Eugene (Gene) J. Lengerich 
Certificate Program in GIS


 

Similar to many people, my personal and professional goals are to make a difference in the lives of others.  Professionally, I am a cancer epidemiologist and a teacher.  My research interests include estimating and reducing the incidence of cancer  among persons who are medically underserved, creating tools and methods that will enable health agencies to monitor the incidence of chronic diseases, and identifying causes of cancer.  Currently, I conduct intervention research on the incidence of cancer in Appalachia and the characteristics of a model GIS/Atlas system state departments of health.  I also teach epidemiological research methods to graduate students and physicians.


 

Geography 5121 Projects



Project 1: Coordinates and Map Projections
I particularly liked the definition that described GIS as a 'decision-support tool' (Dibase, 2004).  Maybe I like this because it is similar to epidemiology which is the study of the cause and distribution of disease AND the application of efforts to reduce that disease.  Epidemiological science is supported by and supports efforts to improve health. 

Project 2: Mapping the Census
I learned to create, download and post Census maps.  I also learned that data tables for specific geographic areas are an important adjunct in examining changes in georeferenced data.

Project 3: Investigating Geographic Data
I learned about the federal structure to create a data warehouse with state nodes for spatial data. Unfortunately, health status and outcome data are not widely available through this infrastructure.

 

Geography 5222 Projects


Project 1: Decision Support with a GIS
I was introduced to ARCMap, selection by layers and attributes.  Though the activity of the exercise was repetative, I found that the exercise reinforced the activity. 

Project 2: Manipulating and Summarizing Attribute Data

In this lesson, I learned to do many tasks with maps and attribute tables.  These tasks included joining layers and tables, defining, calculating and displaying new variables.

Property Destroyed ($) = (the total number of houses, apartments and mobile homes destroyed) * (median value of housing unit).  The map and legend indicate that the value of property destroyed ranged from $54000 to $6.3 million.  Oklahoma County (FIPS 40109) had the greatest property value destroyed.

Property Destroyed (Number) = (the total number of houses, apartments and mobile homes destroyed).  The map and legend indicate that the total number of living units destroyed ranged from 2 to 1182.  Oklahoma County (FIPS 40109) had the greatest number destroyed.

Property Damaged (Number) = (the total number of houses, apartments and mobile homes damaged).  The map and legend indicate that the total number of living units destroyed ranged from 3 to 3411.  Oklahoma County (FIPS 40109) had the greatest number damaged.

Housing Density (the total number of houses per square) - (the total number of houses, apartments and mobile homes) / (area of the county in square miles).  The map and legend indicate that the density ranged from 5 to 385 units per square mile.  Oklahoma County (FIPS 40109) had the density of housing.

Project 3: Analyzing Spatial Data in GIS
This exercise was limited from real world planning because it assumed that other facilities and features were not affected by the tornadoes.  For example, the tornadoes may cause flooding, loss of electricity, fires, and other issues that would limit the access to and utility of emergency sites.   In addition, population density is calculated under the assumption that the population count is accurate and that the population is evenly distributed across the area.  Seasonal changes in the population may occur (e.g., during vacations and holidays) and daily changes may occur (e.g., work and school attendance).  In addition, this calculation assumes that the entire area is affected by the tornado.  These differences in the population and area may affect the relief priority scale.

Other data layers would be particular helpful.  These layers would include transportation, sewage, public facilities (shopping centers, stadiums), agricultural areas, health care providers.  These layers would improve the results by providing additional information about the potential impact of the torndoe to human health, to buildings and facilities, and emergency access and health care.

Project 4: Address Geocoding
This lesson provided the opportunity to address match data in a database, and to identify and indicate specific address sites in ArcMap.  We identified and modified the addresses that did not match with the addresses in the address locator.  This technique updated information, making the data (at least appear) to be more accurate and complete.  However, addresses that were updated may, in fact, have been initially correct.  In addition, the addresses that matched initially may have been incorrect.  Consequently, the technique of address matching is not an exact science despite the potential to complete it.

 

Geography 5223 Projects


 

Geography 5224 Projects