandwidth availability and near ubiquity of mobile phones, are giving rise to a technological environment in which location‐based services (LBS) can realistically develop. In this paper we review the nature of location‐based services and the implications for data and spatial queries. In doing so, we put forward a research agenda that arises for geographical information science and engineering. Central to LBS are problems of response time and the information utility of responses to queries and any pushed alerts, where information utility refers to content, timeliness and geographical footprint. Within a publish/subscribe model of LBS provision, we propose mobile space‐time envelopes as a novel approach to event brokerage. These envelopes simultaneously provide ‘soft clip’ pruning of candidate data sets in anticipation of queries, and provide the trigger that subscribers are pertinently in‐range for alerts. We present the geometrical, algebraic and algorithmic concepts of mobile space‐time envelopes and provide an example of these mobile envelopes in action. We conclude with a discussion of how this initial implementation could be further developed to incorporate added spatio‐temporal intelligence.     

Detection,segmentation and classification of 3D urban objects using mathematical morphology and supervised learning

We propose an automatic and robust approach to detect, segment and classify urban objects from 3D point clouds. Processing is carried out using elevation images and the result is reprojected onto the 3D point cloud. First, the ground is segmented and objects are detected as discontinuities on the ground. Then, connected objects are segmented using a watershed approach. Finally, objects are classified using SVM with geometrical and contextual features. Our methodology is evaluated on databases from Ohio (USA) and Paris (France). In the former, our method detects 98% of the objects, 78% of them are correctly segmented and 82% of the well-segmented objects are correctly classified. In the latter, our method leads to an improvement of about 15% on the classification step with respect to previous works. Quantitative results prove that our method not only provides a good performance but is also faster than other works reported in the literature.     

从机载激光雷达点云提取建筑物屋顶边界的活动轮廓模型改进方法

本文基于边缘与局部信息提出了一种处理多波段图像的活动轮廓模型,并将其应用于LiDAR数据的建筑物边界提取。本文首先将分类得到的屋顶点云数据转换为栅格数据,并作为模型的输入图像,进而采用变分水平集方法解求模型能量函数的最小解,得到建筑物的边界。该模型消除了其他活动轮廓模型对初始曲线和所处理图像类型的限制,适于任意形状的建筑物边界的自动提取;水平集规则项的添加,减小了模型的计算时间。实验结果表明：与IAC模型、GACcolor模型相比,本文模型在建筑物边界提取的应用中可以达到更高的匹配度、形状相似度以及位置精度。     

Computing and querying strict,approximate, and metrically refined topological relations in linked geographic data

Geographic entities and the information associated with them play a major role in Web‐scale knowledge graphs such as Linked Data. Interestingly, almost all major datasets represent places and even entire regions as point coordinates. There are two key reasons for this. First, complex geometries are difficult to store and query using the current Linked Data technology stack to a degree where many queries take minutes to return or will simply time out. Second, the absence of complex geometries confirms a common suspicion among GIScientists, namely that for many everyday queries place‐based relational knowledge is more relevant than raw geometries alone. To give an illustrative example, the statement that the White House is in Washington, DC is more important for gaining an understating of the city than the exact geometries of both entities. This does not imply that complex geometries are unimportant but that (topological) relations should also be extracted from them. As Egenhofer and Mark (1995b) put it in their landmark paper on naive geography, topology matters, metric refines. In this work we demonstrate how to compute and utilize strict, approximate, and metrically refined topological relations between several geographic feature types in DBpedia and compare our results to approaches that compute result sets for topological queries on the fly.     

MASTER: A multiple aspect view on trajectories

For many years trajectory data have been treated as sequences of space‐time points or stops and moves. However, with the explosion of the Internet of Things and the flood of big data generated on the Internet, such as weather channels and social network interactions, which can be used to enrich mobility data, trajectories become more and more complex, with multiple and heterogeneous data dimensions. The main challenge is how to integrate all this information with trajectories. In this article we introduce a new concept of trajectory, called multiple aspect trajectory, propose a robust conceptual and logical data model that supports a vast range of applications, and, differently from state‐of‐the‐art methods, we propose a storage solution for efficient multiple aspect trajectory queries. The main strength of our data model is the combination of simplicity and expressive power to represent heterogeneous aspects, ranging from simple labels to complex objects. We evaluate the proposed model in a tourism scenario and compare its query performance against the state‐of‐the‐art spatio‐temporal database SECONDO extension for symbolic trajectories.     

正二十面体全球剖分模型的Geometry Clipmap球面绘制

地形绘制一直是图形学研究的热点问题,尤其是球面地形绘制,其在形状和数据组织方面比平面地形绘制更加复杂。在已有球面地形绘制算法的基础上,提出一种基于Geometry Clipmap的球面地形剖分与绘制方法。该方法以构建正二十面体球面网格为基础,将正二十面体划分为十个菱形区域,采用球面菱形网格的剖分,针对每个菱形区域的周边网格进行重新剖分和组合,形成一个虚拟的3×3的大菱形区域,扩大了Clipmap的活动范围,并在一定程度上解决了Clipmap的跨边界问题。实验结果表明了本文方法的可行性和有效性。     

综合多要素的地理空间数据众包任务推荐方法

针对境外欠发达国家（或地区）地理空间数据和志愿者不足问题,为提高有限志愿者的贡献积极性和有效性,本文提出了一种综合多要素的地理空间数据众包任务推荐方法。首先采用网格将研究区域划分为若干任务;然后引入三角核函数计算用户空间偏好,结合时间遗忘率综合计算用户的时空偏好,借鉴TF-IDF和余弦相似度计算语义偏好,并融合时空、语义偏好获取初始兴趣推荐列表;最后利用隐语义模型预测用户标注每个任务的信誉（能力）,并根据用户信誉对初始推荐列表重排序。为验证本文方法有效性,以有一定数据基础的巴基斯坦首都伊斯兰堡为试验区,采用OpenStreetMap平台收集的用户及众包数据开展任务区推荐试验,试验数据按照8：2的比例随机划分为训练集和测试集。试验结果表明,该方法不仅能提高推荐任务接受率,还能提高用户完成任务的有效性。     

具有鲁棒性的彩色图像检索方法

提出了一种鲁棒的图像检索方法，它能够在检索大规模图像库时实现基于内容的快速匹配。匹配的索引来源于重量化HSV颜色空间得到的灰度图（Z值图）的区域特征。由于Z值图由反映色彩的聚类区域组成，并且使用矩方法来表达特征，因此该检索方法是鲁棒的，具有2维平移、尺度、旋转不变性，同时可以避免逐点匹配产生的时间耗费。     

The Basic Formal Ontology as a Reference Framework for Modeling the Evolution of Administrative Units

In information systems, ontologies promise advantages such as enhanced interoperability, knowledge sharing, and integration of data sources. In this article, we show that the upper ontology Basic Formal Ontology can facilitate the modeling of an evolution of administrative units. This is demonstrated by creating a spatiotemporal ontology for the administrative units of Switzerland. The ontology tackles the problem that the geometric data is typically captured by taking snapshots at regular intervals while the thematic data is continually updated. The ontology presented merges time‐stamped geometries with a formally described history of administrative units, allowing for complex spatiotemporal queries neither standard approach would support. The resulting populated knowledge base was evaluated against a set of spatiotemporal test queries. The evaluation showed that this knowledge base supports a wide range of queries on the evolution of the administrative units of Switzerland between 1960 and 2010.     

Monocular 3D scene reconstruction at absolute scale

In this article we propose a method for combining geometric and real-aperture methods for monocular three-dimensional (3D) reconstruction of static scenes at absolute scale. Our algorithm relies on a sequence of images of the object acquired by a monocular camera of fixed focal setting from different viewpoints. Object features are tracked over a range of distances from the camera with a small depth of field, leading to a varying degree of defocus for each feature. Information on absolute depth is obtained based on a Depth-from-Defocus approach. The parameters of the point spread functions estimated by Depth-from-Defocus are used as a regularisation term for Structure-from-Motion. The reprojection error obtained from bundle adjustment and the absolute depth error obtained from Depth-from-Defocus are simultaneously minimised for all tracked object features. The proposed method yields absolutely scaled 3D coordinates of the scene points without any prior knowledge about scene structure and camera motion. We describe the implementation of the proposed method both as an offline and as an online algorithm. Evaluating the algorithm on real-world data, we demonstrate that it yields typical relative scale errors of a few per cent. We examine the influence of random effects, i.e. the noise of the pixel grey values, and systematic effects, caused by thermal expansion of the optical system or by inclusion of strongly blurred images, on the accuracy of the 3D reconstruction result. Possible applications of our approach are in the field of industrial quality inspection; in particular, it is preferable to stereo cameras in industrial vision systems with space limitations or where strong vibrations occur.     

Consistency grammar for 3D indoor model checking

Indoor 3D models are digital representations of building interiors reconstructed from scanned data acquired by laser scanners, digital depth (RGBD) cameras, and CAD drawings. Consequently, there is noise in the source data and a notable variety in the methods used to treat the noise and to process these data into reconstructed models. Alas, the correctness of these reconstructions and thus their suitability for a given application are uncertain. There is a lack of a robust base logic that would allow for controlling the consistency of these (automatically) generated models. Fortunately, correctness criteria are well‐defined through existing international standards. Hence, we propose a conceptual framework based on formal grammars to check the semantic, geometric, and topological consistency of a reconstructed 3D model. The proposed method proceeds in three steps to validate the model: (1) correctness checking of individual components; (2) consistency verification of instances’ interactions; and (3) model consistency check for targeted applications. Our method identifies the components in the model that violate the given rules derived from the current standards and expert knowledge. Ultimately, we propose a quantified formulation of our method that may be straightforwardly integrated into industrial‐level model checkers. The approach is independent of level of details and reconstruction method.     

Semantic typing of linked geoprocessing workflows

In Geographic Information Systems (GIS), geoprocessing workflows allow analysts to organize their methods on spatial data in complex chains. We propose a method for expressing workflows as linked data, and for semi-automatically enriching them with semantics on the level of their operations and datasets. Linked workflows can be easily published on the Web and queried for types of inputs, results, or tools. Thus, GIS analysts can reuse their workflows in a modular way, selecting, adapting, and recommending resources based on compatible semantic types. Our typing approach starts from minimal annotations of workflow operations with classes of GIS tools, and then propagates data types and implicit semantic structures through the workflow using an OWL typing scheme and SPARQL rules by backtracking over GIS operations. The method is implemented in Python and is evaluated on two real-world geoprocessing workflows, generated with Esri's ArcGIS. To illustrate the potential applications of our typing method, we formulate and execute competency questions over these workflows.     

面向虚拟地球的海陆地形多尺度TIN建模及可视化方法

提出了一种面向虚拟地球的海陆地形多尺度不规则三角网（triangulated irregular network,TIN）建模及球面快速可视化方法。利用贪心插入TIN表面简化算法构建海陆地形的离线TIN金字塔,并设计了一种高效的虚拟节点结构,对各级TIN构网实施无缝分割和分层分块存储。在利用离线TIN地形金字塔实现多尺度海陆TIN地形的快速检索和三维场景生成的基础上,通过一种接边关系编解码方案实时消除TIN地形渲染时的裂缝,最终实现多尺度海陆TIN地形场景的高效可视化。实验结果表明,该方法能显著减少海面渲染所需的面片数,并实现岛礁、海岸等破碎地形的高保真度表达,有效改善了传统虚拟地球系统采用规则格网（Gird）模式绘制海陆地形导致大量几何冗余和表达失真等缺陷。     

Qualitative GIS: An Open Framework Using SpatiaLite and Open Source GIS

Qualitative GIS is a relatively new methodological approach for analyzing and visualizing qualitative data within a geographic context. Qualitative data can take many forms, including interviews, documents, photographs, and audio and video clips. Content analysis for example, is an effective qualitative method for analyzing text‐based data. We argue that basic concepts, (i.e. how to store data, data requirements, visualization techniques, and modes of analysis) within qualitative GIS have not been adequately defined, rendering difficult the replication of work performed and hindering the development of incremental knowledge in the field. Database management systems provide a means for storing, managing, and analyzing qualitative GIS data. A standardized and well‐designed open source database system provides a mechanism for qualitative GIS projects, ensuring consistency and project replication. Qualitative GIS data stored in a database allows for additional visualization options, such as geographic word clouds. To demonstrate the concepts we performed content analysis on Master Transportation Plans from Calgary and Montreal using SpatiaLite, an open source database system. We developed Structured Query Language (SQL) queries to generate and populate groups and theme tables within the SpatiaLite database. We present our database design and queries in the hopes that they will help others conducting qualitative GIS research.     

A geometric stochastic approach based on marked point processes for road mark detection from high resolution aerial images

Road detection has been a topic of great interest in the photogrammetric and remote sensing communities since the end of the 70s. Many approaches dealing with various sensor resolutions, the nature of the scene or the wished accuracy of the extracted objects have been presented. This topic remains challenging today as the need for accurate and up-to-date data is becoming more and more important. Based on this context, we will study in this paper the road network from a particular point of view, focusing on road marks, and in particular dashed lines. Indeed, they are very useful clues, for evidence of a road, but also for tasks of a higher level. For instance, they can be used to enhance quality and to improve road databases. It is also possible to delineate the different circulation lanes, their width and functionality (speed limit, special lanes for buses or bicycles...).In this paper, we propose a new robust and accurate top–down approach for dashed line detection based on stochastic geometry. Our approach is automatic in the sense that no intervention from a human operator is necessary to initialise the algorithm or to track errors during the process. The core of our approach relies on defining geometric, radiometric and relational models for dashed lines objects. The model also has to deal with the interactions between the different objects making up a line, meaning that it introduces external knowledge taken from specifications.Our strategy is based on a stochastic method, and in particular marked point processes. Our goal is to find the objects configuration minimising an energy function made-up of a data attachment term measuring the consistency of the image with respect to the objects and a regularising term managing the relationship between neighbouring objects. To sample the energy function, we use Green algorithm’s; coupled with a simulated annealing to find its minimum.Results from aerial images at various resolutions are presented showing that our approach is relevant and accurate as it can handle the most frequent layouts of dashed lines. Some issues, for instance, such as the relative weighting of both terms of the energy are also discussed in the conclusion.     

SAR Image Segmentation Based on Level Set With Stationary Global Minimum

In this letter, we propose a new level-set-based energy functional for the purpose of synthetic aperture radar (SAR) image segmentation into Gamma homogeneous regions. The segmentation of SAR images is a difficult problem due to the presence of speckles, which can be modeled as strong multiplicative noise. Our proposed energy functional is designed to get a stationary global minimum. As a result, the level set function that evolves by the Euler–Lagrange equation of the energy functional has a unique stationary convergence state. Moreover, it is easy to set a termination criterion on the curve evolution via a level set by using our energy functional. The experimental results on both synthetic and real SAR images demonstrate the effectiveness of our method.