A Meta‐Analysis on the Return on Investment of Geospatial Data and Systems: A Multi‐Country Perspective

The availability, quality and accessibility of Geographic Information (GI) have significant socio‐economic and environmental benefits, but the collection and maintenance of GI require substantial investments. Cost‐benefit assessments (CBAs) attempt to justify the costs of geospatial data investments, applying different methodologies and focusing on diverse areas. Therefore, the Returns on Investment (ROI) vary considerably across studies, regions and sectors. The objective of this study is to explain some of the variation in the average ROI of GI by conducting a meta‐analysis of 82 cost‐benefit assessments between 1994 and 2013. In a first step, CBAs are systematically reviewed and relevant information is extracted. Particular emphasis is given to investment conditions and study characteristics. In a second step, multivariate regression methods are used to assess the size, significance and direction of individual effects. The results suggest that regional factors have the largest impact on the profitability of GI. Returns in Australia and New Zealand, for example, are four times larger than in Europe. In addition, small‐scale regional investments have a 2.5 times lower return than large‐scale international investments. Overall, the expected benefits of GI investments are approximately 3.2 times larger than the costs.     

空间数据挖掘和知识发现与地理可视化的集成

论述空间数据挖掘和知识发现以及地理可视化的理论及特点,指出二者集成的可能性和必然性,并在此基础上介绍一种集成方法.     

The Development of a Web‐based Demographic Data Extraction Tool for Population Monitoring

The Internet contains a great wealth of information available online. People search engines, such as WhitePages ( http://www.whitepages.com ), gather personal‐level demographic data, including full name, address, age and household members. Requiring only a surname and locational reference (e.g. city or postal code) as the minimum search criteria, such people search engines can be perceived as a gigantic database of demographic records. The objective of this article is to outline the development of a web‐based demographic data extraction tool for population monitoring. In this study, a web prototype was developed to extract web demographics of the Vietnamese‐American (VA) population in Texas, an ethnic minority with unique migration history, from WhitePages. After post‐processing, the personal‐level demographic data represent 40.3% of 202,003 VA in Texas reported by the American Community Survey (ACS) 2009. While all enumeration strategies, the web approach included, have their own strengths and weaknesses, this study suggests an alternative approach that is complementary to existing enumeration strategies. More research and development are needed to validate the accuracy of web demographics and further enhance data navigation and extraction rules. The utilization and release of web demographics must be cautious with regards to privacy and integrity of personal identity.     

Weka‐STPM: a Software Architecture and Prototype for Semantic Trajectory Data Mining and Visualization

Enormous quantities of trajectory data are collected from many sources, such as GPS devices and mobile phones, as sequences of spatio‐temporal points. These data can be used in many application domains such as traffic management, urban planning, tourism, bird migration, and so on. Raw trajectory data, as generated by mobile devices have very little or no semantics, and in most applications a higher level of abstraction is needed to exploit these data for decision making. Although several different methods have been proposed so far for trajectory querying and mining, there are no software tools to help the end user with semantic trajectory data analysis. In this article we present a software architecture for semantic trajectory data mining as well as the first software prototype to enrich trajectory data with both semantic information and data mining. As a prototype we extend the Weka data mining toolkit with the module Weka‐STPM, which is interoperable with databases constructed under OGC specifications. We tested Weka‐STPM with real geographic databases, and trajectory data stored under the Postgresql/PostGIS DBMS.     

A GIS Framework for Spatio-temporal Analysis and Visualization of Laboratory Mice Tracking Data

Knowing the locations and spatio‐temporal paths of individual mice is an essential prerequisite for behavioral analysis of large groups of laboratory mice. Traditional observations have been carried out by trained humans who are able to distinguish more than fifty behavioral patterns. This is a tedious labor limited with respect to length of observation time. In this paper we propose a tracking solution based on the integration of GIS and RFID (Radio Frequency Identification) technology to automatically collect 24h/7days of movement data. Appropriate cage design and antenna placement are discussed. A software solution is presented to facilitate the recording (JerryTS), visualization, and analysis (TOM) of mice movements.     

Automated Digital Photogrammetry: A Valuable Tool for Small‐scale Geomorphological Research for the Non‐photogrammetrist?

Digital photogrammetry provides a tool with which to automatically generate digital elevation models (DEMs). The necessary equipment is now both readily available and affordable: thus there is considerable potential for this technique to be widely adopted in geomorphological studies. But is it possible for geomorphologists without a background in photogrammety to use it successfully? As part of a larger study into rill initiation by overland flow, a non‐metric digital camera and ERDAS IMAGINE OrthoMAX software were used to generate small‐scale DEMs of soil surface microtopography. This paper reports on the procedure used, highlights potential pitfalls, and comments on the quality of the resultant DEMs. Whilst acquisition of high‐quality images using a digital camera is relatively straightforward, problems were subsequently encountered due to the small size of the internal imager and the need for camera calibration. Potential stumbling blocks in the use of the software lay in the setting‐up of ground control points and the use of tie‐points and check‐points, as well as several software glitches not identified in the current manual. Nonetheless, once these problems were overcome the technique proved to be a simple, effective and fast tool for generating high quality microtopographical DEMs. This methodology shows great promise for future geomorphological studies that require these kinds of surface data.     

大尺度多源空间数据可视化与分析组件的设计与实现

采用金字塔多级索引等关键技术,按照COM标准设计并实现了四层结构的大尺度海量地理数据处理与分析组件,且具备对多源空间数据的综合管理与分析功能.通过"中国海区遥感仿真、反演及验证信息系统"试验,表明该组件不仅能够在空间延展度上直观地反映地形地貌的要素特征,而且其完备的地学分析功能能为决策科学化、应急响应快速化、信息服务社...     

GML数据的Web可视化设计与实现

GML是GIS领域的通用交流语言,然而目前的浏览器并不支持GML,因此GML的Web可视化仍是GML应用需要解决的问题。为此,本论文提出了一种基于组件的可视化策略。该策略采用文档对象模型(DOM)进行GML模式文件和实例文件解析,按地理要素对GML进行数据分流/分层,然后分层可视化的办法,实现了GML数据的Web可视化。实践验证,该方法是切实可行的,且对于GML数据量较大时尤为有效。     

疾病数据的时空聚集分析及可视化

GIS应用在疾病领域方面发展迅速,为其提供可靠的空间统计分析方法,其疾病制图实现了疾病数据的可视化。本文以肺结核数据为例,进行了空间聚集分析、时间序列分析及时空扫描统计分析,分析疾病的时空聚集状态,寻找高发病率区域,分析结果可为医疗卫生部门在疾病监测预警、资源分配等方面提供科学参考。     

Geo‐questionnaire: A Method and Tool for Public Preference Elicitation in Land Use Planning

Geo‐questionnaire involves an integration of sketchable maps with questions, aimed at eliciting public preferences and attitudes about land allocation and services. Respondents can link their answers with corresponding locations on a map by marking points or sketching polygon features. Geo‐questionnaires have been used to learn about perceptions and preferences of city residents for specific types of land use, place‐based services, and development projects. This article reports on results of an empirical study, in which an online geo‐questionnaire was designed and implemented to elicit preferences of residents in guiding an urban development plan. Preferences collected in the form of polygon sketches were processed using GIS operations and mapped for visual interpretation. The article focuses on aggregation and analysis of respondent preferences including the analysis of positional and attribute uncertainty. Results of the study show that geo‐questionnaire is a scalable method for eliciting public preferences with a potential for meaningfully informing land use planning.     

全空间时空对象可视化工具的设计与实现

在全空间信息系统中,多粒度时空对象及其时空域的组织方式,本身并没有对对象进行专门的可视化处理.对象的全特征、复杂关联与多维动态特点客观上造成了用户理解和认知数据的困难,需要专门的可视化工具,对对象的特征信息进行可视化检查与交互探索,一方面可以向下验证全空间信息系统建模理论,融合多粒度时空对象一体化管理技术;另一方面可以...     

利用MODIS温度产品进行秩修正滤波FRF时空插值

普通克里金方法具有空间结构探索及插值分析（给出插值结果及其精度）的功能。但是,绝大部分的克里金方法主要用于空间插值,在时空插值方面的研究还较少。综合考虑具体的实验区域和观测数据构建基函数,使用秩修正滤波（fixed rank filtering,FRF）方法对MODIS平流层温度数据进行时空插值预测并将其结果与秩修正克里金（Fixed rank Kriging,FRK）方法的插值结果进行对比分析。实验结果表明,在空间数据（空间点）整体分布均匀且有已知点的情况下,FRK方法预测的数据精度更高,略优于FRF;而对于较大空间范围内缺失数据的情况,考虑温度在时间维上具有一定的相关性,FRF方法在缺失空间信息时能够引入更多时空信息从而获得较其他方法更高质量的插值结果。     

An Event‐driven Spatiotemporal Data Model (E‐ST) Supporting Dynamic Expression and Simulation of Geographic Processes

The wide use of various sensors makes real‐time data acquisition possible. A new spatiotemporal data model, the Event‐driven Spatiotemporal Data Model (E‐ST), is proposed to dynamically express and simulate the spatiotemporal processes of geographic phenomena. In E‐ST, a sensor object is introduced into the model as a flexible real‐time data source. An event type that is generating and driving conditions is registered into a geographic object, so an event can not only express spatiotemporal change in a geographic object, but also drive spatiotemporal change in some geographic objects. As a dynamic GIS data model, the E‐ST has five characteristics – Temporality and Spatiality, Real‐time, Extendability, Causality, and Realizability. Described and realized in UML, a test‐case deployment demonstrating the impact of urban waterlogging on traffic confirms that a spatiotemporal change process in a geographic phenomena is expressed and simulated by this model. Summarizing this work, four directions for future research are outlined.     

The application of the Intermittent SBAS (ISBAS) InSAR method to the South Wales Coalfield,UK

Satellite radar interferometry is a well-documented technique for the characterisation of ground motions over large spatial areas. However, the measurement density is often constrained by the land use, with best results obtained over urban and semi urban areas. We use an implementation of the Small Baseline Subset (SBAS) methodology, whereby areas exhibiting intermittent coherence are considered alongside those displaying full coherence, in the final result, to characterise the ground motion over the South Wales Coalfield, United Kingdom. 55 ERS-1/2 Synthetic Aperture Radar (SAR) C-band images for the period between 1992 and 1999 are processed using the ISBAS (Intermittent Small BAseline Subset) technique, which provides 3.4 times more targets, with associated measurements than a standard SBAS implementation. The dominant feature of the observed motions is a relatively large spatial area of uplift. Uplift rates are as much as 1 cm/yr. and are centred on the part of the coalfield which was most recently exploited. Geological interpretation reveals that this uplift is most likely a result of mine water rebound. Collieries in this part of the coalfield required a ground water to be pumped to enable safe coal extraction; following their closure pumping activity ceased allowing the water levels to return to equilibrium. The ISBAS technique offers significant improvements in measurement density ensuring an increase in detection of surface motions and enabling easier interpretation.     

The Spatial Data Transfer Standard (FIPS 173): A Management Perspective

The Spatial Data Transfer Standard (SDTS) was approved by the Department of Commerce as Federal Information Processing Standard (FIPS) 173 on July 29, 1992. As a FIPS, the SDTS will serve as the national spatial data transfer mechanism for all federal agencies and will be available for use by state and local governments, the private sector, and research organizations. FIPS 173 will transfer digital spatial data sets between different computer systems, making data sharing practicable. This standard is of significant interest to users and producers of digital spatial data because of the potential for increased access to and sharing of spatial data, the reduction of information loss in data exchange, the elimination of the duplication of data acquisition, and the increase in the quality and integrity of spatial data. The success of FIPS 173 will depend on its acceptance by users of spatial data and by vendors of spatial information systems. Comprehensive workshops are being conducted, and the tools and procedures necessary to support FIPS 173 implementations are being developed. The U.S. Geological Survey, as the FIPS 173 maintenance authority, is committed to involving the spatial data community in various activities to promote acceptance of FIPS 173 and to providing case examples of prototype FIPS 173 implementations. Only by participating in these activities will the members of the spatial data community understand the role and impact of this standard.     

SCOPED‐W: SCalable Online Platform for extracting Environmental Data and Water‐related model outputs

This article presents SCOPED, an innovative approach for extracting environmental data using OGC services. In the field of water resource management, SCOPED‐W (‘W’ for ‘Water’) is a method that was developed in the framework of EU/FP7 IASON and EOPOWER projects. This platform supports the collection of data required to build a Soil and Water Assessment Tool (SWAT) model and the uptake, spatialization and dissemination of raw data generated from the outputs of different SWAT models for the Black Sea region. Scientists are documenting the data served by the platform in ISO standardized metadata to support informed use. SCOPED‐W primarily targets the community of SWAT users in the Black Sea region but it can easily be replicated in other geographical areas. Additionally, the SCOPED approach is based on data interoperability that makes it fully compatible with other domains of application as demonstrated here with three original use cases. The article also highlights the benefits of the approach for the GEO community and discusses future improvements for supporting integration with other platforms such as UNEP Live.     

A Space‐Time Raster GIS Data Model for Spatiotemporal Analysis of Vegetation Responses to a Freeze Event

Many past space‐time GIS data models viewed the world mainly from a spatial perspective. They attached a time stamp to each state of an entity or the entire area of study. This approach is less efficient for certain spatio‐temporal analyses that focus on how locations change over time, which require researchers to view each location from a temporal perspective. In this article, we present a data model to organize multi‐temporal remote sensing datasets and track their changes at the individual pixel level. This data model can also integrate raster datasets from heterogeneous sources under a unified framework. The proposed data model consists of several object classes under a hierarchical structure. Each object class is associated with specific properties and behaviors to facilitate efficient spatio‐temporal analyses. We apply this data model to a case study of analyzing the impact of the 2007 freeze in Knoxville, Tennessee. The characteristics of different vegetation clusters before, during, and after the 2007 freeze event are compared. Our findings indicate that the majority of the study area is impacted by this freeze event, and different vegetation types show different response patterns to this freeze.     

Knowledge Discovery in the Environmental Sciences: Visual and Automatic Data Mining for Radon Problems in Groundwater

Efficiently exploring a large dataset with the aim of forming a hypothesis is one of the main challenges in environmental research. The exploration of georeferenced environmental data is usually performed by established statistical methods. This paper presents an alternative approach. The aim of this study was to see if a visual data mining system and an integrated visual‐automatic data mining system could be used for data exploration for a particular environmental problem: the occurrence of radon in groundwater. In order to demonstrate this, two data mining systems were built, one consisting of visualisations and the other including an automatic data mining method – a Self‐Organising Map (SOM). The systems were designed for exploration of a large multidimensional dataset representing wells in Stockholm County.