城市违建分析测量图册的设计与实践

随着社会的发展,城市化的进程也逐渐加快,在城市建设过程中,一些不符合城市规划的违法建筑陆续出现。城市违建分析测量图册充分利用测绘、GIS和遥感技术,以及规划的相关知识对指定的疑似违建地块进行全方位的展现,服务于政府决策。本文对该图册的制作过程及关键技术做了简要描述,为相关工作的开展提供参考。     

Effectiveness of a Semi-Immersive Virtual Environment in Understanding Human–Environment Interactions

Virtual environments and related technology generate interest and excitement. Their power is strengthened with empirical evidence of their utility for scientific inquiry and decision-making. This paper reports on a study to evaluate the effectiveness of virtual environment (VE) presentations about issues typical of those facing decision makers in a rapidly growing urban area. The presentations consisted of the explanation and visualization of two phenomena—groundwater overdraft and the urban heat island. The virtual environment utilized in this study, Arizona State University's Decision Theater, is purported to help policy makers and the larger community visualize complex model output and make decisions about scientific issues. To begin to assess these claims, we carried out a user test during which a group of research participants were given two surveys, one before the presentations, to determine a priori understanding, and a second afterwards, with the same questions. This methodology allowed us to carry out within-subjects tests concerning contrasting phenomena, in order to assess two primary hypotheses: (1) knowledge and perceptions of environmental phenomena will change after the viewing, and (2) understanding will vary based on the phenomena in the presentations. Our analysis shows at least some level of support for the hypotheses, with evidence that the virtual environment positively influenced understanding, and that there may be important differences in insight generation based on characteristics of the phenomena represented. Finally, we outline critical areas of future research to further knowledge about the impact of visual VE settings on understanding and decision making.     

A New Framework for Solving the Spatial Network Problems Based on Line Graphs

In this article we define inverse line graphs of directed graphs as a new framework for solving some classical network analysis problems. The extraction method and theories of inverse line graphs are explained in this article. It is shown that by changing the analysis space from the original directed graph to the inverse line graph, complex problems can be changed into simpler problems. We show the usefulness of the proposed framework in two particular applications: shortest path computations and the more general route planning. Considering the implementation result, we expect that this framework could be used in many more network analysis problems.     

面向地下空间规划建设的三维辅助决策平台研究与实现

基于为地下空间规划建设提供科学决策的目的,本文提出了基于三维仿真技术的地下空间规划建设辅助决策平台建设的思路,构建了三维辅助决策平台的整体框架,借助正元三维GIS平台Genius World,实现了对基础地理、城市地质、地下空间设施数据的一体化存储管理和三维可视化集成表达。同时,根据实际业务需求,研究并实现了集地上地下一体化剖面分析、大型建筑物选址分析、地下轨道交通选线规划、地下空间适宜性评价等于一体的地下空间辅助规划平台,提供了规划设计方案的合理性综合分析与模拟评价,提高了地下空间规划建设的科学性、规范性、严密性和高效性。最后对地下空间规划建设辅助决策做出了总体评价,并提出了下一步研究方向。     

Testing Popular Visualization Techniques for Representing Model Uncertainty

Many land allocation issues, such as land-use planning, require input from extensive spatial databases and involve complex decision-making. Spatial decision support systems (SDSS) are designed to make these issues more transparent and to support the design and evaluation of land allocation alternatives. In this paper we analyze techniques for visualizing uncertainty of an urban growth model called SLEUTH, which is designed to aid decision-makers in the field of urban planning and fits into the computational framework of an SDSS. Two simple visualization techniques for portraying uncertainty—static comparison and toggling—are applied to SLEUTH results and rendered with different background information and color schemes. In order to evaluate the effectiveness of the two visualization techniques, a web-based survey was developed showing the visualizations along with questions about the usefulness of the two techniques. The web survey proved to be quickly accessible and easy to understand by the participants. Participants in the survey were mainly recruited among planners and decision-makers. They acknowledged the usefulness of portraying uncertainty for decision-making purposes. They slightly favored the static comparison technique over toggling. Both visualization techniques were applied to an urban growth case study for the greater Santa Barbara area in California, USA.     

基于决策规则的遥感影像土地利用信息提取

遥感作为近几十年迅速发展起来的一门综合性技术学科,己经在许多领域发挥了重大作用。通过对遥感数据进行专题分类处理以得到土地利用等专题信息是遥感最广泛的应用领域之一。尽管土地利用遥感分类方法不断发展,但分类技术始终跟不上遥感技术本身的发展。本论文的主要目标之一就是以沈阳矿区为研究区,利用多源遥感数据结合地面实地调查,围绕遥感图像,采用常规的最大似然分类法,同时采用选用决策树分类方法,对不同数据源得到的信息进行综合分析,充分利用其中的光谱信息、地学知识以及人的经验知识进行土地利用分类,从而更好地为地方土地有效利用提供决策依据。     

Remote sensing research issues of the National Land Use Change Program of China

In 1999, the Ministry of Land and Resources (MLR) of China launched the National Land Use Change Program especially to monitor the scale and distribution of urban expansion and the decrease in cultivated land through remote sensing technology. This Program has been carried out annually and continuously for seven years since then and played an important role in the policy-making of MLR about land management and planning. This paper gives an overview about this Program and discusses several research issues. First, the remote sensing data sources and other ancillary data used in this Program are presented. The approaches for image preprocessing, i.e. radiometric normalization, image geometric rectification and image fusion are then introduced with an emphasis on the algorithm development for image registration. Second, land use change detection technique is the most critical and complex aspect of the Program. The methodologies for change detection using either bi-temporal image pair or one existing land use map and one remotely sensed image are detailed. Third, since the data of land use changes derived from remote sensing will be operationally used for local and central government, field validation and accuracy assessment are crucial to ensure the reliability of change detection results. The strategy of field work and the resulting accuracy evaluations is presented. The land use and change information derived from remotely sensed data has wide applications for land management, including land use database updating, verification of land use planning and monitoring of national high-tech parks. Last, suggestions on how to make full use of the images and change detection result, to improve the consistency of land use classification and to develop change detection algorithms for diverse and complex remote sensing data are given.     

国内首个省级地理国情监测规划编制

地理国情监测工作是一项全新的工作,目前在推进业务建设,同时正加快推进其"四进"——"进法律""进职责""进规划""进预算"。在当前没有明确法律依据的情况下,要印发省级地理国情监测专项规划是有较大难度的。云南省将《云南省地理国情监测"十三五"规划》作为重大行政决策事项,通过履行重大行政决策程序而使之获得了法律保障,在规划体例、发展目标、任务布局等方面做了有益探索,为同类规划的编制提供了参考。同时,也为围绕党委政府重大战略需求推进地理国情监测常态化应用提供了有效途径。     

面向地理信息共享的AM/FM/GIS核心语义模型

提出了一种适用于管线行业的AM/FM/GIS数据模型——核心语义模型,对核心语义模型的概念框架,包括定义、编码、空间关系和规则组件环境进行了详细的剖析,得出该数据模型有利于实现管线行业的信息共享、提高数据录入精度、完善地理要素的表达,知识的可扩展性和规则组件的可重用性保证了核心语义模型具有更开放灵活的用户参与机制,最后提出了下一步研究的方向。     

城乡一体化发展背景下地理信息技术的发展趋势

对地理信息技术在城乡规划中的应用现状进行了分析,根据发展趋势提出地理信息技术应适应城乡一体化发展要求,建立完善的数据体系、技术体系和应用体系,为协调区域发展、解决跨地区重大问题提供丰富的基础资料、科学的研究方法和强大的决策支持,并指出应该着重扩大地理信息覆盖范围,丰富信息含量,加快更新速度,完善共享机制;加快发展地理信息获取与处理、整合与管理、分发与应用技术,提供分布式、移动环境下的综合应用;围绕规划、建设、管理的各个环节,提供一体化的GIS解决方案等方面的研究。     

A graph-based approach to detecting tourist movement patterns using social media data

ABSTRACT

Understanding the characteristics of tourist movement is essential for tourist behavior studies since the characteristics underpin how the tourist industry management selects strategies for attraction planning to commercial product development. However, conventional tourism research methods are not either scalable or cost-efficient to discover underlying movement patterns due to the massive datasets. With advances in information and communication technology, social media platforms provide big data sets generated by millions of people from different countries, all of which can be harvested cost efficiently. This paper introduces a graph-based method to detect tourist movement patterns from Twitter data. First, collected tweets with geo-tags are cleaned to filter those not published by tourists. Second, a DBSCAN-based clustering method is adapted to construct tourist graphs consisting of the tourist attraction vertices and edges. Third, network analytical methods (e.g. betweenness centrality, Markov clustering algorithm) are applied to detect tourist movement patterns, including popular attractions, centric attractions, and popular tour routes. New York City in the United States is selected to demonstrate the utility of the proposed methodology. The detected tourist movement patterns assist business and government activities whose mission is tour product planning, transportation, and development of both shopping and accommodation centers.     

Deeply integrating Linked Data with Geographic Information Systems

The realization that knowledge often forms a densely interconnected graph has fueled the development of graph databases, Web‐scale knowledge graphs and query languages for them, novel visualization and query paradigms, as well as new machine learning methods tailored to graphs as data structures. One such example is the densely connected and global Linked Data cloud that contains billions of statements about numerous domains, including life science and geography. While Linked Data has found its way into everyday applications such as search engines and question answering systems, there is a growing disconnect between the classical ways in which Geographic Information Systems (GIS) are still used today and the open‐ended, exploratory approaches used to retrieve and consume data from knowledge graphs such as Linked Data. In this work, we conceptualize and prototypically implement a Linked Data connector framework as a set of toolboxes for Esri's ArcGIS to close this gap and enable the retrieval, integration, and analysis of Linked Data from within GIS. We discuss how to connect to Linked Data endpoints, how to use ontologies to probe data and derive appropriate GIS representations on the fly, how to make use of reasoning, how to derive data that are ready for spatial analysis out of RDF triples, and, most importantly, how to utilize the link structure of Linked Data to enable analysis. The proposed Linked Data connector framework can also be regarded as the first step toward a guided geographic question answering system over geographic knowledge graphs.     

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.     

测绘新技术在建筑工程竣工验收中的应用

针对规划竣工验收测量工作存在的不完善部分,列举了测绘行业内新兴技术的应用方法。应用这些新兴技术,完善了规划竣工验收测量的测绘内容,从而更加细化了规划验收工作的内容,使测绘技术能够在更多的领域为规划管理服务。     

面向行业深度耦合的专业级云GIS服务平台设计

针对行业具体需求定制开发专业级地理信息服务平台,是将地理信息资源和技术优势与具体行业深度耦合,充分挖掘地理信息潜在应用价值的重要步骤。本研究立足专业级地理信息服务平台建设,以云GIS架构为基础开展研究,重点就复杂业务环境下系统高效运行问题、多层级平台架构下各地区信息化发展不均衡问题、平台优势资源灵活复用问题等展开探讨。期望研究成果为相关行业专业级地理信息云服务平台建设提供借鉴。     

智能化土地定级估价信息系统设计与实现

总结分析了当前系统中存在的主要问题,提出将GIS、SDM、ES和可视化等多种信息技术进行有机结合,共同构建具有智能特性和辅助决策功能的土地定级估价信息系统。给出了GIS、SDM、ES和可视化等技术集成的基本框架,设计了基于多种信息技术集成的土地定级估价信息系统的基本结构。采用VC++6.0和MO2.0结合开发了基于多种技术集成的土地定级估价信息系统。研究表明,系统定级估价工作流程简单,结果可靠,且具有良好的移植性、复用性、扩展性和广泛适应性,能较好地解决土地定级估价中土地信息缺失、定性因子量化困难等半结构和非结构化问题。     

城市典型要素遥感智能监测与模拟推演关键技术EI北大核心CSCD

城市典型要素遥感智能监测与模拟推演的理论、方法与应用,对于国土空间规划与管理,城市规划与综合治理,区域决策与管理等均具有关键支撑作用。针对覆盖要素和驱动要素复杂非线性,本文研发了协同多源遥感数据的智能识别方法,实现了精细化高可信覆盖要素分类;协同遥感、POI兴趣点和时空大数据等多源数据,有效探测和识别了要素变动的驱动力。在此基础上,开展了空间演变机理挖掘、空间统计建模、启发式智能建模,并应用于土地利用、城市扩张、生态演变、碳储量等。同时,研发了聚焦城市生长推演的UrbanCA平台以及聚焦多类土地利用变化推演的Futureland平台,集成了自主研发的模拟推演系列方法并以长三角为主要区域进行了验证。     

智慧城市时空信息综合决策关键技术与系统

如何根据智慧城市运行管理、建设规划和应急指挥等政府决策部门的综合需求,实现分散信息资源的统一集成、复杂模型资源的有效调用和决策时空信息的高效共享与可视化,成为现阶段城市综合决策的重大挑战。首先提出了感知联网与时空信息接入、地理空间模型联网与认知、决策时空信息聚焦服务等智慧城市时空信息综合决策共性关键技术,突破了城市时空信息智能分析、协同决策与主动聚焦服务的瓶颈;其次,设计并实现了智慧城市时空信息综合决策原型系统,并以太原市燃气泄漏应急响应为例,验证了系统辅助城市综合决策的可行性和适用性;最后,概括了城市（群）立体感知网、城市（群）模型网和城市（群）时空大数据3大主要发展趋势。     

A spatially explicit reinforcement learning model for geographic knowledge graph summarization

Web‐scale knowledge graphs such as the global Linked Data cloud consist of billions of individual statements about millions of entities. In recent years, this has fueled the interest in knowledge graph summarization techniques that compute representative subgraphs for a given collection of nodes. In addition, many of the most densely connected entities in knowledge graphs are places and regions, often characterized by thousands of incoming and outgoing relationships to other places, actors, events, and objects. In this article, we propose a novel summarization method that incorporates spatially explicit components into a reinforcement learning framework in order to help summarize geographic knowledge graphs, a topic that has not been considered in previous work. Our model considers the intrinsic graph structure as well as the extrinsic information to gain a more comprehensive and holistic view of the summarization task. By collecting a standard data set and evaluating our proposed models, we demonstrate that the spatially explicit model yields better results than non‐spatial models, thereby demonstrating that spatial is indeed special as far as summarization is concerned.