摘要:

This paper presents a personal view on some emerging research directions at the interface of social science and spatial analysis. Particular emphasis is placed on methodological challenges presented by developments in social science theory, demands for data manipulation, and the need for education and dissemination.

ISSN:1082-4006    

DOI:10.1080/10824009909480516

出版商:Taylor & Francis Group    

年代:1999

数据来源: Taylor

摘要:

Spatial statistics quantify spatial pattern and identify local and global departures from null spatial models. As part of Exploratory Spatial Data Analysis they play a critical role in the evaluation of spatial pattern, and in the formulation of hypotheses to explain spatial pattern. While all spatial data have imprecise locations, the magnitude of this imprecision can vary dramatically from one measuring instrument to another and from one study to another. When does location uncertainty impede our ability to quantify spatial pattern? This paper describes credibility-based spatial randomization tests that propagate location uncertainty through proximity metrics and into spatial statistics. Credibility is a flexible new approach to spatial randomization tests, but is not a panacea. It applies to spatial statistics that incorporate measures of geographic proximity (e.g. spatial adjacency, weight, nearest neighbor relationship, distanceetc.). It uses Monte Carlo sampling to generate the null distribution, and not distribution theory, as classical statistics do. It is a technique for testing hypotheses regarding spatial pattern, and is best described as a method for Exploratory Spatial Data Analysis. It is meant to complement, not replace, traditional spatial statistics that use P-values and alpha levels. In conjunction with these techniques it forms a quantitative basis for evaluating the likely impact of location uncertainty on one's ability to make statistical decisions with spatial data.

ISSN:1082-4006    

DOI:10.1080/10824009909480517

出版商:Taylor & Francis Group    

年代:1999

数据来源: Taylor

摘要:

This paper reviews four different approaches for estimating the block-averaged value of an environmental attribute from point data: 1) the sample arithmetic average, 2) the declustered mean, 3) block kriging, and 4) stochastic simulation. The first approach is straightforward and well suited for estimation over large blocks that contain many randomly located observations. Declustering techniques can be used to correct for preferential sampling of specific subareas of such large blocks. The last two techniques, kriging and simulation, account for the pattern of spatial dependence of observations and allow one to compensate for the shortage of data inside small blocks by incorporating observations outside the block. The major advantage of stochastic simulation is that it provides a non-parametric measure of the uncertainty attached to the prediction of a single block or multiple spatially dependent blocks. Stochastic simulation can also be used to upscale properties like permeability that do not average linearly in space, whereas the first 3 techniques are only valid for linear averaging parameters. The different techniques are illustrated using a soil data set related to heavy metal contamination over a 14.5km2area in the Swiss Jura.

ISSN:1082-4006    

DOI:10.1080/10824009909480518

出版商:Taylor & Francis Group    

年代:1999

数据来源: Taylor

摘要:

This paper contributes to the ongoing debate about which spatial analysis functions should be coupled with a GIS by identifying research problems that need to be solved before a richer toolbox of spatial statistical techniques can be implemented in a GIS. Three general problem areas are addressed. The first replaces a sequential ordinary least squares linear regression implementation with a single regression analysis. The second establishes the effective sample size for a single variable in a georeferenced data set, a result useful when calculating confidence intervals for means. The third establishes the effective sample size for pairs of variables in a georeferenced data set, a result useful when calculating the significance of correlation coefficients. These three general problems allow four more specific research problems to be identified that are in need of definitive solutions before a richer toolbox of spatial statistical techniques can be relatively easily implemented in a GIS. Their complete solutions will involve both empirical assessments and simulation experiments. These four problems are represented by four principal equations posited in this paper, equations that offer considerable computational simplification for the implementation of spatial statistical techniques within a GIS. Sufficient evidence in support of them is presented here to allow their implementation at this time on an experimental basis. These equations remove the need for eigenfunction and nonlinear optimization routines, and maintain the standard linear regression technique as the workhorse of a GIS statistical analysis. They also strengthen the inferential basis for a spatial scientist.

ISSN:1082-4006    

DOI:10.1080/10824009909480519

出版商:Taylor & Francis Group    

年代:1999

数据来源: Taylor

摘要:

This study uses various spatial statistical methods to examine and model large- and small-scale spatial structure in bird abundance and urbanization. A set of chaparral-vegetated points across an urbanizing landscape in the Santa Monica Mountains of southern California was surveyed for birds in 1997 and mapped in a GIS. For each sample location, GIS landuse data were used to calculate surrounding urbanization proportion.

ISSN:1082-4006    

DOI:10.1080/10824009909480520

出版商:Taylor & Francis Group    

年代:1999

数据来源: Taylor

摘要:

Based on the subdistrict (jie-dao) data from 1982 and 1990 national population censuses, this research employs two approaches to investigate the urban population change patterns in Shenyang, China. The density function approach examines what function best characterizes its density distribution, how the density pattern has changed over time, how many centers can be identified in the city, and how influential each center has been on the citywide population distribution. Unlike the socialist cities in Russia, Shenyang has a negative density gradient, bearing more resemblance to western cities. A polycentric model explains the spatial variation of densities in Shenyang much better than a monocentric model. The spatial association approach analyzes the core-peripheral relationship between a city center and its neighboring areas. Both approaches show that people moved from the central city to suburbs, indicating a trend of population decentralization. This trend is attributable to the land use reform, central city renovation projects and improvements of suburban infrastructure and services.

ISSN:1082-4006    

DOI:10.1080/10824009909480521

出版商:Taylor & Francis Group    

年代:1999

数据来源: Taylor

摘要:

This paper utilizes GIS technology integrated with spatial analysis and spatial modeling techniques to explore the roles of intermediate-size regional centers – Chiang Mai City and Lamphun Municipality (Northern Thailand) – in spreading development to surrounding rural areas. The spatial process of regional development is mapped in various physical, socio-demographic and economic aspects for the years 1986 and 1994 and, then, quantified using spatial autocorrelation statistics. The radiuses of significant spreading effects from the two centers are defined using so-calledring analysisandspatial cross-correlograms. The roles of growth centers in terms of urban core – rural periphery interaction are then modeled using spatial lag regression model. As results, insights into spatial patterns, spatial extent and intensity of core-periphery inter-dependencies in terms of important socio-economic factors in regional development during the 1986 – 1994 period are revealed. This application also demonstrates that GIS can serve as a useful technical vehicle, upon which various exploratory and explanatory spatial analysis techniques can be built in order to evaluate and further advance regional development strategies.

ISSN:1082-4006    

DOI:10.1080/10824009909480522

出版商:Taylor & Francis Group    

年代:1999

数据来源: Taylor

摘要:

It is universally acknowledged that China's recent economic growth involves distinct spatial patterns across the 30 provinces. Despite this, most studies analyze provincial economic growth patterns using cross-sectional methods that average over all provinces. This study analyzes China's recent economic growth at a provincial level using non-parametric and Bayesian spatial econometric methods that allow for locally linear spatial variation in the relationships being analyzed.

ISSN:1082-4006    

DOI:10.1080/10824009909480523

出版商:Taylor & Francis Group    

年代:1999

数据来源: Taylor

摘要:

Spatially fragmented patterns of development have led to an interest in growth control measures aimed at altering the fragmented pattern and creating incentives to cluster development in the landscape. Due to the spatially dependent nature of land values, a geographic information system is used with statistical software to visualize and analyze the spatial pattern of land values in a fast growing suburban county of Washington DC. Spatial statistical measures of correlation and the semivariogram are used to measure the degree of spatial correlation and the distance over which the residuals of the hedonic land value model are correlated. These results are used in a spatial econometric framework to more efficiently draw inference on the effects of growth controls on the spatial pattern of land value. Hedonic analysis reveals that open space and rural preservation are implicitly positively capitalized into newly developed land values through zoning regulations.

ISSN:1082-4006    

DOI:10.1080/10824009909480524

出版商:Taylor & Francis Group    

年代:1999

数据来源: Taylor

摘要:

Significant research effort has been focusing on using GIS for advanced spatial statistics, modeling, and simulation. This paper argues that even though GIS have great potential to facilitate sophisticated spatial modeling and spatial statistics, the simple but important theme of combining spatial information with statistical analysis has not received enough attention and should not be neglected. This paper discusses how different types of geographic information can be derived from and stored in GIS with special attention on location information. Other types of geographic information such as spatial relationship and connectivity are derivatives of simple location information and are briefly discussed. Using a set of centrographic measures – a subset of spatial statistics, this paper demonstrates how statistical techniques can be combined with geographic information such as longitude and latitude of points in analyses. Some of these techniques also utilize attribute data of the point locations in conjunction with locational information. As long as geographic information is extracted from GIS and made accessible to users, the GIS environment provides great potential to develop new spatial analytical methods by directly manipulating geographic information alone or together with attribute data. Using locational and attribute data of selected U.S. cities as an example, this paper shows how spatial mean, spatial median, standard distance and deviational ellipse are derived in a GIS environment.

ISSN:1082-4006    

DOI:10.1080/10824009909480525

出版商:Taylor & Francis Group    

年代:1999

数据来源: Taylor