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1.
Geographic Information System (GIS) software is constrained, to a greater or lesser extent, by a static world view that is not well-suited to the representation of time (Goodchild 2000). Space Time Intelligence System (STIS) software holds the promise of relaxing some of the technological constraints of spatial only GIS, making possible visualization approaches and analysis methods that are appropriate for temporally dynamic geospatial data. This special issue of the Journal of Geographical Systems describes some recent advances in STIS technology and methods, with an emphasis on applications in public health and spatial epidemiology.The STIS expert workshops were funded in part by grants R01CA092669 and R01CA096002 from the National Cancer Institute, and by grants R43-ES010220 and R44-ES010220 from the National Institute of Environmental Health Sciences. Gillian AvRuskin provided cheerful editorial assistance. We thank the participants at the workshops for providing invaluable expertise and critical insights. 相似文献
2.
This paper presents the first application of spatially correlated neutral models to the detection of changes in mortality rates across space and time using the local Morans I statistic. Sequential Gaussian simulation is used to generate realizations of the spatial distribution of mortality rates under increasingly stringent conditions: 1) reproduction of the sample histogram, 2) reproduction of the pattern of spatial autocorrelation modeled from the data, 3) incorporation of regional background obtained by geostatistical smoothing of observed mortality rates, and 4) incorporation of smooth regional background observed at a prior time interval. The simulated neutral models are then processed using two new spatio-temporal variants of the Morans I statistic, which allow one to identify significant changes in mortality rates above and beyond past spatial patterns. Last, the results are displayed using an original classification of clusters/outliers tailored to the space-time nature of the data. Using this new methodology the space-time distribution of cervix cancer mortality rates recorded over all US State Economic Areas (SEA) is explored for 9 time periods of 5 years each. Incorporation of spatial autocorrelation leads to fewer significant SEA units than obtained under the traditional assumption of spatial independence, confirming earlier claims that Type I errors may increase when tests using the assumption of independence are applied to spatially correlated data. Integration of regional background into the neutral models yields substantially different spatial clusters and outliers, highlighting local patterns which were blurred when local Morans I was applied under the null hypothesis of constant risk.This research was funded by grants R01 CA92669 and 1R43CA105819-01 from the National Cancer Institute and R43CA92807 under the Innovation in Biomedical Information Science and Technology Initiative at the National Institute of Health. The views stated in this publication are those of the authors and do not necessarily represent the official views of the NCI. The authors also thank three anonymous reviewers for their comments that helped improve the presentation of the methodology. 相似文献
3.
Measuring similarity between geospatial lifelines in studies of environmental health 总被引：3，自引：0，他引：3
Many epidemiological studies involve analysis of clusters of diseases to infer locations of environmental hazards that could be responsible for the disease. This approach is however only suitable for sedentary populations or diseases with small latency periods. For migratory populations and diseases with long latency periods, people may change their residential location between time of exposure and onset of ill health. For such situations, clusters are diffused and diluted by in- and out-migration and may become very difficult to detect. One way to address the problem of diffused clusters is to include in analyses not only current residential locations, but all past locations at which cases might have been exposed to environmental hazardous. In this paper, we assume that a persons residential history provides such information and represent it through a discrete geospatial lifeline data model. Clusters of similar geospatial lifelines represent individuals who have similar residential histories—and therefore represent people who are more likely to have had similar environmental exposure histories. We therefore introduce a lifeline distance (dissimilarity) measure to detect clusters of cases, providing a basis for revealing possible regions in space-time where environmental hazards might have existed in the past. The ability of the measure to distinguish cases from controls is tested using two sets of synthetically generated cases and controls. Results indicate that the measure is able to consistently distinguish between populations of cases and controls with statistically significant results. The lifeline distance measure consistently outperforms another measure which uses only the distance between subjects residences at time of diagnosis. However, the advantages of using the entire residential history are only partly realized, since the ability to distinguish between cases and controls is only moderately better for the lifeline distance function. Future work is needed to investigate modifications to the inter-lifeline distance measure in order to enhance the potential of this approach to detect locations of environmental hazards over the lifespan.This project is supported by grant number 1 R01 ES09816-01 from the National Institute of Environmental Health Sciences, NIH. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the NIEHS or NIH. We wish to thank Peter Rogerson for helpful discussions of the migration models, and the anonymous reviewers for pointing out areas where the paper could be improved. 相似文献
4.
This article describes the Cancer Atlas Viewer: free, downloadable software for the exploration of United States cancer mortality data. We demonstrate the software by exploring spatio-temporal patterns in colon cancer mortality rates for African-American and white females and males in the southeastern United States over the period 1970–1995. We compare the results of two cluster statistics: the local Moran and the local G*, through time. Overall, the two statistics reach similar conclusions for most locations. Where they disagree reveals functional differences in the kinds of local spatial variation to which the statistics are sensitive and identifies some interesting patterns in the data. There are only two persistent clusters of colon cancer mortality through time, and these are clusters of low values.This project was funded by grant CA92669 from the National Cancer Institute to BioMedware, Inc. The perspectives stated in this article are those of the authors and do not necessarily represent the official views of the National Cancer Institute. Constructive criticism from Heidi Durbeck of BioMedware, Peter Rogerson of SUNY-Buffalo, and three anonymous reviewers helped us improve the interpretation and presentation of these results. 相似文献
5.
Sharon K. Greene Mark A. Schmidt Mary Grace Stobierski Mark L. Wilson 《Journal of Geographical Systems》2005,7(1):85-99
To characterize Michigans high viral meningitis incidence rates, 8,803 cases from 1993–2001 were analyzed for standard epidemiological indices, geographic distribution, and spatio-temporal clusters. Blacks and infants were found to be high-risk groups. Annual seasonality and interannual variability in epidemic magnitude were apparent. Cases were concentrated in southern Michigan, and cumulative incidence was correlated with population density at the county level (r=0.45, p<0.001). Kulldorffs Scan test identified the occurrence of spatio-temporal clusters in Lower Michigan during July–October 1998 and 2001 (p=0.01). More extensive data on cases, laboratory isolates, sociodemographics, and environmental exposures should improve detection and enhance the effectiveness of a Space-Time Information System aimed at prevention.The authors gratefully acknowledge Dr. Duane Newton, former manager of the Virology Section, Michigan Department of Community Health Bureau of Laboratories, for his provision of data on viral isolates. We also appreciate the contributions of Drs. Leah Estberg and Dunrie Greiling for ClusterSeer support, Scott Swan for his assistance with ArcView GIS, and Dr. Edward L. Ionides for his advice on time series analysis. We are grateful to Dr. Pierre Goovaerts and two anonymous reviewers for their insightful comments on an earlier draft of this paper. This project was supported in part by a grant from the National Oceanic and Atmospheric Administrations Joint Program on Climate Variability and Human Health, a consortium including the EPA, NASA, NSF, and EPRI (NA16GP2361) to MLW. 相似文献
6.
Design and implementation of a Space-Time Intelligence System for disease surveillance 总被引：2，自引：0，他引：2
Geoffrey M. Jacquez Dunrie A. Greiling Andrew M. Kaufmann 《Journal of Geographical Systems》2005,7(1):7-23
Modeling chronic and infectious diseases entails tracking and describing individuals and their attributes (such as disease status, date of diagnosis, risk factors and so on) as they move and change through space and time. Using Geographic Information Systems, researchers can model, visualize and query spatial data, but their ability to address time has been limited by the lack of temporal referencing in the underlying data structures. In this paper, we discuss issues in designing data structures, indexing, and queries for spatio-temporal data within the context of health surveillance. We describe a space-time object model that treats modeled individuals as a chain of linked observations comprised of an ID, space-time coordinate, and time-referenced attributes. Movement models for these modeled individuals are functions that may be simple (e.g. linear, using vector representation) or more complex. We present several spatial, temporal, spatio-temporal and epidemiological queries emergent from the data model. We demonstrate this approach in a representative application, a simulation of the spread of influenza in a hospital ward.This research was supported by grant R44ES010220 from the National Institute of Environmental Health Sciences (NIEHS) and by grants R01CA092669 and R01CA96002 from the National Cancer Institute (NCI). The content of this paper does not necessarily represent the official views of the NIEHS or the NCI. 相似文献
7.
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.This research was supported in part by a number of grants from the US National Science Foundation: NSF Grant SBR-9410612, BCS-9978058, to the Center for Spatially Integrated Social Science (csiss), and a grant from the National Consortium on Violence Research (ncovr is supported under grant SBR-9513040 from the National Science Foundation). In addition, support was provided by grant RO1 CA 95949-01 from the National Cancer Institute. Special thanks to Dr. Eugene J. Lengerich of the Pennsylvania State Cancer Institute for providing the data on colon cancer diagnoses. 相似文献
8.
Peter Rogerson 《Journal of Geographical Systems》2005,7(1):101-114
When assessing maps consisting of comparable regional values, it is of interest to know whether the peak, or maximum value, is higher than it would likely be by chance alone. Peaks on maps of crime or disease might be attributable to random fluctuation, or they might be due to an important deviation from the baseline process that produces the regional values. This paper addresses the situation where a series of such maps are observed over time, and it is of interest to detect statistically significant deviations between the observed and expected peaks as quickly as possible. The Gumbel distribution is used as a model for the statistical distribution of extreme values; this distribution does not require the underlying distributions of regional values to be either normal, known, or identical. Cumulative sum surveillance methods are used to monitor these Gumbel variates, and these methods are also extended for use when monitoring smoothed regional values (where the quantity monitored is a weighted sum of values in the immediate geographical neighborhood). The new methods are illustrated by using data on breast cancer mortality for the 217 counties of the northeastern United States, and prostate cancer mortality for the entire United States, during the period 1968-1998.The research assistance of Ikuho Yamada is gratefully acknowledged. I also am grateful for the support of Grant 1R01 ES09816-01 from the National Institutes of Health, the support of National Cancer Institute Grant R01 CA92693-0, and the helpful comments made by the referees 相似文献
9.
Multicollinearity and correlation among local regression coefficients in geographically weighted regression 总被引：5，自引：3，他引：5
Present methodological research on geographically weighted regression (GWR) focuses primarily on extensions of the basic GWR model, while ignoring well-established diagnostics tests commonly used in standard global regression analysis. This paper investigates multicollinearity issues surrounding the local GWR coefficients at a single location and the overall correlation between GWR coefficients associated with two different exogenous variables. Results indicate that the local regression coefficients are potentially collinear even if the underlying exogenous variables in the data generating process are uncorrelated. Based on these findings, applied GWR research should practice caution in substantively interpreting the spatial patterns of local GWR coefficients. An empirical disease-mapping example is used to motivate the GWR multicollinearity problem. Controlled experiments are performed to systematically explore coefficient dependency issues in GWR. These experiments specify global models that use eigenvectors from a spatial link matrix as exogenous variables.This study was supported by grant number 1 R1 CA95982-01, Geographic-Based Research in Cancer Control and Epidermiology, from the National Cancer Institute. The author thank the anonymous reviewers and the editor for their helpful comments. 相似文献
10.
A new orthometric correction (OC) formula is presented and tested with various mean gravity reduction methods using leveling, gravity, elevation, and density data. For mean gravity computations, the Helmert method, a modified Helmert method with variable density and gravity anomaly gradient, and a modified Mader method were used. An improved method of terrain correction computation based on Gaussian quadrature is used in the modified Mader method. These methods produce different results and yield OCs that are greater than 10 cm between adjacent benchmarks (separated by 2 km) at elevations over 3000 m. Applying OC reduces misclosures at closed leveling circuits and improves the results of leveling network adjustments. Variable density yields variation of OC at millimeter level everywhere, while gravity anomaly gradient introduces variation of OC of greater than 10 cm at higher elevations, suggesting that these quantities must be considered in OC. The modified Mader method is recommended for computing OC.Acknowledgments.This study is supported by the Ministry of the Interior (MOI), Taiwan, under the project `Measuring gravity on first-order benchmarks'. The authors are grateful to F.S. Ning and his colleagues at BSB (Base Survey Battalion) for their precision work in collecting gravity data, and to R. Forsberg for the terrain correction program. They also thank the Institute of Agricultural and Forestry Aerial Survey for elevation data and MOI for leveling data. Dr. Will Featherstone and three anonymous reviewers are thanked for their constructive comments. 相似文献
11.
Y. H. Zhou X. H. Yan X. L. Ding X. H. Liao D. W. Zheng W. T. Liu J. Y. Pan M. Q. Fang M. X. He 《Journal of Geodesy》2004,78(1-2):109-113
Changes in the annual variation of the Earths polar motion are found to be largely caused by the variation of the atmospheric angular momentum (AAM). Recent simulation results of oceanic general circulation models further suggest global oceanic effects on the annual polar motion in addition to the atmosphere. In comparison with previous model studies of global oceanic effects, this research particularly singles out a large-scale ocean anomaly and investigates its effect on the annual polar motion, determined from satellite observations of the movement of the Western Pacific Warm Pool (WPWP). Although the scale of the warm pool is much smaller than that of the solid Earth, analysis of the non-atmospheric polar motion excitation has shown that the WPWP contributes non-negligibly to the annual polar motion. The analysis consists of over 30 years of WPWP data (1970–2000) and shows values of polar motion excitation for the x-component of (2.5 mas, –79°) and for the y-component of (0.6 mas, 173°). Comparison of this result with the total geodetic non-atmospheric polar motion excitation of (10.3 mas, 59°) for the x-component and (10.6 mas, 62°) for the y-component shows the significance of the WPWP. Changes in the Earths polar motion have attracted significant attention, not only because it is an important geodetic issue, but also because it has significant value as a global measure of variations within the hydrosphere, atmosphere, cryosphere, and solid Earth, and hence global changes.Tel: 86–21–64386191 Fax: 86–21–64384618Acknowledgments. The authors are grateful to Dr. R. Gross (JPL) and two anonymous reviewers for providing invaluable comments. They also thank Dr. J.L. Chen (CSR) for helpful discussions. Y. Zhou, D. Zheng and X. Liao were supported by the National Natural Science Foundation of China (10273018, 10133010) and Key Project of Chinese Academy of Sciences (KJCX2-SW-T1). X-H. Yan was supported by the National Aeronautics and Space Administration (NASA) through Grant NAG5–12745, and by the National Science Foundation (NSF) through the Presidential Faculty Fellow award to X-H. Yan (OCE-9453499). W.T. Liu was supported by the NASA Physical Oceanography Program. 相似文献
12.
Integrating Web-based GIS and image processing tools for environmental monitoring and natural resource management 总被引：1，自引：1，他引：0
The combined powers of Web-based geographic information systems (GIS) and on-line remote sensing tools can significantly reduce the high cost and labor associated with environmental monitoring and natural resource management. This paper introduces an integrated Web-based GIS architecture by combining three levels of geographic information services (GIServices): data archive, information display, and spatial analysis. A prototype Web site, WGAT (Web-based GIS and Analytic Tools), has been developed to provide easy access of geospatial information and to facilitate Web-based image analysis and change detection capabilities for natural resource managers and regional park rangers. The Web-based integration framework emphasizes user-oriented services, distributed network environments, metadata standards, communication protocols, client/server computation, and ubiquitous access.This paper forms a portion of the Integrated Mobile GIS and Wireless Image Web Services for Environmental Monitoring and Management project supported by NASAs Affiliated Research Center (ARC) at San Diego State University. Funding by the NASA ARC program and matching funds from the San Diego State University Foundation are acknowledged and greatly appreciated. The author wishes to thank John Kaiser, the ARC program coordinator, and Dr. Douglas Stow, the ARC program Principle Investigator, for their coordination efforts on this project. Java programming was provided by Liang Guo, a geography graduate student at San Diego State University. 相似文献
13.
Detecting clusters of disease with R 总被引：2，自引：0，他引：2
V. Gómez-Rubio J. Ferrándiz-Ferragud A. López-Quílez 《Journal of Geographical Systems》2005,7(2):189-206
One of the main concerns of Public Health surveillance is the detection of clusters of disease, i. e., the presence of high incidence rates around a particular location, which usually means a higher risk of suffering from the disease under study (Aylin et al. 1999). Many methods have been proposed for cluster detection, ranging from visual inspection of disease maps to full Bayesian models analysed using MCMC. In this paper we describe the use and implementation, as a package for the R programming language, of several methods which have been widely used in the literature, such as Openshaws GAM, Stones test and others. Although some of the statistics involved in these methods have an asymptotical distribution, bootstrap will be used to estimate their actual sampling distributions.We would like to thank co-editor Dr. Manfred M. Fischer and four anonymous referees for their suggestions and comments to improve this paper. The help of Dr. Roger Bivand has also been of great value. Furthermore, this work has been partly funded by Consellería de Sanitat and EUROHEIS Project (code SI2.329122, 2001CVG2-604). The authors wish to express their regard and gratitude to Prof. Juan Ferrándiz-Ferragud who died during the revision of this paper. Juan was the main researcher of the Spanish EUROHEIS group, and was really a master for all the people involved in the project. 相似文献
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15.
This paper elucidates the manner in which users of an online decision support system respond to spatially distributed data when assessing the solution to environmental risks, specifically, nuclear waste disposal. It presents tests for revealing whether users are responding to geographical data and whether they are influenced by their home location (Not in My Back Yard – style behavior). The tests specifically cope with problems associated with testing home-to-risk distances where both locations are constrained by the shape of the landmass available. In addition, we detail the users wider feelings towards such a system, and reflect upon the possibilities such systems offer for participatory democracy initiatives.The authors would like to thank the two anonymous referees for their helpful and generous comments. 相似文献
16.
《Geoscience and Remote Sensing Letters, IEEE》2009,6(4):649-652
17.
Peiliang Xu 《Journal of Geodesy》2003,77(5-6):247-256
The previous work of Xu on discrete nonlinear filtering is extended to continuous systems. The new results are summarized as follows: (1) a second-order unbiased prediction of the true state governed by a vector stochastic differential equation is worked out; (2) a set of coupled differential equations for a new truncated second-order nonlinear filter and its variance–covariance matrix are derived from the frequentist point of view. The new filter is proved to be unbiased to the second-order approximation; and, most importantly, (3) comparison of the new filtering and accuracy results with the literature on nonlinear filtering has indicated that more than 40 years of nonlinear filtering of continuous systems may have foundational problems.Acknowledgments.This work is supported by a Grant-in-Aid for Scientific Research (C13640422). The author thanks Prof J.A.R. Blais, Prof A. Dermanis and Prof B. Schaffrin for their constructive comments. 相似文献
18.
In order to investigate the ability of numerical techniques in computing seismic displacement fields, a forward problem of dislocation theory is first solved by both analytical and numerical techniques. Convergency of the numerical solution and a comparison with the results of a well-known analytical solution are presented for a particular problem. The results are then used when the numerical technique is applied to the same problem without any information on the dislocation source. The latter results may be applied in an inverse dislocation problem. Numerical techniques are in particular expected to be flexible enough to (1) include internal discontinuities, (2) apply geodetic observations as boundary conditions and (3) model lateral, in addition to radial, material heterogeneities. A model with lateral variation of elastic parameters is considered in the last problem.
Acknowledgments.The authors are most grateful to Y. Okada, National Research Institute for Earth Science and Disaster Prevention, Japan, for providing the Fortran code of his analytical solution. 相似文献
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For ages, links between environment, climate and their impacts on human health have been observed and studied. Research to improve our understanding of environmental key determinants of infectious diseases can provide innovative information for adaptation strategies and lead to new tools optimizing surveillance, vector control measures, and disease prevention. As earth observation satellites can measure meteorological and environmental parameters, NASA and CNES have separately engaged in an innovative use of their earth observation infrastructure development programs: space tools addressing public health. As NASA and CNES have fruitful cooperation for satellite development missions for years, both health programs have proposed to explore a new area of collaboration: satellites addressing health issues. As members of international organizations, NASA and CNES could promote their common views towards the Group on Earth Observations (GEO) Community of Practice for Health & Environment and the Committee on Earth Observation Satellites (CEOS) Societal Benefit Area on Health. 相似文献