Browsing by Author "Martin, Pamela A."

Now showing 1 - 8 of 8
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    A comparison of geocoding baselayers for electronic medical record data analysis
    (2014-01-16) Severns, Christopher Ray; Wilson, Jeffrey S. (Jeffrey Scott), 1967-; Johnson, Daniel P. (Daniel Patrick), 1971-; Martin, Pamela A.
    Identifying spatial and temporal patterns of disease occurrence by mapping the residential locations of affected people can provide information that informs response by public health practitioners and improves understanding in epidemiological research. A common method of locating patients at the individual level is geocoding residential addresses stored in electronic medical records (EMRs) using address matching procedures in a geographic information system (GIS). While the process of geocoding is becoming more common in public health studies, few researchers take the time to examine the effects of using different address databases on match rate and positional accuracy of the geocoded results. This research examined and compared accuracy and match rate resulting from four commonly-used geocoding databases applied to sample of 59,341 subjects residing in and around Marion County/ Indianapolis, IN. The results are intended to inform researchers on the benefits and downsides to their selection of a database to geocode patient addresses in EMRs.
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    The correlation of sea surface temperatures, sea level pressure and vertical wind shear with ten tropical cyclones between 1981-2010
    (2013-11-12) Compton, Andrea Jean; Martin, Pamela A.; Johnson, Daniel P. (Daniel Patrick), 1971-; Wilson, Jeffrey S. (Jeffrey Scott), 1967-
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    The effects of potential changes in United States beef production on global grazing systems and greenhouse gas emissions
    (Office of the Vice Chancellor for Research, 2013-04-05) Dumortier, Jerome; Hayes, Dermot J.; Carriquiry, Miguel; Dong, Fengzia; Du, Xiaodong; Elobeid, Amani; Fabiosa, Jacinto F.; Martin, Pamela A.; Mulik, Kranti
    With climate change becoming an increasingly pressing issue together with a world population of 7 billion people in 2011, significant pressure is put on global agriculture and forestry. Although treated separately in national GHG inventories, there is little doubt that both categories are closely linked and climate policies targeting agriculture will have spillover effects on forestry and vice versa. Hence, the implementation of large-scale agricultural policies is prone to unintended consequences. For this poster, we analyze the hypothesis that a reduction of cattle in the U.S. causes a net increase in GHG emissions on a global scale. We couple a global agricultural production and trade model with a greenhouse gas model to assess leakage associated with modified beef production in the United States. The effects on emissions from agricultural production (i.e., methane and nitrous oxide emissions from livestock and crop management) as well as from land-use change, especially grazing system, are assessed. We find that a reduction of U.S. beef production induces net carbon emissions from global land-use change ranging from 37 to 85 kg CO2-equivalent per kg of beef annualized over 20 years. The increase in emissions is caused by an inelastic domestic demand as well as more land-intensive cattle production systems internationally. Changes in livestock production systems such as increasing stocking rate could partially offset emission increases from pasture expansion. In addition, net emissions from enteric fermentation increase because methane emissions per kilogram of beef tend to be higher globally.
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    Identifying enhanced urban heat island convection areas for Indianapolis, Indiana using space-borne thermal remote sensing methods
    (2015-04-02) Boyd, Kelly D.; Johnson, Daniel P.; Wilson, Jeffery S.; Martin, Pamela A.
    Heat is one of the most important factors in our atmosphere for precipitation (thunderstorm) formation. Thermal energy from local urban land-cover is also a common source of heat in the lower atmosphere. This phenomenon is known as the urban heat island effect (UHI) and is identified as a substantial cause to a changing climate in surface weather modification. The proceeding study investigates this connection between the UHI and surface weather using remote sensing platforms A ten-year analysis of the Indianapolis UHI and thunderstorms were studied from the summer months of May, June, July, August and September (MJJAS) from 2002 until 2011. LANDSAT space borne satellite technology and land-surface based weather radar technology was used in this analysis for thunderstorm investigation. Precipitation areas identified from land-based NEXRAD WSR-88D technology were used to identify convection from non-synoptic forcing and non-normal surface diurnal heating scenarios. Only convection appearing from the UHI were studied and analyzed. Results showed twenty-one events over eighteen days with the year 2005 and 2011 having the largest frequency of events. The month of August had the largest concentration with seven events during the late afternoon hours. UHI results showed July had the largest heat island magnitude with April and September having the lowest magnitude in UHI temperatures. Three events of the twenty-one storm paths did not had a significant mean temperature difference in the heat island below the storm reflectivity. The nineteen storm paths that were significant had a warmer area underneath storm path development by an average 6.2°C than surrounding areas. UHI initiation points showed twelve of the twenty-one events having statistically significant differences between 2 km initiation areas and the rest of the study areas. Land-cover results showed low intensity developed areas had the most land-cover type (48%) in the 2km initiation buffer regions.
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    Impact of different bioenergy crops on area allocation and cellulosic ethanol feedstock mix.
    (2013-04) Dumortier, Jerome; Hayes, Dermot J.; Carriquiry, Miguel; Dong, Fengxia; Du, Xiaodong; Elobeid, Amani; Fabiosa, Jacinto F.; Martin, Pamela A.; Mulik, Kranti
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    The Influence of Trust and Attitudes on the Purchase Frequency of Organic Produce
    (Taylor & Francis, 2017) Dumortier, Jerome; Evans, Keith S.; Grebitus, Carola; Martin, Pamela A.; School of Public and Environmental Affairs
    Growth in organic food sales is mainly due to consumers becoming more aware of health issues and environmental concerns. Understanding the drivers of organic consumption is crucial to predict future market outcomes. In this analysis, the authors expand previous research by including general and institutional trust variables in addition to consumer attitudes to examine organic food purchases. Food production is unobservable and hence, consumers need to exhibit trust with respect to organic production and certification. A bivariate ordered probit model applied to U.S. survey data confirms that organic purchases are determined by health, nutrition, and taste. In some cases, general trust and trust in media are statistically significant. Trust in institutions that are involved in the organic certification process is not statistically significant. A hierarchical cluster analysis grouping consumers based on trust and attitudes shows that (dis)trust in the organic certification and supply chain does not hinder organic food market growth.
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    Rivers of the Anthropocene, Phase 1: A Comparative Study of the Ohio and Tyne River Systems
    (Office of the Vice Chancellor for Research, 2013-04-05) Kelly, Jason M.; Martin, Pamela A.; Scarpino, Philip V.
    Rivers of the Anthropocene” addresses a fundamental problem facing scholars and policy makers alike: despite important advances in our understanding of the earth as a system — one in which humans and human systems have become recognized as prime agents in effecting changes to the earth — we have yet to create an approach that brings together scholars of earth systems with scholars of human systems. This is to the detriment of our overall understanding of global ecological change and limits our ability to respond to escalating crises. Without integrating methods from the earth sciences, social sciences, and humanities, scholars of the environment lose important tools in tackling some of the biggest issues facing humanity in the 21st century. As humans continue to play an increasingly significant role in altering their planet, it is incumbent upon environmental scholars to understand the human-environment interface in all its complexities. It is not enough that scientists measure what humans have done or what they can do to shift environmental systems; it is necessary that they work hand-in-hand with specialists in human systems to understand the limits and feedback mechanisms that beliefs, practices, ideologies, social structures, and cultural norms impose on human action. A comparative study of international river systems is a good place to begin building more meaningful bridges across the science-humanities divide, and it addresses the pressing issue of global water insecurity, which 80% of the earth’s population faces. The first stage of “Rivers of the Anthropocene” will create a flexible, interdisciplinary methodological and conceptual framework for examining the human-environment interface, one in which specialists in the earth sciences can learn from the approaches of the humanities and human sciences and vice versa.
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    Spatio-temporal analyses of the distribution of alcohol outlets in California
    (2014) Li, Li; Banerjee, Aniruddha; Bein, Frederick L. (Frederick Louis), 1943-; Lulla, Vijay O.; Martin, Pamela A.
    The objective of this research is to examine the development of the California alcohol outlets over time and the relationship between neighborhood characteristics and densities of the alcohol outlets. Two types of advanced analyses were done after the usual preliminary description of data. Firstly, fixed and random effects linear regression were used for the county panel data across time (1945-2010) with a dummy variable added to capture the change in law regarding limitations on alcohol outlets density. Secondly, a Bayesian spatio-temporal Poisson regression of the census tract panel data was conducted to capture recent availability of population characteristics affecting outlet density. The spatial Conditional Autoregressive model was embedded in the Poisson regression to detect spatial dependency of unexplained variance of alcohol outlet density. The results show that the alcohol outlets density reduced under the limitation law over time. However, it was no more effective in reducing the growth of alcohol outlets after the limitation was modified to be more restrictive. Poorer, higher vacancy rate and lower percentage of Black neighborhoods tend to have higher alcohol outlet density (numbers of alcohol outlets to population ratio) for both on-sale general and off-sale general. Other characteristics like percentage of Hispanics, percentage of Asians, percentage of younger population and median income of adjacency neighbors were associated with densities of on-sale general and off sale general alcohol outlets. Some regions like the San Francisco Bay area and the Greater Los Angeles area have more alcohol outlets than the predictions of neighborhood characteristics included in the model.