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23rd ACM SIGspatial International Conference on Advances in Geographic Information Systems (ACM SIGspatial GIS)

作者： Li, Xun Anselin, Luc Koschinsky, Julia Arizona State Univ Sch Geog Sci & Urban Planning Tempe AZ 85287 USA

ISBN: (纸本)9781450339674

Cloud mapping platforms, such as Google Maps, CartoDB, MapZen, and the like have become powerful alternatives to traditional desktop-based mapping and GIS applications. However, unlike their desktop counterparts, web mapping platforms typically do not contain any but the most basic spatial analytical functionality. In this paper, we introduce GeoDa-Web, a cloud mapping platform that integrates spatial analytics and web mapping. The platform enables researchers to retrieve spatial data from the cloud, conduct spatial analysis in the cloud, visualize results using cloud mapping, and publish maps and plots to social media in a user-friendly way. It leverages the code base from the widely used GeoDa desktop software for spatial data exploration and the PySAL Python library of spatial analytical functions. We outline the architecture, discuss the implementation and illustrate the functionality of GeoDa-Web.

关键词： spatial analytics CyberGIS web mapping exploratory spatial data analysis spatial regression

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A spatial analysis OF PRECARIOUS FORMS OF EMPLOYMENT IN FRANCE

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TIJDSCHRIFT VOOR ECONOMISCHE EN SOCIALE GEOGRAFIE 2015年第5期106卷 536-555页

作者： Jacquemond, Marc Breau, Sebastien McGill Univ Dept Geog Montreal PQ H3A 0B9 Canada

This paper provides the first detailed analysis of the spatial dimensions of precarious employment across the French territory. We find that different forms of precarious employment exhibit different spatial patterns. The most striking locational pattern is shown by fixed-term contracts and part-time work where we observe clusters of high levels of precarious employment primarily in southern regions. Northern regions, in contrast, are characterised by clusters of low levels of precarious employment. We also find that precarious employment is predominantly a rural phenomenon with the exception of temporary (interim) work which displays higher average levels in urban communes. Finally, modelling results suggest that the geographical distribution of precarious forms of employment is linked to factors such as the unemployment rate, the industrial composition of a region, gender and the structure of family households.

关键词： Precarious employment France communes exploratory spatial data analysis

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Cyanobacteria blooms and non-alcoholic liver disease: evidence from a county level ecological study in the United States

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ENVIRONMENTAL HEALTH 2015年第1期14卷 41-41页

作者： Zhang, Feng Lee, Jiyoung Liang, Song Shum, C. K. Ohio State Univ Environm Sci Grad Program Columbus OH 43210 USA Ohio State Univ Coll Publ Hlth Div Environm Hlth Sci Columbus OH 43210 USA Ohio State Univ Dept Food Sci & Technol Columbus OH 43210 USA Univ Florida Coll Publ Hlth & Hlth Profess Dept Environm & Global Hlth Gainesville FL 32610 USA Univ Florida Emerging Pathogens Inst Gainesville FL 32610 USA Ohio State Univ Sch Earth Sci Div Geodet Sci Columbus OH 43210 USA Chinese Acad Sci Inst Geodesy & Geophys Wuhan Peoples R China

Background: Harmful cyanobacterial blooms present a global threat to human health. There is evidence suggesting that cyanobacterial toxins can cause liver damage and cancer. However, because there is little epidemiologic research on the effects of these toxins in humans, the excess risk of liver disease remains uncertain. The purpose of this study is to estimate the spatial distribution of cyanobacterial blooms in the United States and to conduct a Bayesian statistical analysis to test the hypothesis that contamination from cyanobacterial blooms is a potential risk factor for non-alcoholic liver disease. Methods: An ecological study design was employed, in which county-specific gender and age standardized mortality rates (SMR) of non-alcoholic liver disease in the United States were computed between 1999 and 2010. Bloom coverage maps were produced based on estimated phycocyanin levels from MERIS (Medium Resolution Imaging Spectrometer) water color imageries from 08/01/2005 to 09/30/2005. A scan statistical tool was used to identify significant clusters of death from non-alcoholic liver disease. A map of local indicator of spatial association (LISA) clusters and a Bayesian spatial regression model were used to analyze the relationship between cyanobacterial bloom coverage and death from non-alcoholic liver disease. Results: Cyanobacterial blooms were found to be widely spread in the United States, including coastal areas;62% of the counties (1949 out of 3109) showed signs of cyanobacterial blooms measured with MERIS. Significant clusters of deaths attributable to non-alcoholic liver disease were identified in the coastal areas impacted by cyanobacterial blooms. Bayesian regression analysis showed that bloom coverage was significantly related to the risk of non-alcoholic liver disease death. The risk from non-alcoholic liver disease increased by 0.3% (95% CI, 0.1% to 0.5%) with each 1% increase in bloom coverage in the affected county after adjusting for age, gender,

关键词： Cyanobacterial Bloom exploratory spatial data analysis Cyanobacterial Toxin spatial Random Effect Toxic Cyanobacterial Bloom

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Monitoring county-level chlamydia incidence in Texas, 2004-2005: application of empirical Bayesian smoothing and exploratory spatial data analysis (ESDA) methods

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INTERNATIONAL JOURNAL OF HEALTH GEOGRAPHICS 2009年第1期8卷 12-12页

作者： Owusu-Edusei, Kwame, Jr. Owens, Chantelle J. Ctr Dis Control & Prevent Div STD Prevent Atlanta GA 30333 USA

Background: Chlamydia continues to be the most prevalent disease in the United States. Effective spatial monitoring of chlamydia incidence is important for successful implementation of control and prevention programs. The objective of this study is to apply Bayesian smoothing and exploratory spatial data analysis (ESDA) methods to monitor Texas county-level chlamydia incidence rates by examining spatiotemporal patterns. We used county-level data on chlamydia incidence (for all ages, gender and races) from the National Electronic Telecommunications System for Surveillance (NETSS) for 2004 and 2005. Results: Bayesian-smoothed chlamydia incidence rates were spatially dependent both in levels and in relative changes. Erath county had significantly (p < 0.05) higher smoothed rates (> 300 cases per 100,000 residents) than its contiguous neighbors (195 or less) in both years. Gaines county experienced the highest relative increase in smoothed rates (173% - 139 to 379). The relative change in smoothed chlamydia rates in Newton county was significantly (p < 0.05) higher than its contiguous neighbors. Conclusion: Bayesian smoothing and ESDA methods can assist programs in using chlamydia surveillance data to identify outliers, as well as relevant changes in chlamydia incidence in specific geographic units. Secondly, it may also indirectly help in assessing existing differences and changes in chlamydia surveillance systems over time.

关键词： spatial Dependence Local Outlier Chlamydia Screening exploratory spatial data analysis Monte Carlo Randomization

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FluMapper: A cyberGIS application for interactive analysis of massive location-based social media

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2014年第13期26卷 2253-2265页

作者： Padmanabhan, Anand Wang, Shaowen Cao, Guofeng Hwang, Myunghwa Zhang, Zhenhua Gao, Yizhao Soltani, Kiumars Liu, Yan Univ Illinois CyberInfrastruct & Geospatial Informat Lab Champaign IL 61820 USA Univ Illinois Dept Geog & Geog Informat Sci Champaign IL USA Univ Illinois CyberGIS Ctr Adv Digital & Spatial Studies Champaign IL USA Univ Illinois Natl Ctr Supercomp Applicat NCSA Champaign IL USA Univ Illinois Illinois Informat Inst Champaign IL USA Texas Tech Univ Dept Geosci Lubbok TX USA Chinese Acad Sci Comp Network Informat Ctr Beijing Peoples R China

Social media have experienced a spectacular rise in popularity, attracting hundreds of millions of users and generating unprecedented amount of content that increasingly contain location and place information. Collectively, the massive location information in these data provides an excellent opportunity to better understand many geographic phenomena and geospatial dynamics in a timely fashion. Recent studies capitalizing on social networking and media data show significant societal impacts in many areas including prediction of stock market and infectious disease surveillance. However, because location-based social media data are often massive, generated dynamically, and unstructured, significant computation, data, and visualization challenges need to be resolved. This research aims to demonstrate the use of massive social media data to interactively analyze spatiotemporal events across spatial and temporal scales, by establishing a data-driven framework using cyberGISgeographic information systems (GIS) based on advanced cyberinfrastructureto resolve aforementioned challenges. Specifically, FluMapperan application on the CyberGIS Gatewayis employed as a case study to demonstrate the data-driven framework and seamless integration of massive location-based social media data and spatial analytical services within the online problem solving environment of the Gateway. FluMapper presents integrated results from two complementary spatial analyses: (i) an interactive exploration of spatial distribution of flu risk and (ii) dynamic mapping of movement patterns, across multiple spatial, and temporal scales. The seamless integration of these two analyses through the framework illustrates the potential of cyberGIS to resolve the compute and data challenges of analyzing near real-time social media data in an efficient and scalable manner and to support interactive visualization. Copyright (c) 2014 John Wiley & Sons, Ltd.

关键词： CyberGIS data-driven analytics social media exploratory spatial data analysis

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exploratory Space-time analysis of Inbound Tourism Flows to China Cities

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INTERNATIONAL JOURNAL OF TOURISM RESEARCH 2014年第3期16卷 303-312页

作者： Yang Xing-zhu Wang Qun Anhui Normal Univ Coll Tourism Wuhu 241002 Peoples R China

The integration of space and time generates much closer interactions between geography and other social sciences in general while providing new perspectives for the role of geography in tourism flow studies. This paper aims to apply exploratory space-time analysis to provide insights into inbound tourism flow patterns in China's cities over the period of 2000-2009 using city-level Geographical Information System datasets. First, this paper ascertains that there exists geographic neighborhood effect at city level by testifying significantly positive spatial autocorrelation. The hot spots and temporal stability are identified. The hot spots are locally concentrated in metropolitan areas. Local Markov matrix has also shown significant transitions with negative or positive influence of geographic neighbors upon a city. Specifically, three-dimensional surface is created to visualize tourism flows. The spatial inequalities have the pattern of 'the east more dense than the west, the south more dense than the north'. There simultaneously exist spatial agglomeration and spatial dispersion. The intensity of spatial agglomeration has become stronger. At the same time, smaller peaks of tourism flow centers developed around the main cities and spread toward surrounding cities. These potential tourism flow centers have gradually emerged and grown larger. Furthermore, the space-time covariance matrix uncovers correlation, which shows strong regional integration over years. Eight hundred and ninety links are identified and visualized. Two hundred and sixty nine links forming 10 spatial clusters represent strong positive correlation. One hundred and thirty-four links are negative correlation, which is about 15.06 per cent of all links. In conclusion, our comprehensive evidences offer deeper insights and have important policy implications. These enable the tourism-oriented governmental agencies, as well as the tourism industry professionals, to better understand the changes of inboun

关键词： surface visualization space-time covariance matrix inbound tourism flows exploratory spatial data analysis China's cities

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spatial Patterns of Population Growth and Social Indicators' Change in Korea : an exploratory spatial data analysis

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INTERNATIONAL JOURNAL OF URBAN SCIENCES 2008年第2期12卷 61-72页

作者： Bae, Yujin Yoon, Minkyoung Kim, Euijune Seoul Natl Univ Dept Agr Econ & Rural Dev Reg Informat Seoul South Korea

The purpose of this paper is to identify regional concentration in terms of population and social indicators such as employment and infrastructure, at a disaggregated level using the exploratory spatial data analysis (ESDA). Through an investigation of the change of Moran-I in 1995-2007, we found two phenomena, dramatic deconcentmtion in 1998, and gradually increasing concentration after 1999 due to the IMF financial crisis and its recovery pace. analysis of local spatial autocorrelation revealed a concentration of regions with positive population growth in SMA and near-SMA and that with negative population growth in the south of Gangwon. Gyeongbuk and the midst of Jeolla in 2000-2005. The distribution of employment growth follows the spatial patterns of population growth among various social indicators. We can conclude that the concentration of population spread out over SMA and the gap of population between growing regions and declining ones widened after the financial crisis. The gap of in population numbers between growing and declining regions is not expected to be reduced within a short period due to simultaneous employment and population growth and past regulatory policies in SMA cannot achieve population deconcentration.

关键词： population concentration spatial patterns exploratory spatial data analysis spatial autocorrelation

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Changing Rural Development Inequality in Jilin Province, Northeast China

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Chinese Geographical Science 2013年第5期23卷 620-633页

作者： CHENG Yeqing WANG Yanfei WANG Zheye LUO Xiaolong Northeast Institute of Geography and Agroecology Chinese Academy of Sciences University of Chinese Academy of Sciences Department of Urban Planning and Design Nanjing University

Rural development inequality is an important practical issue during the course of full establishment of a ′moderately well-off society′ in modern China,and the objective understanding and evaluation of the status and regional inequality of rural development can provide scientific basis for ′building a new countryside′ and coordination development of rural-urban *** on the county-level data of 2000,2005 and 2009,this paper examines the rural development inequality of Jilin Province in Northeast China by establishing a rural development *** spatio-temporal dynamic patterns and domain factors are discussed by using the method of exploratory spatial data analysis and multi-regression *** results are shown as ***,most of the counties were in lower development level,which accounted for 58.3%,62.5% and 66.7% of the total counties in 2000,2005 and 2009,*** characteristics of spatial inequality were very obvious at county *** example,rural development level of Changchun Proper and the proper of seven prefecture-level cities were much higher than that of the surrounding *** counties in the eastern and northern Jilin Province were the lowest regions of rural development level,while the middle counties were the rapid growth areas in rural ***,Moran′s I of rural development index(RDI) was 0.01,–0.16 and –0.06 in 2000,2005 and 2009,respectively,which indicated that spatial agglomeration of RDI was not obvious in Jilin Province,and took on the characteristic of random *** counties of both the units and its adjacent units have higher development level(HH) were transferred from the western areas to the eastern areas,while the countries of both the units and its adjacent units have lower development level(LL) were diffused from the eastern to middle and western Jilin ***,the result of multi-regression analysis showed that the improvement of agricultural production condition,development

关键词： rural development index exploratory spatial data analysis multi-regression model Jilin Province

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Mapping travelers' attitudes: does space matter?

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JOURNAL OF TRANSPORT GEOGRAPHY 2013年 26卷 117-125页

作者： Paez, Antonio McMaster Univ Sch Geog & Earth Sci Hamilton ON L8S 4K1 Canada

exploratory spatial data analysis of attitudinal variables can provide useful information about underlying behavioral processes. In this paper, elemental symbol mapping and spatial association analysis techniques are applied to travelers' attitudes. Attitudinal data, drawn from a recent travel survey conducted in McMaster University (Hamilton, Canada) among staff, students, and faculty, are analyzed. The place of residence of the respondents is geocoded in order to map the responses, and the spatial pattern of the qualitative/ordinal attitudinal variables is analyzed using the Q(m) statistic. analysis of a selection of variables shows how some attitudes appear to develop independently from the local environments, whereas others are related to a preference towards certain types of local environments or social aspects of the local environment, which suggests underlying processes of self-selection or adaptation. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Travel behavior exploratory spatial data analysis Attitudes spatial association Q statistic

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Concentration of Manufacturing and Service Sector Activities in Italy: Accounting for spatial Dependence and Firm Size Distribution

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REGIONAL STUDIES 2013年第3期47卷 405-418页

作者： De Dominicis, Laura Arbia, Giuseppe De Groot, Henri L. F. JRC IPTS European Commiss E-41092 Seville Spain Univ G DAnnunzio I-65127 Pescara Italy Vrije Univ Amsterdam Dept Spatial Econ NL-1081 HV Amsterdam Netherlands Tinbergen Inst NL-1082 MS Amsterdam Netherlands Ecorys NEI NL-3067 GG Rotterdam Netherlands

De Dominicis L., Arbia G. and De Groot H. L. F. Concentration of manufacturing and service sector activities in Italy: accounting for spatial dependence and firm size distribution, Regional Studies. Empirical analysis of the spatial distribution of economic activity on a discrete space is based on measures that suffer from a series of drawbacks. A methodological advance is proposed here in two respects. First, the analysis is extended to take spatial dependence explicitly into account. Second, differences in the size distribution of firms between territorial units are controlled for. Using data for Italy, exploratory spatial data analysis is applied to identify sectoral location patterns in both the manufacturing industry as well as the business services. It is found that large differences prevail in the geographical concentration of production across sectors.

关键词： exploratory spatial data analysis Firm size distribution Geographic concentration spatial autocorrelation Italy C12 R12 R30

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