Spatial analysis of linguistic data with GIS functions

Abstract

During the 1980s techniques for analysis of geographical patterns have been refined to the point that they may be applied to data from many fields. Quantitative spatial analysis and existing functions available in geographical information systems (GIS) enable computerized implementations of these spatial analysis methods. This paper describes the application of quantitative spatial analysis and GIS functions to analysis of language data, using the extensive files of the Linguistic Atlas of the Middle and South Atlantic States (LAMSAS). A brief review of recent development of using quantitative and statistical methods for analysing linguistic data is also included.     

Hillslope-to-valley transition morphology: New opportunities from high resolution DTMs

The search for the optimal spatial scale for observing landforms to understand physical processes is a fundamental issue in geomorphology. Topographic attributes derived from Digital Terrain Models (DTMs) such as slope, curvature and drainage area provide a basis for topographic analyses. The slope–area relationship has been used to distinguish diffusive (hillslope) from linear (valley) processes, and to infer dominant sediment transport processes. In addition, curvature is also useful in distinguishing the dominant landform process. Recent topographic survey techniques such as LiDAR have permitted detailed topographic analysis by providing high-quality DTMs. This study uses LiDAR-derived DTMs with a spatial scale between 1 and 30 m in order to find the optimal scale for observation of dominant landform processes in a headwater basin in the eastern Italian Alps where shallow landsliding and debris flows are dominant. The analysis considered the scaling regimes of local slope versus drainage area, the spatial distribution of curvature, and field observations of channel head locations. The results indicate that: i) hillslope-to-valley transitions in slope–area diagrams become clearer as the DTM grid size decreases due to the better representation of hillslope morphology, and the topographic signature of valley incision by debris flows and landslides is also best displayed with finer DTMs; ii) regarding the channel head distribution in the slope–area diagrams, the scaling regimes of local slope versus drainage area obtained with grid sizes of 1, 3, and 5 m are more consistent with field data; and iii) the use of thresholds of standard deviation of curvature, particularly at the finest grid size, were proven as a useful and objective methodology for recognizing hollows and related channel heads.     

Integrating GIS and spatial data analysis: problems and possibilities

Abstract

This article is an agreed summary of a workshop held in Sheffield between 18-20 March 1991. The focus here is on three of the themes of the workshop: the mutual benefits of closer links between geographical information systems (GIS) and the methods of spatial data analysis (SDA); the specific areas of SDA that should be linked with GIS; how the linkage should be made in practice. Directions for future research are also reviewed. The emphasis throughout is on statistical SDA and principally from the perspective of human rather than physical geography.     

Providing spatial statistical data analysis functionality for the GIS user: the SAGE project

Geographic representation has become more complex through time as researchers have added new concepts, leading to apparently endless proliferation and creating a need for simplification. We show that many of these concepts can be derived from a single foundation that we term the atomic form of geographic information. The familiar concepts of continuous fields and discrete objects can be derived under suitable rules applied to the properties and values of the atomic form. Fields and objects are further integrated through the concept of phase space, and in the form of field objects. A second atomic concept is introduced, termed the geo‐dipole, and shown to provide a foundation for object fields, metamaps, and the association classes of object‐oriented data modelling. Geographic dynamics are synthesized in a three‐dimensional space defined by static or dynamic object shape, the possibility of movement, and the possibility of dynamic internal structure. The atomic form also provides a tentative argument that discrete objects and continuous fields are the only possible bases for geographic representation.     

Municipal GIS and the enterprise data model

Abstract

The City of Scarborough, like many corporations, recently re-evaluated its information technology requirements. The decision was made to model the City's needs in terms of activities and data requirements, concentrating on the Municipal Data Model. First, a two year study was undertaken to understand the business activities of all the disparate components that make up the corporation. This study resulted in individual Information Resource Plans (IRP) for each department. A third year was spent in reconciling the many separate documents and creating a high-level Conceptual Data Model for a Corporate Information System. Of the thirteen broad data groupings, four were assigned to the GIS Group for the design of Detailed Data Models and to populate the resultant databases. The GIS Group, in fact, were to initiate the new Information System for the entire City. The modelling sessions involved hundreds of users from the entire user community in small and large groups, in intensive entity-definition activities, in technical review sessions and in the general examination of context. The detailed models were validated by involving still more users and by testing the model in prototypes, special projects and joint ventures. The GIS Project has demonstrated that data modelling is an effective and realistic method of reflecting the municipality as an enterprise.     

Qualitative GIS and the visualization of narrative activity space data

Qualitative activity space data, i.e. qualitative data associated with the routine locations and activities of individuals, are recognized as increasingly useful by researchers in the social and health sciences for investigating the influence of environment on human behavior. However, there has been little research on techniques for exploring qualitative activity space data. This research illustrates the theoretical principles of combining qualitative and quantitative data and methodologies within the context of geographic information systems (GIS), using visualization as the means of inquiry. Through the use of a prototype implementation of a visualization system for qualitative activity space data and its application in a case study of urban youth we show how these theoretical methodological principles are realized in applied research. The visualization system uses a variety of visual variables to simultaneously depict multiple qualitative and quantitative attributes of individuals' activity spaces. The visualization is applied to explore the activity spaces of a sample of urban youth participating in a study on the geographic and social contexts of adolescent substance use. Examples demonstrate how the visualization can be used to explore individual activity spaces to generate hypotheses, investigate statistical outliers, and explore activity space patterns among subject subgroups.     

Geographical data handling and GIS in China

Abstract

Abstract Chinese governments have long paid a great deal of attention to the collection of geodata, and existing sources have been further enhanced by technological advances, notably in remote sensing. Progress has also been made with automated cartography. An expert working group has been examining GIS and it is recognized that a system combining both national and regional components is most appropriate for China. Three basic functions are envisaged for such GIS: comprehensive regional analysis, prediction of change and the sharing of data. Such systems must serve the needs of users and, in order to demonstrate potential applications, regional experiments are being undertaken, including examples of urban information systems, river basin information systems and specialized systems (e.g. for tourist and forest resources). In the next few years, the emphasis will be on research and on technological preparation for the adoption of GIS, including the use of an experimental set of geographical grid cells. Chinese scholars are also involved in international collaboration in the study of global problems and propose a cooperative programme for a global geographical information system.     

Many sorted algebraic data models for GIS

Although many GIS data models are available, a declarative, operational, well-defined, implementation-independent, and object-oriented language is lacking. Based on the theory of many sorted algebra, this work presents a family of geometric data models. Some geographical data models of urban information systems are illustrated using homomorphism. According to the results, the preferred characteristics of mixing declarative and operational statements, multiple representations, tight interdependency among objects, and integration of vector and raster based systems can be achieved through this mechanism.     

An integration of GIS,virtual reality and the Internet for visualization,analysis and exploration of spatial data

This paper explores the way in which GIS, Virtual Reality (VR) and the Internet are closely integrated through the link of Virtual Reality Modelling Language (VRML) for spatial data visualization, analysis and exploration. Integration takes advantage of each component, and enables the dynamic 3D content to be built, visualized, interacted with and deployed all on the Web. To accomplish this, a hybrid approach that merges the conventional client-side and server-side methods is proposed, which offers the best of both worlds in terms of flexibility and capability, as well as the rational use of computing resources. Based on this approach, a Web-based prototype toolkit is designed and implemented by using an affordable desktop GIS through its macro language together with Java, Common Gateway Interface (CGI) and HTML programming. This toolkit comprises a 3D visualization tool, a 3D analysis tool, and a Java/VRML interface, which are respectively used for the creation of VRML models from 2D maps, surface analysis (e.g. profile creation and visibility analysis), and interaction (e.g. selecting and querying) with the output VRML worlds of 3D visualization and analysis. It is demonstrated that this toolkit provides an integrated environment, facilitating users to gain insights from the interaction with virtual environments that are built from existing GIS databases.     

GIS and spatial analysis in the media

It is not uncommon to see maps and more advanced statistical or spatial analysis reported in the media. Geographical information systems (GIS) have no doubt facilitated access to and analysis of spatial information. This article is the outgrowth of contact by the Boston Globe and subsequent published articles examining structure fires and the location of fire stations in Massachusetts. The questions asked by the Boston Globe are important geographical ones regarding location specific urban/rural service provision issues, and to answer these questions requires the use of spatial analysis. This article focuses on the use of methods for answering the questions raised in the context of applying academic research, an issue that continues to be a challenge.     

A GIS data model for landmark-based pedestrian navigation

Landmarks provide the most predominant navigation cue for pedestrian navigation. Very few navigation data models in the geographical information science and transportation communities support modeling of landmarks and use of landmark-based route instructions for pedestrian navigation services. This article proposes a landmark-based pedestrian navigation data model to fill this gap. This data model can model landmarks in several pedestrian navigation scenarios (buildings, open spaces, multimodal transportation systems, and urban streets). This article implements the proposed model in the ArcGIS software environment and demonstrates two typical pedestrian navigation scenarios: (1) a multimodal pedestrian navigation environment involving bus lines, parks, and indoor spaces and (2) a subway system in a metropolitan environment. These two scenarios illustrate the feasibility of the proposed data model in real-world environments. Further improvements of this model could lead to more intuitive and user-friendly landmark-based pedestrian navigation services than the functions supported by current map-based navigation systems.     

Statistical analysis of drainage density from digital terrain data

Drainage density (D_d), defined as the total length of channels per unit area, is a fundamental property of natural terrain that reflects local climate, relief, geology, and other factors. Accurate measurement of D_d is important for numerous geomorphic and hydrologic applications, yet it is a surprisingly difficult quantity to measure, particularly over large areas. Here, we develop a consistent and efficient method for generating maps of D_d using digital terrain data. The method relies on (i) measuring hillslope flow path distance at every unchanneled site within a basin, and (ii) analyzing this field as a random space function. As a consequence, we measure not only its mean (which is half the inverse of the traditional definition of drainage density) but also its variance, higher moments, and spatial correlation structure. This yields a theoretically sound tool for estimating spatial variability of drainage density. Averaging length-to-channel over an appropriate spatial scale also makes it possible to derive continuous maps of D_d and its spatial variations. We show that the autocorrelation length scale provides a natural and objective choice for spatial averaging. This mapping technique is applied to a region of highly variable D_d in the northern Apennines, Italy. We show that the method is capable of revealing large-scale patterns of variation in D_d that are correlated with lithology and relief. The method provides a new and more general way to quantitatively define and measure D_d, to test geomorphic models, and to incorporate D_d variations into regional-scale hydrologic models.     

Detecting outliers in irregularly distributed spatial data sets by locally adaptive and robust statistical analysis and GIS

In this paper, we propose a new method for detecting outliers in an irregularly distributed spatial data set. Our method has two desirable properties. First, it is functionally effective due to the introduction of sensitive outlier indices and locally adaptive and robust statistical criteria. Second, it is computationally efficient because of the use of super-block based spatial data sorting and searching scheme. Our method has been implemented using the C programming language and integrated with the Arc/Info GIS system. The integration leads to a powerful exploratory data analysis tool for checking and analysing anomalous values in a GIS environment. Local outliers can be automatically labeled with our method, subject to some user-defined parameters. Outliers represent anomalous or suspicious values in a statistical sense, which may not necessarily be erroneous values. Instead of being simply discarded, statistical outliers should be investigated further using prior qualitative knowledge or in association with other GIS data layers.     

面向对象整体GIS数据模型的设计与实现

本文在前期GIS概念数据模型研究的基础上 ,提出了面向对象整体GIS数据模型 ,并针对整体GIS软件的实现在系统数据组织、存储结构与访问机制方面进行了较为深入的探讨 ,Deskpro最后简单介绍了基于整体GIS数据模型的商品化软件———SuperMapDeskpro的实现情况     

Visualizing and quantifying the movement of vegetative drought using remote-sensing data and GIS

Remote-sensing-based drought monitoring methods provide fast and useful information for a sustainable management strategy of drought impact over a region. Common pixel-based monitoring methods are limited in the analysis of the dynamics of this impact at regional scale. For instance, these hardly allow us to quantify the movement of drought in space and time and to compare drought with rainfall deficits without losing the variability of these events within a region. This study proposed an object-based approach that allowed us to visualize and quantify the spatio-temporal movement of drought impact on vegetation, called vegetative drought, in a region. The GIS software Dynomap was used to extract and track objects. Measures of distance and angle were used for determining the speed and direction of vegetative drought and rainfall deficit objects, calculated from the National Oceanic and Atmospheric Administration's (NOAA's) normalized difference vegetation index and rainfall estimates data. The methods were applied to the two rainy seasons during the drought year 1999 in East Africa. Results showed that vegetative drought objects moved into the southwestern direction at an average angle of??138.5° during the first season and??144.5° during the second season. The speed of objects varied between 38 km dekad^?1 and 185 km dekad^?1 during the first season and between 33 km dekad^?1 and 144 km dekad^?1 during the second season, reflecting the rate of spread between dekads. Vegetative drought objects close to rainfall deficit objects showed similar trajectories and sometimes regions overlapped. This indicated that the two events are related. We conclude that a spatiotemporal relationship existed between the two types of events and that this could be quantified.     

GIS analysis of depression among Twitter users

Depression is a common chronic disorder. It often goes undetected due to limited diagnosis methods and brings serious results to public and personal health. Former research detected geographic pattern for depression using questionnaires or self-reported measures of mental health, this may induce same-source bias. Recent studies use social media for depression detection but none of them examines the geographic patterns. In this paper, we apply GIS methods to social media data to provide new perspectives for public health research. We design a procedure to automatically detect depressed users in Twitter and analyze their spatial patterns using GIS technology. This method can improve diagnosis techniques for depression. It is faster at collecting data and more promptly at analyzing and providing results. Also, this method can be expanded to detect other major events in real-time, such as disease outbreaks and earthquakes.     

Spectral analysis of Pennocarboniferous geomagnetic variation data from glacial rhythmites

Summary. Palaeomagnetic results for a sequence of Permocarboniferous rhythmites presented in the previous paper have been submitted to maximum entropy spectral analysis to test whether these palaeomagnetic data could supply information on geomagnetic variations. There is a good correlation between the thickness of the rhythmites and sunspot spectra, suggesting that these sediments are really seasonal. The palaeomagnetic spectra are compared with those of observatory records. Periods of approximately 24.4, 12.4, 8.6, 6.7 and 5.5 found for palaeomagnetic data have corresponding values in the geomagnetic spectrum. Most of these periods, however, are the same as those found in the thickness data, implying that magnetization can be influenced by the sedimentation process as suggested by other investigators. On the other hand, both geomagnetic and climatic (thickness) variations seem to be related to solar activity. Therefore, at least indirectly, palaeomagnetic data may reflect geomagnetic variations.     

Split-Match-Aggregate (SMA) algorithm: integrating sidewalk data with transportation network data in GIS

Sidewalk geodata are essential to understand walking behavior. However, such geodata are scarce, only available at the local jurisdiction and not at the regional level. If they exist, the data are stored in geometric representational formats without network characteristics such as sidewalk connectivity and completeness. This article presents the Split-Match-Aggregate (SMA) algorithm, which automatically conflates sidewalk information from secondary geometric sidewalk data to existing street network data. The algorithm uses three parameters to determine geometric relationships between sidewalk and street segments: the distance between streets and sidewalk segments; the angle between sidewalk and street segments; and the difference between the lengths of matched sidewalk and street segments. The SMA algorithm was applied in urban King County, WA, to 13 jurisdictions’ secondary sidewalk geodata. Parameter values were determined based on agreement rates between results obtained from 72 pre-specified parameter combinations and those of a trained geographic information systems (GIS) analyst using a randomly selected 5% of the 79,928 street segments as a parameter-development sample. The algorithm performed best when the distances between sidewalk and street segments were 12 m or less, their angles were 25° or less, and the tolerance was set to 18 m, showing an excellent agreement rate of 96.5%. The SMA algorithm was applied to classify sidewalks in the entire study area and it successfully updated sidewalk coverage information on the existing regional-level street network data. The algorithm can be applied for conflating attributes between associated, but geometrically misaligned line data sets in GIS.     

Human geography and its relationship to GIS: a perspective from the vantage point of GIS

Concern abounds over what is a never ending sequence of paradigm shifts within human geography. One result is the marginalisation of previous work. Considerable concern has been expressed among those working with geographical information systems (GIS) over the relationship of this area of work to human geography. Behind much of this turmoil is the ascendancy of post‐modernism, an approach with which many human geographers are unable to actively engage in debate. At a time when the other social sciences are incorporating space into their research, human geography and GIS are parting company with the two facing very different futures.