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County child poverty rates in the US: a spatial regression approach

POPULATION RESEARCH AND POLICY REVIEW 2006年第4期25卷 369-391页

作者： Voss, Paul R. Long, David D. Hammer, Roger B. Friedman, Samantha Univ Wisconsin Dept Rural Sociol Madison WI 53706 USA Oregon State Univ Dept Sociol Corvallis OR 97331 USA Northeastern Univ Dept Sociol & Anthropol Boston MA 02115 USA

We apply methods of exploratory spatial data analysis (ESDA) and spatial regression analysis to examine intercounty variation in child poverty rates in the US. Such spatial analyses are important because regression models that exclude explicit specification of spatial effects, when they exist, can lead to inaccurate inferences about predictor variables. Using county-level data for 1990, we re-examine earlier published results [Friedman and Lichter (Popul Res Policy Rev 17:91-109, 1998)]. We find that formal tests for spatial autocorrelation among county child poverty rates confirm and quantify what is obvious from simple maps of such rates: the risk of a child living in poverty is not (spatially) a randomly distributed risk at the county level. Explicit acknowledgment of spatial effects in an explanatory regression model improves considerably the earlier published regression results, which did not take account of spatial autocorrelation. These improvements include: (1) the shifting of "wrong sign" parameters in the direction originally hypothesized by the authors, (2) a reduction of residual squared error, and (3) the elimination of any substantive residual spatial autocorrelation. While not without its own problems and some remaining ambiguities, this reanalysis is a convincing demonstration of the need for demographers and other social scientists to examine spatial autocorrelation in their data and to explicitly correct for spatial externalities, if indicated, when performing multiple regression analyses on variables that are spatially referenced. Substantively, the analysis improves the estimates of the joint effects of place-influences and family-influences on child poverty.

关键词： child poverty exploratory spatial data analysis spatial error models spatial lag models spatial regression

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spatial analysis of hemorrhagic fever with renal syndrome in China

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BMC INFECTIOUS DISEASES 2006年第1期6卷 77-77页

作者： Fang, Liqun Yan, Lei Liang, Song de Vlas, Sake J. Feng, Dan Han, Xiaona Zhao, Wenjuan Xu, Bing Bian, Ling Yang, Hong Gong, Peng Richardus, Jan Hendrik Cao, Wuchun Beijing Inst Microbiol & Epidemiol State Key Lab Pathogen & Biosecur Beijing Peoples R China Chinese Acad Sci Inst Remote Sensing Applicat Beijing Peoples R China Erasmus MC Univ Med Ctr Dept Publ Hlth Rotterdam Netherlands Univ Buffalo Dept Geog Buffalo NY USA Univ Calif Berkeley Sch Publ Hlth Berkeley CA 94720 USA

Background: Hemorrhagic fever with renal syndrome ( HFRS) is endemic in many provinces with high incidence in mainland China, although integrated intervention measures including rodent control, environment management and vaccination have been implemented for over ten years. In this study, we conducted a geographic information system (GIS)-based spatial analysis on distribution of HFRS cases for the whole country with an objective to inform priority areas for public health planning and resource allocation. Methods: Annualized average incidence at a county level was calculated using HFRS cases reported during 1994 - 1998 in mainland China. GIS- based spatial analyses were conducted to detect spatial autocorrelation and clusters of HFRS incidence at the county level throughout the country. Results: spatial distribution of HFRS cases in mainland China from 1994 to 1998 was mapped at county level in the aspects of crude incidence, excess hazard and spatial smoothed incidence. The spatial distribution of HFRS cases was nonrandom and clustered with a Moran's I = 0.5044 ( p = 0.001). spatial cluster analyses suggested that 26 and 39 areas were at increased risks of HFRS ( p < 0.01) with maximum spatial cluster sizes of <= 20% and <= 10% of the total population, respectively. Conclusion: The application of GIS, together with spatial statistical techniques, provide a means to quantify explicit HFRS risks and to further identify environmental factors responsible for the increasing disease risks. We demonstrate a new perspective of integrating such spatial analysis tools into the epidemiologic study and risk assessment of HFRS.

关键词： County Level Hemorrhagic Fever With Renal Syndrome spatial Autocorrelation analysis exploratory spatial data analysis Annualize Average Incidence

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Geovisualization of forest simulation modelling results: A case study of carbon sequestration and biodiversity

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COMPUTERS AND ELECTRONICS IN AGRICULTURE 2005年第1期49卷 175-191页

作者： Chertov, O Komarov, A Mikhailov, A Andrienko, G Andrienko, N Gatalsky, P St Petersburg State Univ Biol Res Inst St Petersburg Russia Russian Acad Sci Inst Phys Chem & Biol Problems Soil Sci Pushchino 142290 Russia Fraunhofer Inst Autonomous Intelligent Syst D-53754 St Augustin Germany

Sustainable forest management requires new tools to analyze spatial and temporal forest dynamics and to examine those forest parameters that are related to sustainability. We built a prototype system for data analysis and decision-making at forest enterprise level by integrating a forest ecosystem model EFIMOD-PRO, (long-term prediction of forest growth and soil development) with an interactive visualization system CommonGIS for analysis of spatially and temporally related data. Using the prototype, a case study in Central European Russia simulated four silvicultural regimes over 200 years: natural development, selective forestry, legal forestry according to the Russian forestry legislation, and illegal forest practice. exploratory analysis of the simulation results demonstrated that (1) natural stand development is the best alternative for carbon sequestration;(2) legal forest management is the best regime for timber production;(3). selective forestry combines the advantages of two previous strategies, and can be the best strategy for implementing sustainable forest management;and (4) illegal forest practices lead to a fast decrease in forest productivity and decreasing biodiversity. Interactive and dynamic visualizations With maps and statistical graphics played a crucial role in data cleaning, model validation, and analysis of simulation results. The case study demonstrated the potential of integrating forest ecosystem models with exploratory data visualization for the analysis and expert evaluation at the local level. The prototype can be used to present ecological and silvicultural consequences of various management practices to stakeholders and differing social groups, thus stimulating effective decision-making for sustainable forestry. (c) 2005 Elsevier B.V. All rights reserved.

关键词： simulation modelling silvicultural strategies geovisualization exploratory spatial data analysis

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Geovisualization of forest simulation modelling results: A case study of carbon sequestration and biodiversity

Geovisualization of forest simulation modelling results: A c...

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Conference on Decision Support for Multiple Purpose Forestry

关键词： simulation modelling silvicultural strategies geovisualization exploratory spatial data analysis

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Conditioned choropleth maps and hypothesis generation

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ANNALS OF THE ASSOCIATION OF AMERICAN GEOGRAPHERS 2005年第1期95卷 32-53页

作者： Carr, DB White, D MacEachren, AM George Mason Univ Ctr Computat Stat Fairfax VA 22030 USA US EPA Corvallis OR 97333 USA Penn State Univ Dept Geog GeoVISTA Ctr University Pk PA 16802 USA

The article describes a recently developed template for multivariate data analysis called conditioned choropleth maps (CCmaps). This template is a two-way layout of maps designed to facilitate comparisons. The template can show the association between a dependent variable, as represented in a classed choropleth map, and two potential explanatory variables. The data-analytic objective is to promote better-directed hypothesis generation about the variation of a dependent variable. The CCmap approach does this by partitioning the data into subsets to control the variation in the dependent variable that is associated with two conditioning variables. The interactive implementation of CCmaps introduced here provides dynamically updated map panels and statistics that help in comparing the distributions of conditioned subsets. Patterns evident across subsets indicate the association of conditioning variables with the dependent variable. The patterns lead to hypothesis generation about scientific relationships behind the apparent associations. spatial patterns evident within individual subsets lead to hypothesis generation that is often mediated by the analyst's knowledge about additional variables. Examples showing applications of the methods to health-environment interaction and biodiversity analysis are presented.

关键词： geovisualization exploratory spatial data analysis choropleth maps hypothesis generation partitioning sliders stratified comparison dynamic map statistical annotation

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Web-based analytical tools for the exploration of spatial data

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Journal of Geographical Systems 2004年第2期6卷 197-218页

作者： Anselin, Luc Kim, Yong Wook Syabri, Ibnu Spatial Analysis Laboratory Dept. of Agric./Consumer Economics Univ. of Illinois Urbana-Champaign Urbana IL 61801 United States

This paper deals with the extension of internet-based geographic information systems with functionality for exploratory spatial data analysis (ESDA). The specific focus is on methods to identify and visualize outliers in maps for rates or proportions. Three sets of methods are included: extreme value maps, smoothed rate maps and the Moran scatterplot. The implementation is carried out by means of a collection of Java classes to extend the Geotools open source mapping software toolkit. The web based spatial analysis tools are illustrated with applications to the study of homicide rates and cancer rates in U.S. counties. © Springer-Verlag 2004.

关键词： exploratory spatial data analysis Geotools Internet GIS Smoothing spatial autocorrelation spatial outliers

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Interactive Graphics and Local Statistics

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Journal of the Royal Statistical Society: Series D (The Statistician) 2002年第3期47卷 423-430页

作者： A. Wilhelm R. Steck Universitat Augsburg Germany

exploratory spatial data analysis has a series of aims including determining spatial structure in the data, describing and visualizing geographical distributions, exploring spatial dependencies, measuring heterogeneity and identifying outliers. To quantify these phenomena a rich variety of statistics has been proposed. Standard methods use all the data for the entire area under study, yet this area has usually been arbitrarily bounded and may include quite distinctive geographic features. Local statistics are relatively independent of the global boundaries and they attempt to quantify how close a given datum is to the values in its neighbourhood. Since each local statistic focuses on slightly different aspects of the data the use of more than one is suggested. Interactive graphics methods help to link the information from different local statistics and dynamic tools can be used to visualize the effects of changing the neighbourhood definition.

关键词： exploratory spatial data analysis Interactive graphics Linking information Local statistics Neighbourhood

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analysis of Dialect Features

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Journal of the Royal Statistical Society: Series D (The Statistician) 2002年第3期47卷 445-455页

作者： A. Wilhelm M. Sander Universitat Augsburg Germany

Interactive graphical analysis has proven to be a seminal method in exploring quantitative spatial data. Using data from a dialect survey we demonstrate that it can also reveal structure in qualitative spatial data. The flexibility offered by such exploratory tools can deal with the special problems caused by multiple responses and by local geographic effects.

关键词： Classification Dialect features exploratory spatial data analysis Interactive graphics Multiple responses

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Cartographic visualization: exploratory spatial data analysis with local indicators of spatial association using Tcl/Tk and cdv

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JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES D-THE STATISTICIAN 1998年第3期47卷 485-497页

作者： Dykes, J Univ Leicester Dept Geog Leicester LE1 7RH Leics England

cdv, a cartographic data visualizer, is a piece of demonstration software designed for research and teaching. It uses established symbolism techniques for displaying spatially referenced information, and adds newer dynamic capabilities that are suitable for exploratory spatial data analysis (ESDA). The software takes advantage of the symbolism, dynamism and inherent spatial information afforded by the Tcl/Tk language and comprises interpreted scripts which provide a flexible environment for prototyping and extension. This introduction to the software and approach outlines some of the rationale behind the development and contains an overview of the cartographic and statistical ESDA functionality. The distributed scripts produce concurrent linked views of enumerated data sets. Views are available for statistical and geographic visualization of univariate, bivariate and multivariate distributions. These include dotplots, scatterplots, polygon maps, population cartograms and parallel cc-ordinates plots. Each view is extremely dynamic so that transient maps can be produced to highlight specific cases and to focus on points of interest to suit the researcher. The ideas are applied to procedures for determining locality and assessing the characteristics of local variation, and some examples of dynamic graphical local indicators are provided. The examples and images provide a flavour of the approach and the dynamic and flexible nature of the software. One of the advantages of the approach is that, as the software is free and accessible on the Internet, the author is not restricted to static black-and-white graphics for communicating dynamic colourful ideas. Larger colour versions of the images can be downloaded to support the paper.

关键词： cartography exploratory spatial data analysis flexibility local indicators of spatial association scripting visualization

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Using local statistics for boundary characterization

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GeoJournal 2001年第4期53卷 339-345页

作者： Boots, Barry Dept. of Geogr./Environ. Studies Wilfrid Laurier University Waterloo Ont. N2L 3C5 Canada

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