Showing papers on "Spatial analysis published in 1990"

Spatial Data Analysis in the Social and Environmental Sciences

Abstract: 1. Introduction 2. Issues in analysing spatial data 3. Statistical models for spatial populations 4. Statistical analysis of spatial populations 5. Sampling spatial populations 6. Preliminary analysis of spatial data 7. Analysing univariate data sets 8. Analysing multivariate data sets Postscript Glossary References Index.

Estimating uncertain spatial relationships in robotics

Abstract: In this paper, we describe a representation for spatial information, called the stochastic map, and associated procedures for building it, reading information from it, and revising it incrementally as new information is obtained. The map contains the estimates of relationships among objects in the map, and their uncertainties, given all the available information. The procedures provide a general solution to the problem of estimating uncertain relative spatial relationships. The estimates are probabilistic in nature, an advance over the previous, very conservative, worst-case approaches to the problem. Finally, the procedures are developed in the context of state-estimation and filtering theory, which provides a solid basis for numerous extensions.

Spatial and temporal analysis of landscape patterns

Abstract: A variety of ecological questions now require the study of large regions and the understanding of spatial heterogeneity. Methods for spatial-temporal analyses are becoming increasingly important for ecological studies. A grid cell based spatial analysis program (SPAN) is described and results of landscape pattern analysis using SPAN are presentedd. Several ecological topics in which geographic information systems (GIS) can play an important role (landscape pattern analysis, neutral models of pattern and process, and extrapolation across spatial scales) are reviewed. To study the relationship between observed landscape patterns and ecological processes, a neutral model approach is recommended. For example, the expected pattern (i.e., neutral model) of the spread of disturbance across a landscape can be generated and then tested using actual landscape data that are stored in a GIS. Observed spatial or temporal patterns in ecological data may also be influenced by scale. Creating a spatial data base frequently requires integrating data at different scales. Spatial is shown to influence landscape pattern analyses, but extrapolation of data across spatial scales may be possible if the grain and extent of the data are specified. The continued development and testing of new methods for spatial-temporal analysis will contribute to a general understanding of landscape dynamics.

A qualitative model for space

Abstract: Most geometric models are quantitative, making it difficult to abstract the underlying spatial information needed for tasks such as planning, learning or vision. Furthermore, the precision used in a typical quantitative system often exceeds the actual accuracy of the data. In this work we describe a systematic representation that builds spatial maps based on local qualitative relations between objects. It derives relations that are more "functionally relevant" - i.e. those that involve accidental alignments, or can be described based on such alignments. In one dimension, interval logic (Allen 83] provides a mechanism for representing these type of relations; in this work we propose a formalism that enables us to perform alignment-based reasoning in two and higher dimensions with objects at angles. The principal advantages of this representation is that a) it is free of subjective bias, and b) it is complete in the qualitative sense of distinguishing all overlap/ tangency/nocontact geometries. In addition, the model is capable of handling uncertainty in the initial system (e.g. "the fuse box is somewhere behind the compressor") by constructing bounded inferences from disjunctive input data. Two kinds of uncertainty can be handled - those arising from deliberate imprecision in the interest of compactness ("down the road from"), or those caused by an inadequacy of data (sensors, spatial descriptions, or maps).

A topological data model for spatial databases

Abstract: There is a growing demand for engineering applications which need a sophisticated treatment of geometric properties. Implementations of Euclidian geometry, commonly used in current commercial Geographic Information Systems and CAD/CAM, are impeded by the finiteness of computers and their numbering systems. To overcome these deficiencies a spatial data model is proposed which is based upon the mathematical theory of simplices and simplicial complexes from combinatorial topology and introduces completeness of incidence and completeness of inclusion as an extension to the closed world assumption. It guarantees the preservation of topology under affine transformations. This model leads to straightforward algorithms which are described. The implementation as a general spatial framework on top of an object-oriented database management system is discussed.

Model-free estimation from spatial samples: A reappraisal of classical sampling theory

Abstract: A commonly held view among geostatisticians is that classical sampling theory is inapplicable to spatial sampling because spatial data are dependent, whereas classical sampling theory requires them to be independent. By comparing the assumptions and use of classical sampling theory with those of geostatistical theory, we conclude that this view is both false and unfortunate. In particular, estimates of spatial means based on classical sampling designs require fewer assumptions for their validity, and are therefore more robust, than those based on a geostatistical model.

Quantitative Methods and Biogeographic Analysis

Abstract: Numerical methods are presented that represent three different approaches to biogeographic problems. The first approach is multivariate data analysis. The delineation of biogeographic “provinces” or areas is a type of descriptive analysis that can be accomplished by clustering faunal data (with or without spatial contiguity constraint) and drawing the resulting choropleth map. On the other hand, ecological biogeographers like to use ordinations of sampling localities and interpret the main axes of variation in terms of environmental gradients; canonical ordination, where a species presence or abundance data table and an environmental data matrix are both analyzed simultaneously, can be used with profit in this context. Secondly, the analysis of spatial patterns can help identify the type of spatial distribution of the biological material, both at the population and at the community level, while Mantel tests and other derived analyses make it possible to test hypotheses concerning causal factors possibly responsible for the observed spatial structures. Finally, phylogenetic-tree reconstruction methods, as well as other techniques, can be used for historical biogeographic studies; these include the study of taxa cladograms and of area cladograms.

Statistical comparison of spatial fields in model validation, perturbation, and predictability experiments

Abstract: The comparison of spatial fields of meteorological variables is an essential component of model validation studies and is central in assessing the significance of any change between a perturbed and control run of a general circulation model. Comparisons may be made of statistics which define the time-mean state, the temporal variability about this state, and/or spatial variability. Comparisons may also be made of the two time-mean spatial patterns, or of the temporal evolutions of spatial patterns. We consider here a suite of univariate and multivariate statistics which may be used to make these comparisons. Some of these statistics have been used previously, while others are either new or have not previously been used in the present context. The use of these statistics, their differences and similarities, and their relative performances are illustrated by considering mean sea level pressure changes between the decades 1951–1960 and 1971–1980 over an area covering North America, the North Atlantic Ocean, and Europe. Significance levels are assessed using the pool-permutation procedure of Preisendorfer and Barnett (1983) (henceforth P+B). This overcomes problems arising from nonideal behavior of the data (particularly spatial autocorrelation), unknown sampling distributions, and multiplicity in the case of univariate statistics. A subset of statistics is identified as most useful. For tests of differences in means these are the grid point by grid point t-test, a test comparing the overall means, and P+B's SITES statistic. For tests of differences in temporal variability they are the grid point by grid point F-test, and SPRET1 (the ratio of the spatial means of the time variances). SPRET1 is a modification of P+B's SPRED statistic designed to identify the direction of any variance difference. As a test of spatial variability differences, we identify SPREX1 (the ratio of the time means of the spatial variances), and for comparing spatial patterns the best statistic is the (spatial) correlation coefficient between the time-mean fields. For comparing the temporal evolution of spatial patterns, we recommend using the time-mean anomaly field correlation which is a more easily interpreted equivalent to P+B's SHAPE statistic.

Approximate analysis of variance of spatially autocorrelated regional data

Abstract: The classical method for analysis of variance of data divided in geographic regions is impaired if the data are spatially autocorrelated within regions, because the condition of independence of the observations is not met. Positive autocorrelation reduces within-group variability, thus artificially increasing the relative amount of among-group variance. Negative autocorrelation may produce the opposite effect. This difficulty can be viewed as a loss of an unknown number of degrees of freedom. Such problems can be found in population genetics, in ecology and in other branches of biology, as well as in economics, epidemiology, geography, geology, marketing, political science, and sociology. A computer-intensive method has been developed to overcome this problem in certain cases. It is based on the computation of pooled within-group sums of squares for sampled permutations of internally connected areas on a map. The paper presents the theory, the algorithms, and results obtained using this method. A computer program, written in PASCAL, is available.

SPIDER—an interactive statistical tool for the analysis of spatially distributed data

Abstract: Interactive statistical graphics are reviewed in the contexts of spatial data and geographical information systems (GIS). GIS provide the user with an active geographical view of the data—a map that can be used as an entry point to the data base. Prototype software—SPIDER—illustrates the possibilities of using statistical graphics as further views of the data, which can be made active and thus provide alternative means of querying the data. These views can be cross-referenced by 'linking'. It is argued that such a system can provide a very rich environment for pursuing exploratory statistical analysis of spatial data.

Rendering and managing spherical data with sphere quadtrees

Abstract: Most databases for spherically distributed data are not structured in a manner consistent with their geometry. As a result, such databases possess undesirable artifacts, including the introduction of "tears" in the data when they are mapped onto a flat file system. Furthermore, it is difficult to make queries about the topological relationship among the data components without performing real arithmetic. The sphere quadtree (SQT), which is based on the recursive subdivision of spherical triangles obtained by projecting the faces of an icosahedron onto a sphere, eliminates some of these problems. The SQT allows the representation of data at multiple levels and arbitrary resolution. Efficient search strategies can be implemented for the selection of data to be rendered or analyzed by a specific technique. Furthermore, sphere quadtrees offer significant potential for improving the accuracy and efficiency of spherical surface rendering algorithms as well as for spatial data management and geographic information systems. Most importantly, geometric and topological consistency with the data is maintained.

Spatial autocorrelation of wildfire distribution in the Idyllwild Quadrangle, San Jacinto Mountain, California.

Abstract: A spatial autocorrelation analysis was conducted to examine the distribution of wildfires. Moran's I coefficients of past fire activity were generated based on different spatial weighting functions. Data overlays of multiple GIS layers derive the explanatory variables for modeling the distribution of wildfires from logistic regressions. Without incorporating the spatial term, fire rotation is the leading factor of fire occurrence. The model is improved significantly when the spatial term is included

One-Sample Tests in Regional Archaeological Analysis: New Possibilities through Computer Technology

Abstract: Archaeologists commonly employ two-sample statistical tests in regional locational analyses that compare environmental measurements obtained at site locations against measurements taken at random locations from the background environment. One-sample tests that compare a site sample against a background standard are conceptually and statistically superior, but have been difficult to implement for continuous data types. This situation now is changed owing to a relatively new computer technology known as Geographic Information Systems (GIS). GIS can provide a complete description of the nature of the background environment of entire regions for categorical and continuous data types, thereby allowing the ready application of one-sample testing strategies. Examples of several GIS-based one-sample tests are given using data from east-central Arizona. Such conventional tests only should be applied, however, when the observations can be shown to be statistically independent through tests for spatial autocorrelation.

Integration of spatial data in vector and raster formats in a geographic information system environment

Abstract: This paper examines the common methods for converting spatial data sets between vector and raster formats and presents the results of extensive benchmark testing of these procedures. The tests performed are unique in this field since: (1) they used both synthetic and real test data sets; (2) they measured conversion quality, accuracy and efficiency, not just how fast the procedure operated; and (3) they were conducted in a generic geographic information system (GIS) environment without the aid of specialized computer hardware. The results show that the best overall techniques are the ones which take advantage of spatial relationships inherent in the data sets. These were the Scan Line algorithm for vector to raster conversions and the Boundary Linking algorithm for raster to vector conversions.

Autocorrelation Functions for Offshore Geotechnical Data

Abstract: Autocorrelation functions are described. Data from several North Sea sites are analyzed with respect to the vertical and horizontal autocorrelation of a number of soil properties. Based on these analyses, a simple method for estimating autocorrelation functions is recommended. The use of autocorrelation functions for describing a site probabilistically, in particular for stochastic interpolation (kriging) and reduction of uncertainty due to spatial averaging, is discussed.

The use of added variable plots in regression modelling with spatial data

Abstract: A simple graphical method for developing regression models for spatially referenced data is presented. The method supplements formal testing procedures and provides the analyst with useful information helpful in developing an understanding of data properties without the need for complex data manipulations. The paper includes a worked example and suggests directions for further work in this area.

Limitations to the identification of spatial structures from AVHRR data

Abstract: Satellite sensor data with different resolution-cell sizes have been used to show how sensor-induced spatial autocorrelation in High Resolution Picture Transmission (HRPT) data, and local variance induced by sampling in Global Area Coverage (GAC) data, may limit the use of Advanced Very High Resolution Radiometer (AVHRR) data for the identification of spatial structure and pattern.

Spatial autocorrelation in marine birds

Abstract: All marine organisms exhibit some degree of spatial autocorrelation, which is the tendency for high (or low) densities to occur in proximity, rather than at random in the ocean. Autocorrelation occurs at scales ranging from the length of the organism to thousands of kilometres. Autocorrelation results from a wide variety of mechanisms, many of which act at characteristic scales. Consequently, some insight into causal mechanisms can be obtained from exploratory analysis of the scale and intensity of autocorrelation of abundance or behaviour, and the scale and intensity (coherence) of cross-correlation with environmental variables such as water temperature or prey abundance. This paper uses seabird counts along extended transects to illustrate standard measures of autocorrelation and cross-correlation. A brief discussion of exploratory and confirmatory analysis of autocorrelated data on marine birds follows.

Interaction with geographic information systems via spatial queries

Abstract: In the past, the design of Geographic Information Systems (GIS) has been investigated in a bottom-up manner. At the same time, little consideration has been paid to those system components with which users have immediate contact such as languages to query spatial objects, or the user interface. Considerations about the interaction between the users and spatial data are of primary importance for these issues. The domain of this paper is the investigation of interactive spatial query languages that allow users to pose ad hoc queries against a geographic information system. Its motivation has been the observation that traditional database query languages are insufficient for the treatment of spatial properties. Deficiencies observed include the disregard of user concerns and the lack of support for renderings of query results in forms other than text. This paper presents a methodology for the design of interactive spatial query languages which are embedded into a human interface. The methodology is based upon the users' interactions with spatial objects, which are graphically rendered on a screen, and their pertinent operations. Objects and operations are provided at the conceptual level of the user interface and complemented by the selection of appropriate techniques to interact with spatial objects rendered on a screen. A number of spatial concepts are presented which are crucial for the design of a GIS query language. In a series of interface snapshots their incorporation into a human interface is presented, simulating the interaction between a user and a GIS.

A Data Structure for Spatio-Temporal Databases

Abstract: The advantages and applications of spatial mechanisms are well documented; however, there are very few being designed. The principal hinderance to the design of spatial mechanisms is the great difficulty involved in specifying spatial problems and in interpreting spatial solutions. Similarly, the development of spatial codes to implement these techniques is held back by the lack of means to easily visualize and verify solutions, particularly in the realm of relational databases. If spatial mechanisms are to be successful, the designer must be able to synthesize, analyse and evaluate, as well as load and extract information, using a single code representing a spatial structure. This entails the implementation of spatial relationships involving spatial data structures. It is with this in mind that the Canadian Hydrographic Service database group embarked on the development of a new type of spatial database structure based on the quadtree concept.

Spatial patterns of genetic variability in Italian chestnut (Castanea sativa).

Abstract: The spatial patterns of genetic variation for 15 loci in 18 Italian populations of chestnut were analyzed. Multivariate analysis and spatial autocorrelation analysis showed two clinal variations, one in a west–east direction, the other in a north–south direction. There was a nonrandom spatial pattern of at least three alleles and a marked heterogeneity among populations of many others. An explanation is proposed in terms of migration flow for the majority of the polymorphisms and of selection for the three autocorrelated alleles. However, anthropic interferences may also be important. Key words: chestnut, electrophoresis, spatial autocorrelation, correspondence analysis, genetic boundaries, discriminant analysis.

Two Approaches to Design of Monitoring Networks

Abstract: Two different approaches to the design of a ground-water-quality monitoring network may be appropriate, depending on the type of information desired. First, where the objective is to determine what ground-water-quality characteristics are like in an area (statistical quantification of typical concentrations, as given by the mean or median, or percentage of wells exceeding various use standards), networks can be designed to provide estimates of known reliability using standard parametric and nonparametric statistical techniques. This approach can provide information adequate to perform general water-quality assessments where the intention of the monitoring network is to provide data about general suitability of the water for various uses. Second, where the objective is to maximize areal ground-water-quality information, networks also can be designed using geostatistical techniques, such as kriging. This second approach would be appropriate when information is needed on where particular problem areas may exist. Both approaches were applied to 1965 chloride data from a deep confined aquifer in the Llobregat delta near Barcelona, Spain. Traditional statistical techniques are demonstrated to design a network that would provide an estimated median chloride concentration. A method is introduced that can be used to determine the sample size necessary to describe any selected quantile with known precision. On the basis of 120 observations in the 1965 data set, between 13 and 25 wells would be necessary to estimate the median chloride concentration within 40 percent of the true median with 95-percent confidence. Kriging, a geostatistical technique, was applied to the data set to determine the minimum number of wells necessary to include in the network to retain the essential spatial information of the original network. By use of this technique, the original network of 120 wells was reduced by 17.5 percent to 99 wells, while the standard error was increased by only 1 percent. A comparison of these two approaches indicates that a network designed by use of geostatistical techniques generally will require larger sample sizes than networks designed by use of traditional techniques, but the geostatistical techniques can provide data adequate to describe both stochastic and spatial features of water-quality variables. Detailed description of spatial variability requires many sample points for extremely variable data. On the basis of results presented in this paper, prediction errors for chloride concentrations in ground water at selected points in the Llobregat delta were as much as 300 percent. Nevertheless, even the modified network of 99 wells would produce statistical estimates adequate for most general water-quality assessments, in addition to retaining the spatial information contained in the original 1965 data set.

Manipulating the graphical representation of query results in geographic information systems

Abstract: An investigation into how the properties of spatial data, in particular their graphical representation, influence the interaction between user and system is presented. Of particular interest are the concepts humans have about spatial data and the operations that allow them to manipulate and examine the graphical representation of spatial data. An overview of the architecture of spatial information systems is given, concentrating on user interfaces for spatial data handling. An investigation into how users manipulate the representation of spatial data is given, followed by the introduction of the corresponding operations necessary to examine the representation. A series of interface snapshots is given to demonstrate these ideas in a simulated user interface. >

Fractal descriptions for spatial statistics.

Abstract: Measures of spatial statistics have been available for estimating means, calculating or assessing differences, estimating nearest neighbor distances, and such, but have not provided a general approach to describing variances. Because measures of heterogeneity depend upon choosing a particular element size in the domain, estimates of apparent heterogeneity are larger with high-resolution observations than with low-resolution data. Many descriptors might be used to describe the relationships between apparent heterogeneity and the size of the observed spatial elements, but we have found that fractal relationships provide concise and precise descriptions of many types of data over large ranges of element sizes. Perhaps more importantly, the fractal approaches give additional insight, such as measures of spatial correlation, and often suggest ways of approaching the underlying basis of the heterogeneity.

Defect cluster analysis for wafer-scale integration

Abstract: A methodology for characterizing spatial defect distributions is presented. A correlation function approach providing spatial information not measurable with classical methods such as yield-versus-area curves is described. This additional information includes the spatial extent of defect clustering, the strength of clustering, and uncertainty in clustering magnitude. The correlation function methods are applicable to experimentally determined defect maps or to simulation results based on different assumptions concerning the spatial distribution of defects. It is also shown that the approach is useful in predicting yield for redundant circuit configurations when experimental data pertaining to the spatial distribution of defects are available. This type of yield prediction capability is important for judging the feasibility of various redundancy implementations, including wafer scale integration. >

Integrating Urban Information Systems and Spatial Models

Abstract: The evolution of spatial and nonspatial information systems is rapidly altering the role of applied computing in urban and regional planning. Urban development tracking and monitoring systems are in place in many regions in the United States and Canada. These systems provide continual status reports on land-use activity. Also, spatial interaction models are being developed for several major cities in the United States. The corollary collection of many types of spatial information has been impressive, The US Census will produce TIGER geo-referenced files with the 1990 census, and information will be widely available on CD-ROM disks. In this paper current trends in the development of new data sources, information systems, and spatial modelling are discussed and the potential for integrating these elements into a working planning-support system is discussed.

Integrating spatial data : a user's perspective

Abstract: An emerging trend in geographic information systems (GIS) applications is the use of multiple systems and diverse data sets in a single study In practice, sharing spatial data among several different systems is difficult because of incompatibilities in spatial data formats and limitations within existing GIS We propse in this paper a new GIS design ― a multi-format GIS ― which has the potential to transparently integrate spatial data from diverse sources into a common operation