Yongmei Lu

California State University, San Marcos, San Marcos, California, United States

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Publications (12)10.63 Total impact

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    ABSTRACT: The purpose of this research is to illustrate a three-component operationalization of the Hazards-of-Place Model (HPM) by integrating urban infrastructure (using the capacity of road networks to facilitate evacuation as an example) to describe place vulnerability. This approach is informed by the HPM first articulated by Cutter (Vulnerability to environmental hazards. Prog Hum Geog. 20:529–39, 1996). The HPM is a conceptual framework through which place vulnerability is defined as a combination of social characteristics (expressed by selected socioeconomic demographics) and geophysical risk (expressed by probabilities of occurrence). Using a geographic information system (GIS), the study models the capacity of road networks to facilitate evacuation and used it as an example of urban infrastructure within which place vulnerability occurs. The output of the model was integrated with a geophysical risk layer and social vulnerability index layer as components for assessing the overall place vulnerability. The three-component approach to operationalizing the HPM provides a detailed and nuanced illustration of place-based vulnerability. As an applied tool, the three-component approach presents emergency planners with a new method of integrating diverse geographic data when illustrating spatial patterns of vulnerability to environmental hazards.
    Geomatics, Natural Hazards and Risk 12/2013; 6(3):1-17. DOI:10.1080/19475705.2013.832406 · 0.62 Impact Factor
  • Cartographica The International Journal for Geographic Information and Geovisualization 01/2012; 47(3):168-178. DOI:10.3138/carto.47.3.1112
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    ABSTRACT: This paper reports a study examining the association between colorectal cancer (CRC) survival and access to healthcare in Texas using data from the Texas cancer registry. We geo-referenced the data to the census tract level and used an enhanced 2-step floating catchment area method and factor analysis to estimate people's spatial and non-spatial access to healthcare. In addition, Cox proportional hazard regression was employed to assess the influence of different factors on CRC survival, and a spatial scan statistic was used to investigate the geographic disparity of CRC survival and the influence of access to healthcare. The analyses revealed that Hispanics, non-Hispanic blacks, and residents from several regions in Texas were more likely to die from CRC than others. Disadvantaged population groups based on factors rather than spatial access had an increased risk of CRC-specific mortality. Spatial access to oncologists has a significant association with CRC survival in non-urban areas but not in urban areas. Geographic disparities of CRC survival were largely influenced by factors rather than spatial access to healthcare.
    Health & Place 11/2011; 18(2):321-9. DOI:10.1016/j.healthplace.2011.10.007 · 2.44 Impact Factor
  • Shing Lin, Yongmei Lu
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    ABSTRACT: This paper reports on the investigation of the spatial patterns and variations of adverse health effects of ozone pollution on childhood respiratory diseases in Houston, Texas. The study period is June to September of 2001. No significant global relationship exists between ozone pollution and prevalence of childhood respiratory diseases. However, geographically weighted regression (GWR) analysis reveals spatially varied adverse health effect. With the guidance from GWR results, the association between ozone pollution and childhood respiratory disease prevalence is proved to be significant in three sub-regions. Moreover, spatial regression analysis suggests the presence of spatial dependence of the prevalence of childhood respiratory diseases.The spatial variation of the relationship between ozone pollution and childhood respiratory disease prevalence indicates health effects of confounding or intervening factors. The spatial dependency of disease prevalence is related to both the spatial patterns of pollution and those of confounding factors. The findings call for future investigation to examine the factors that might be working together with or against ozone pollution when health effects are concerned. For health practice and management, a set of neighborhood-specific policy, practice, and resource allocation strategies need to be developed to minimize the adverse health effects of ozone pollution.
    12/2009; 15:127-140. DOI:10.1080/19475680903271133
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    ABSTRACT: The purpose of this article is to describe a capstone course in undergraduate student geographical research in which GIS and other geospatial tools were used to teach undergraduate students basic geographical principles. The course uses the “cooperative learning” pedagogical approach to address one of a number of client-supplied research projects, chosen on the basis of logistical difficulty, time, student ability, and project importance. In the connection of primary data with existing data, students confronted a number of important research issues such as mapping ethics, database design and management, time management, group dynamics, and research limitations.
    Journal of Geography 11/2007; 106(6):285-295. DOI:10.1080/00221340701839956 · 0.87 Impact Factor
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    ABSTRACT: Chagas disease is endemic and is recognized as a major health problem in many Latin American countries. Despite the parallels between socio-economic and environmental conditions in Texas and much of Latin America, Chagas disease is not a notifiable human disease in Texas. Based on extensive review of related literature, this paper seeks to recognize the evidence that Chagas Disease is endemic to Texas but the epidemiological, parasitological and entomological patterns of Chagas disease in Texas are both different from and parallel to other endemic regions. We find that with a growing immigrant human reservoir, the epidemiological differences may be reduced and result in increasing incidence of the disease. Chagas disease should be recognized as an emerging disease among both immigrant and indigenous populations. Without proper actions, Chagas disease will place increasing burden on the health care system. Current medical treatments consist of chemotherapies that carry the risk of serious side effects; curing the potentially fatal disease remains equivocal. Therefore, as shown in South America, prevention is paramount and can be successfully achieved through intervention and education. We conclude that biogeographical research is needed to (1) distinguish the dynamic evolution of the agent-vector-host system, (2) document locations with greater risk and identify mechanisms responsible for observed changes in risk, and (3) assist in developing a model for Triatomid vector-borne disease in states like Texas where the disease is both endemic and may be carried by a sizeable immigrant population. Tracking of Chagas disease and planning for appropriate health care services would also be aided by including Chagas disease on the list of reportable diseases for humans.
    Social Science [?] Medicine 08/2007; 65(1):60-79. DOI:10.1016/j.socscimed.2007.02.041 · 2.56 Impact Factor
  • Yongmei Lu, Xuwei Chen
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    ABSTRACT: Many social and economic activities, especially those in urban areas, are subject to location restrictions imposed by existing street networks. To analyze the spatial patterns of these urban activities, the restrictions imposed by the street networks need to be taken into account. K-function is a method commonly used for general point pattern analysis as well as crime pattern study. However, applying the planar K-function to analyze the spatial autocorrelation patterns of urban activities that are typically distributed along streets could result in false alarm problems. Depending on the nature of the urban street networks and the distribution of the urban activities, either positive or negative false alarm might be introduced. Acknowledging that many urban crimes are typically distributed along streets, this paper compares the traditional planar K-function with a network K-function for crime pattern analysis. The patterns of vehicle thefts in San Antonio, Texas are examined as a case study.
    Social Science Research 06/2007; DOI:10.1016/j.ssresearch.2006.05.003 · 1.27 Impact Factor
  • Yongmei Lu
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    ABSTRACT: A series of exploratory analyses of auto thefts in the city of Buffalo are reported and discussed in this paper. With the aid of Geographic Information Systems (GIS) and Exploratory Spatial Data Analysis (ESDA), the spatial clustering of auto thefts in Buffalo is evaluated, the distribution of auto thefts along the streets is examined, and the spatial choice of auto thefts as related to the patterns of socioeconomic activities in the study area is investigated. In addition to the patterns of auto theft hot spots, this study also examines the impact that the distribution of the available vehicles has on auto theft locations. Analyses reveal that locations along the major roads and the roads directly connected to the major roads are at high risk of being targeted by auto thieves. Furthermore, it is concluded that certain types of urban socioeconomic activities are more attractive to the potential auto thieves than others.
    Security Journal 07/2006; 19(3):143-166. DOI:10.1057/palgrave.sj.8350008 · 0.61 Impact Factor
  • Shing Lin, Yongmei Lu
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    ABSTRACT: Abstract Multi-scale effects of spatial autocorrelation may be present in datasets. Given the importance of detecting local non-stationarity in many theoretical as well as applied studies, it is necessary to “remove” the impact of large-scale autocorrelation before common techniques for local pattern analysis are applied. It is proposed in this paper to employ the regionalized range to define spatially varying sub-regions within which the impact of large-scale autocorrelation is minimized and the local patterns can be investigated. A case study is conducted on crime data to detect crime hot spots and cold spots in San Antonio, Texas. The results confirm the necessity of treating the non-stationarity of large-scale spatial autocorrelation prior to any action aiming at detecting local autocorrelation.
    Transactions in GIS 03/2006; 10:301-318. DOI:10.1111/j.1467-9671.2006.00259.x · 0.54 Impact Factor
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    ABSTRACT: While we have seen the wide use of other information technologies in health services and management, the use of geographic information technologies in health related services has been limited so far. Given that location-related data play important roles in many health related services, it is anticipated that geographic information technologies have a lot to offer in helping improve health related services, management, and research. As an example, the authors report the development of a geographic information system (GIS) for Texas-Mexico border disease surveillance and environmental health research. This presentation covers three important aspects in the development of the GIS: (1) the specification of uses and users of the GIS and the associated data, products, and functions; (2) a preliminary design of the data types and formats in the GIS; and (3) a prototype of a GIS-based spatial search tool that can be used to support environmental epidemiology research. In some disease monitoring and environmental epidemiology studies, it is often necessary to perform spatial search to determine the distances between environmental hazardous sites and the locations of cases and controls when distance is used as measure of exposure. The GIS can be used to interactively and automatically determine the distance between any possible pair of environmental hazardous sites and cases/controls. Preliminary results suggest that the prototype GIS is indeed a powerful tool for spatial search when distance is used as a measure of exposure in environmental health research. The reported system should be useful to researchers facing similar situations in disease monitoring and environmental health research.
    Services Systems and Services Management, 2005. Proceedings of ICSSSM '05. 2005 International Conference on; 07/2005
  • Yongmei Lu, Junmei Tang
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    ABSTRACT: A city and its transportation network are both complicated systems. Fractal geometry provides an effective way to describe the complex property of geographical features. This paper uses a modified box-counting method to describe the fractal property of urban transportation networks. Assuming that human settlements of different sizes are all operated by the same growth procedure, this paper investigates the relationship between the mass size of cities and the complexity of their road systems. The results confirm that, as cities grow from small to large, their transportation networks generally become more complicated -- the urban spaces are filled up more densely by city roads and the locations within a city are more accessible. The quantitative relationship identified between the complexity of urban transportation network and city size provides an empirical guide for the planning and policymaking of urban development and road construction.
    Environment and Planning B Planning and Design 11/2004; 31(6):895-911. DOI:10.1068/b3163 · 1.73 Impact Factor
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    Yongmei Lu

Publication Stats

95 Citations
10.63 Total Impact Points

Institutions

  • 2004–2013
    • California State University, San Marcos
      San Marcos, California, United States
  • 2005–2011
    • Texas State University
      • Department of Geography
      San Marcos, Texas, United States
  • 2009
    • Beijing Normal University
      Peping, Beijing, China