Showing papers on "Spatial analysis published in 1980"

Linear Models with Spatially Distributed Data: Spatial Disturbances or Spatial Effects?

Abstract: This article deals with linear models for which data have been aggregated over well-defined geographic areas. Such data may be generated by spatial processes, and these may be represented in the fo...

Spatial management of data

Abstract: Spatial data management is a technique for organizing and retrieving information by positioning it in a graphical data space (GDS). This graphical data space is viewed through a color raster-scan display which enables users to traverse the GDS surface or zoom into the image to obtain greater detail. In contrast to conventional database management systems, in which users access data by asking questions in a formal query language, a spatial data management system (SDMS) presents the information graphically in a form that seems to encourage browsing and to require less prior knowledge of the contents and organization of the database.This paper presents an overview of the SDMS concept and describes its implementation in a prototype system for retrieving information from both a symbolic database management system and an optical videodisk.

Extensions of linear discriminant analysis for statistical classification of remotely sensed satellite imagery

Abstract: Linear discriminant analysis is a commonly used statistical tool for the classification of surface features using satellite surface reflectance data. Extensions of this basic tool promise substantial improvements. In particular, we examine the added effectiveness of the integration of spatial autocorrelation into the discriminant model, the resolution of nonhomogeneous pixels, and data based prior probability estimates of class membership.

A prototype Spatial Data Management System

Abstract: Spatial Data Management is a technique for organizing and retrieving information by positioning it in a spatial framework. Data is accessed in a Spatial Data Management System (SDMS) via pictorial representations which are arranged in space and viewed through a computer graphics system. These pictures can be created by an interactive graphical editor, allowing an SDMS to serve as a personal repository of diagrams, text, and photographs. Pictograms can also be generated from data in a symbolic database management system, allowing SDMS to be used as an interface to large, shared databases.A prototype SDMS has been constructed which employs a set of color, raster scan displays driven by a large minicomputer. The user can create and examine data surfaces which are larger than the display screen, traversing a surface and zooming in and out to control the level of detail displayed. The prototype system provides a uniform mechanism for accessing a wide variety of data types in a manner which does not require the use of a formal command or query language.

Spatial bias in Australian news reporting

Abstract: Summary Although the mass media in Australia have attracted a good deal of academic comment, their significance as sources of spatial information has scarcely been examined despite the fact that the ‘agenda setting’ approach to the study of media impact affords a practical method of assessing how media content may contribute to spatial awareness. News reports constitute a major source of spatial information and, accordingly, a content analysis of New South Wales press, radio, and television is undertaken to show the extent of spatial bias in news coverage and hence the highly constrained ‘agendas’ that are set before the public.

A spatial data structure for geographic information systems

Abstract: In this chapter we describe a data structure that is equally natural for spatial data in the raster run length format and the vector format. This makes it easier to design a geographic information system that handles both data formats and that optimizes for itself whether any particular data set is in raster or vector format. This same data format is appropriate for intelligent query and inference uses as described in Shapiro's chapter of this book. Brief mention is made of the topological consistency requirements for each data format. A bibliography of many of the fast algorithms for vector format data is provided at the end of the paper.

Geographic Information Systems

Abstract: The impetus for the development of GIS technologies is derived primarily from the fact that traditional manual techniques for the derivation, organization, storage and use of spatial data are no longer sufficient to meet the demands and expectations placed on such activities. The GIS technology is a service technology used to assist spatial data management, evaluations and analyses. There are three basic approaches currently developed that organize spatial data in a format such that the computer can perform previously time-consuming analytical and display processes. These are: (1)the rectangular grid approach; (2)the fine or coarse polygon approach; and (3)the triangulated irregular network approach. There is a wide range of applications that can be supported by GIS. These can be reasonably divided into two groups: those that depend on qualitative analysis and those that depend on quantitative analysis. The GIS design requirements are much more demanding to support quantitative analyses.

Spatial data integration

Abstract: Spatial data integration is defined as the process of combining multiple spatial data types and providing for their storage, retrieval, analysis, and display Automated procedures to support data integration are related to spatial data characteristics, software features, and hardware capabilities Spatial data integration issues associated with data characteristics are discussed as discipline issues; software and hardware features are referred to as automated data processing issues Spatial data integration concepts, issues and research are reviewed

Methodological observations on the state of geocartographic analysis in the context of automated spatial information systems

Abstract: Publisher Summary This chapter defines cartography and highlights the contribution of the computer to automated cartography. The chapter describes the major data problems, which form a bottleneck in automated geocartographic analysis, and discusses those aspects with respect to problems related to automated spatial information systems. An automated spatial information system is a dynamically updatable body of data, interfaced with a body of models programmed for a computer transformation of these data into spatial information, to satisfy specific needs of defined users within the framework of well-defined concepts and technology. The various problems discussed in the chapter, all relating to geocartographic spatial analysis, relate to it in a variety of different levels. Problems of all levels converge at the spatial information system level, for it contains all the way from data to its analysis in both hardware and software matters.

A Geographical Evaluation of Cliff and Ord’s Spatial Autocorrelation Technique

Abstract: Spatial autocorrelation is a technique designed to measure spatial covariance between neighbouring values on a two-dimensional surface. Hypothetical surfaces used in this paper are point patterns that are subdivided according to a regular grid matrix, thus providing a measurable value for each subarea or grid square. It is shown that although the shape and size of the subareas is constant the coefficient does vary according to the number of grid squares, and consequently the number of joins in the system. The coefficient also varies according to changes in the directional orientation of the grid matrix, and the location and number of non-content or blank grid squares inside the matrix.