Location Intelligence: An Innovative Approach to Business Location Decision‐making

As one of the leading ‘world cities’, London is particularly reliant on sources of foreign direct investment (FDI). In the face of increasing global competition and a difficult economic climate, the capital must compete effectively to encourage and support such investors. Through a collaborative study with London's official FDI promotion agency, Think London, the need for a coherent framework for data, methodologies and tools to inform business location decision‐making became apparent. This article discusses the development of a rich environment to explore, compare and rank London's business neighbourhoods. This is achieved through the development and evaluation of a model for location‐based decision support. First, we discuss the development of a geo‐business classification for London which draws upon methods and practices common in geodemographic neighbourhood classification. A geo‐business classification is developed, encapsulating relevant location variables using Principal Components Analysis into a set of composite area profiles. Second, we discuss the implementation of an appropriate Multi‐Criteria Decision Making methodology, in this case Analytical Hierarchy Process (AHP), enabling the aggregation of the geo‐business classification and decision‐makers' preferences into discrete decision alternatives. Finally, we present the results of the integration of both data and model through the development and evaluation of a web‐based prototype.     

运用GIS进行空间选址分析

现代物流等应用空间选址的行业在国民经济生活中的重要性日渐凸现,GIS以其强大的数据管理功能、查询分析功能和数据显示功能,在空间选址的应用中具有无法比拟的优势。文章分析了利用GIS进行空间选址的优点,阐述了GIS对空间选址的支持作用,并且对空间选址的方法进行了具体分析。     

Street‐segment‐based salt and abrasive prediction for winter maintenance using machine learning and GIS

Salting operations are essential but expensive in northern winters. We aim to predict the quantity of salt and abrasive needed for a specific road segment for each hour. An estimate of the quantity allows managers to better manage the loads in the trucks and to propose optimal vehicle routes based on the forecast, which will allow them to optimize costs. This article uses machine‐learning techniques based on truck telemetry data, weather conditions, and segment attributes. Geographic information systems (GIS) allow us to exploit the street‐network characteristics, which were ignored by previous prediction models. The results show that the XGBoost method performs better than other techniques (R² = 0.83).     

Using GIS and K = 3 Central Place Lattices for Efficient Solutions to the Location Set‐Covering Problem in a Bounded Plane

One of the simplest location models in terms of its constraint structure in location‐allocation modeling is the location set‐covering problem (LSCP). Although there have been a variety of geographic applications of the set‐covering problem (SCP), the use of the SCP as a facility location model is one of the most common. In the early applications of the LSCP, both potential facility sites as well as demand were represented by points discretely located in geographic space. The advent of geographic information systems (GIS), however, has made possible a greater range of object representations that can reduce representation error. The purpose of this article is to outline a methodology using GIS and K = 3 central place lattices to solve the LSCP when demand is continuously distributed over a bounded area and potential facility sites have not been defined a priori. Although, demand is assumed to exist over an area, it is shown how area coverage can be accomplished by the coverage of a point pattern. Potential facility site distributions based on spacings that are powers of one‐third the coverage distance are also shown to provide more efficient coverage than arbitrarily chosen spacings. Using GIS to make interactive adjustments to an incomplete coverage also provides an efficient alternative to smaller spacings between potential facility sites for reducing the number of facilities necessary for complete coverage.     

Appreciative GIS and Strength‐Based Community Change

Problem‐solving is embedded deeply in the digital DNA of GIS. Most projects involving GIS 1.0 and 2.0 raise community weaknesses, failures and other problems and use them to motivate change. The projects often create a future that does not differ greatly from the past or last long. Although looking into community problems is important and sometimes necessary, the steps of problem‐solving do not always leave people feeling happy. To inspire communities to create change based on their strengths and achievements, and to provide better participant experience, this article develops the concept of a new form of GIS called Appreciative GIS (AGIS). AGIS are grounded in the affirmative premise that every community, however challenged, is gifted with certain assets, potentials and strengths which, when effectively exploited, can take that community to a better and sustainable future. Based on Earth's internal structure, the article develops a useful layered community model where crust, mantle and core strata represent the community's body, life‐draining and life‐giving elements in that order. The model helps explain the different views of the community from current GIS and AGIS perspectives. A Total GIS (TGIS) cube is also developed and used to indicate that current GIS commonly focus on elements of the mantle or what we do not have, what we cannot do and what makes us weak. AGIS, on the other hand, dig up the core and cultivate what we have, what we can possibly do and what makes us strong. In a significant departure from the linear approach of problem‐solving, the article suggests implementing AGIS through a 7G cyclical method. The article contends that although AGIS may not be the whole enchilada, they can serve as a beacon of hope and a powerful source of inspiration especially for individuals and groups who are perceived or made to perceive themselves as dysfunctional, weak or poor.     

GIS与GPS管道特征定位应用

输送石油和天然气的管道多埋在地下,免于受地面上人、动物的破坏.地下管道特征的定位,如焊缝、阀门、缺陷、异常等,传统方法主要采用扯皮尺和PCM探测,这种方法受地形和建筑设施的影响很大,如果地面参照物破坏,找到特征比较费时,准确性差.目前的GIS和GPS技术,可避免这些缺点,通过GIS将各种管道数据整合到一起,获取管道特征...     

GIS本科多层次技能影响因素及其培养课程体系研究

分析GIS专业人才技能培养与课程体系问题,总结出GIS专业技能具有入门级、专业级、扩展级和创新级4个层次,对满足社会多样化人才需求具有很好的适应性。通过系列教改课题研究,设计并落实了与GIS层次化技能培养相适应的课程体系。     

A GIS Toolbox for Measuring and Mapping Person‐Based Space‐Time Accessibility

This article presents a toolbox to compute and map person‐based accessibility indicators, based on classical time geography concepts. The intent is to provide GIS and urban planning practitioners with a user‐friendly and easily customizable tool. While it relies on well‐known concepts, the toolbox implements a major innovation in person‐based accessibility assessment by taking into account opening hours when measuring the accessibility of urban facilities. The toolbox can be downloaded from http://bit.ly/1h6yg5Z .     

基于GIS和AHP的疏散地域选址

人员疏散是战时减少人员伤亡的有效手段,疏散地域又是人员疏散的基础.做好疏散地域选址分析对人员疏散体系建设具有十分重要的意义.对影响疏散地域选址的因素进行了归类和分析;基于GIS和层次分析法建立了一个疏散地域选址模型,并对模型进行了实例应用.该模型的实现大大降低了人为因素对疏散地域选址的影响,增强了疏散地域选址的科学性和...     

StarBorn: Towards making in‐situ land cover data generation fun with a location‐based game

Data contributed by a large number of non‐experts is increasingly used to validate and curate land cover data, with location‐based games (LBGs) developed for this purpose generating particular interest. We here present our findings on StarBorn, a novel LBG with a strong focus on game play. Users conquer game‐tiles by visiting real‐world locations and collecting land cover data. Within three months, StarBorn generated 13,319 land cover classifications by 84 users. Results show that data are concentrated around users’ daily life spaces, agreement among users is highest for urban and industry land cover, and user‐generated land cover classifications exhibit high agreement with an authoritative data set. However, we also observe low user retention rates and negative correlations between number of contributions and agreement rates with an authoritative land cover product. We recommend that future work consider not only game play, but also how motivational aspects influence behavior and data quality. We conclude that LBGs are suitable tools for generating cost‐efficient in‐situ land cover classifications.     

GIS和免疫算法的垃圾楼选址优化

针对现有城市公共设施选址模型较少考虑具体城市特色和服务设施运行现状这一问题,该文提出基于地理信息系统(GIS)空间分析、改进潜能模型和免疫算法相结合的方法,在评估研究区垃圾楼可达性的基础上,利用GIS空间分析进行初步优化,并构建双目标免疫优化模型再次优化.研究表明:西城区7个街道之间可达性空间差异较大,可达性较好的区域分布在研究区中下部;现有垃圾楼数量不能满足居民需求,拟在可达性较差区域增加9座垃圾楼;经两步优化后,在原有垃圾楼布局不变前提下,研究区居民点平均可达性提高34.50％,7个街道平均可达性标准差下降了 58.18％,表明该方法在提高垃圾楼整体可达性的同时也促进其空间布局的均衡化.     

A multi‐criteria decision‐making approach for geometric matching of areal objects

We propose a method for geometric areal object matching based on multi‐criteria decision making. To enable this method, we focused on determining the matched areal object pairs that have all relations, one‐to‐one relationships to many‐to‐many relationships, in different spatial data sets by fusing geometric criteria without user invention. First, we identified candidate corresponding areal object pairs with a graph‐based approach in training data. Second, three matching criteria (areal hausdorff distance, intersection ratio, and turning function distance) were calculated in candidate corresponding pairs and these criteria were normalized. Third, the shape similarity was calculated by weighted linear combination using the normalized matching criteria (similarities) with the criteria importance through intercriteria correlation method. Fourth, a threshold (0.738) of the shape similarity estimated in the plot of precision versus recall versus all possible thresholds of training data was applied, and the matched pairs were determined and identified. Finally, we visually validated the detection of similar areal feature pairs and conducted statistical evaluation using precision, recall, and F‐measure values from a confusion matrix. Their values were 0.905, 0.848, and 0.876, respectively. These results validate that the proposed classifier, which detects 87.6% of matched areal pairs, is highly accurate.     

Modeling and Communicating the Conceptual Intent of Geo‐Analytical Tasks for Human‐GIS Interaction

One of the fundamental issues of geographical information science is to design GIS interfaces and functionalities in a way that is easy to understand, teach, and use. Unfortunately, current geographical information systems (including ArcGIS) remains very difficult to use as spatial analysis tools, because they organize and expose functionalities according to GIS data structures and processing algorithms. As a result, GIS interfaces are conceptually confusing, cognitively complex, and semantically disconnected from the way human reason about spatial analytical activities. In this article, we propose an approach that structures GIS analytical functions based on the notion of “analytical intent”. We describe an experiment that replaces ArcGIS desktop interface with a conversational interface, to enable mixed‐initiative user‐system interactions at the level of analytical intentions. We initially focus on the subset of GIS functions that are relevant to “finding what's inside” as described by Mitchell, but the general principles apply to other types of spatial analysis. This work demonstrates the feasibility of delegating some spatial thinking tasks to computational agents, and also raises future research questions that are key to building a better theory of spatial thinking with GIS.     

Dracunculiasis,Proximity, and Risk: Analyzing the Location of Guinea Worm Disease in a GIS

Dracunculus medinesis is a waterborne parasite that has afflicted human populations for millennia. It is spread to new water bodies by the travel activities of the humans it affects. This study analyzes the relationship between Guinea worm incidence and its proximity to features of the built and natural environment to identify any apparent relationships. The study examines the Tillabéri region in the country Niger where there was a reemergence in the number of cases of Guinea worm in 2003. It is found that population centers with Guinea worm infected individuals are often within two kilometers of nomadic herding routes.     

Runoff modelling of a small watershed using satellite data and GIS

This study was conducted for the Nagwan watershed of the Damodar Valley Corporation (DVC), Hazaribagh, Bihar, India. Geographic Information System (GIS) was used to extract the hydrological parameters of the watershed from the remote sensing and field data. The Digital Elevation Model (DEM) was prepared using contour map (Survey of India, 1:50000 scale) of the watershed. The EASI/PACE GIS software was used to extract the topographic features and to delineate watershed and overland flow-paths from the DEM. Land use classification were generated from data of Indian Remote Sensing Satellite (IRS-1B—LISS—II) to compute runoff Curve Number (CN). Data extracted from contour map, soil map and satellite imagery, viz. drainage basin area, basin shape, average slope of the watershed, main stream channel slope, land use, hydrological soil groups and CN were used for developing an empirical model for surface runoff prediction. It was found that the model can predict runoff reasonably well and is well suited for the Nagwan watershed. Design of conservation structures can be done and their effects on direct runoff can be evaluated using the model. In broader sense it could be concluded that model can be applied for estimating runoff and evaluating its effect on structures of the Nagwan watershed.     

Loose programming of GIS workflows with geo‐analytical concepts

Loose programming enables analysts to program with concepts instead of procedural code. Data transformations are left underspecified, leaving out procedural details and exploiting knowledge about the applicability of functions to data types. To synthesize workflows of high quality for a geo‐analytical task, the semantic type system needs to reflect knowledge of geographic information systems (GIS) at a level that is deep enough to capture geo‐analytical concepts and intentions, yet shallow enough to generalize over GIS implementations. Recently, core concepts of spatial information and related geo‐analytical concepts were proposed as a way to add the required abstraction level to current geodata models. The core concept data types (CCD) ontology is a semantic type system that can be used to constrain GIS functions for workflow synthesis. However, to date, it is unknown what gain in precision and workflow quality can be expected. In this article we synthesize workflows by annotating GIS tools with these types, specifying a range of common analytical tasks taken from an urban livability scenario. We measure the quality of automatically synthesized workflows against a benchmark generated from common data types. Results show that CCD concepts significantly improve the precision of workflow synthesis.     

Student Learning in an Introductory GIS Course: Using a Project‐Based Approach

Introductory courses in Geographic Information Science (GIS) expose students to the concepts and practices necessary for future academic and professional use of GIS tools. Traditional GIS courses balance lectures in the theories of GIS with pre‐built and pre‐packaged lab activities to learn the practices of GIS. This article presents a case study of an experimental introductory course in which students conducted novel, independent project‐based group research under the supervision of graduate or advanced undergraduate students enrolled in the course, culminating in a class presentation and publication quality paper. Surveys and interviews indicated that students reacted more positively to project‐based group research than to traditional activities. Students felt the projects better prepared them for ‘real world’ applications of GIS, and recommend project‐based group research in other GIS coursework. Additionally, our findings indicate that students appreciate interactions with peers of varying skill levels and experiences, as these broaden their capabilities to work with other GIS users.     

GIS与模糊数学理论在商服中心空间选址中的应用

城市商服中心空间位置选择的好坏,直接关系到商服中心能否最大限度的发挥其效用和实现其自身的利益或价值。在利用城市地理信息系统,获取若干可行商服中心地址样本的基础上,采用特尔菲法确定影响选址的因素和它们的权重,并采用贴近度的方法比较被选地址与理想目标的接近程度,由此来确定备选地址的优劣次序,选择最佳的地址。     

Exploring Mobility Indoors: an Application of Sensor‐based and GIS Systems

The popularization of tracking devices, such as GPS, accelerometers and smartphones, have made it possible to detect, record, and analyze new patterns of human movement and behavior. However, employing GPS alone for indoor localization is not always possible due to the system's inability to determine location inside buildings or in places of signal occlusion. In this context, the application of local wireless networks for determining position is a promising alternative solution, although they still suffer from a number of limitations due to energy and IT‐resources. Our research outlines the potential for employing indoor wireless network positioning and sensor‐based systems to improve the collection of tracking data indoors. By applying various methods of GIScience we developed a methodology that can be applicable for diverse human indoor mobility analysis. To show the advantage of the proposed method, we present the result of an experiment that included mobility analysis of 37 participants. We tracked their movements on a university campus over the course of 41 days and demonstrated that their movement behavior can be successfully studied with our proposed method.     

浅谈京石高速铁路工程的测绘工作

高速铁路是指通过改造原有线路(直线化、轨距标准化),使营运速率达到每小时200公里以上,或者专门修建新的"高速新线",使营运速率达到每小时250公里以上的铁路系统。"十二五"期间,我国大力加强高速铁路交通的建设力度,使得高速铁路在国民经济建设中的地位日益增加。结合近几年承接的高速铁路轨道交通的测绘工作,以京石高速铁路北京段14～48千米拨地的实际工作情况来谈谈在建设高速铁路过程中的测绘工作的应用,简单介绍作业方法、基本流程、质量控制措施以及经验和心得体会。