Powerpoint Presentation:
http://students.uwf.edu/ldl14/LDL_Napas_Best_Sales_Routes.pptx
Driving Directions:
http://students.uwf.edu/ldl14/NorthwestSalesRoute.pdf
http://students.uwf.edu/ldl14/NortheastSalesRoute.pdf
http://students.uwf.edu/ldl14/SouthSalesRoute.pdf
Wednesday, November 24, 2010
Wednesday, November 17, 2010
Monday, November 8, 2010
Project 4: Prepare
Map produced in the prepare phase of Project 4.
http://students.uwf.edu/ldl14/LDL_Project4_Prepare.pdf
http://students.uwf.edu/ldl14/LDL_Project4_Prepare.pdf
Monday, November 1, 2010
Project 3: Presentation
Below is the link to my Project 3 Presentation.
http://students.uwf.edu/ldl14/LDL_Project 3 Presentation.pptx
http://students.uwf.edu/ldl14/LDL_Project 3 Presentation.pptx
Thursday, October 14, 2010
Monday, October 11, 2010
Project 2: Report
Project 2 Powerpoint presentation on the Marin, CA tree program and proposed city center.
http://students.uwf.edu/ldl14/LDL_Project2_Presentation.pptx
http://students.uwf.edu/ldl14/LDL_Project2_Presentation.pptx
Monday, September 27, 2010
Project 2: Prepare
Monday, September 20, 2010
Analyze and Report: Project 1



This week was a little disorienting for me. I think I got caught up in the amount of data and lost sight of the task. I did what I could and I sort of just turned in what I had. When I did my analysis it was not clear to me what population to target. I think the next weeks should be easier now that I know how its going to work.
Tuesday, September 7, 2010
Week 1: Prepare
Here are my excel tables created for this week:
http://students.uwf.edu/ldl14/Asthma_Data.xlsx
http://students.uwf.edu/ldl14/Demographics_Pop.xlsx
http://students.uwf.edu/ldl14/Monthly_Ozone_Data.xlsx
http://students.uwf.edu/ldl14/Partical_Matter_Data.xlsx
I went ahead and imported the tables into the database and created metadata for them:
http://students.uwf.edu/ldl14/demographics.htm
http://students.uwf.edu/ldl14/asthma.htm
http://students.uwf.edu/ldl14/ozone.htm
http://students.uwf.edu/ldl14/partical_matter.htm
Then I updated the metadata for the files I altered to fit the bay area:
http://students.uwf.edu/ldl14/air_mon_stations.htm
http://students.uwf.edu/ldl14/ba_counties.htm
http://students.uwf.edu/ldl14/ba_places.htm
http://students.uwf.edu/ldl14/Asthma_Data.xlsx
http://students.uwf.edu/ldl14/Demographics_Pop.xlsx
http://students.uwf.edu/ldl14/Monthly_Ozone_Data.xlsx
http://students.uwf.edu/ldl14/Partical_Matter_Data.xlsx
I went ahead and imported the tables into the database and created metadata for them:
http://students.uwf.edu/ldl14/demographics.htm
http://students.uwf.edu/ldl14/asthma.htm
http://students.uwf.edu/ldl14/ozone.htm
http://students.uwf.edu/ldl14/partical_matter.htm
Then I updated the metadata for the files I altered to fit the bay area:
http://students.uwf.edu/ldl14/air_mon_stations.htm
http://students.uwf.edu/ldl14/ba_counties.htm
http://students.uwf.edu/ldl14/ba_places.htm
Monday, July 26, 2010
Module 5: LIDAR
Wednesday, July 21, 2010
Module 4 - Challenge Map
http://students.uwf.edu/ldl14/LeviLeBourgeoisModule4Map.xps
I found this module challenging. I believe I got the concept of getting signatures. I had a little trouble analyzing them. I also ran into software trouble. I had a hard time actually using the signature editor because it would become unresponsive and other times it worked great. I was not sure if we needed to merge any classes or if you wanted to see the histogram data for all. If I would have merged classes, the fallow fields and some of the urban areas would have been merged.
I found this module challenging. I believe I got the concept of getting signatures. I had a little trouble analyzing them. I also ran into software trouble. I had a hard time actually using the signature editor because it would become unresponsive and other times it worked great. I was not sure if we needed to merge any classes or if you wanted to see the histogram data for all. If I would have merged classes, the fallow fields and some of the urban areas would have been merged.
Tuesday, July 13, 2010
Module 3: Challenge
http://students.uwf.edu/ldl14/LeviLeBourgeoisModule3Map1c.xps
http://students.uwf.edu/ldl14/LeviLeBourgeoisGCPTablePensacola.pdf
The above map and tables were created during the module 3 challenge. The most trouble I had in this challenge was formating my finished map's layout. It's a little hard getting used to the new software. Once I got the hang of the control points the challenge went smoothly.
http://students.uwf.edu/ldl14/LeviLeBourgeoisGCPTablePensacola.pdf
The above map and tables were created during the module 3 challenge. The most trouble I had in this challenge was formating my finished map's layout. It's a little hard getting used to the new software. Once I got the hang of the control points the challenge went smoothly.
Monday, July 5, 2010
Sunday, June 27, 2010
Tuesday, April 27, 2010
Final Project
Tuesday, April 6, 2010
Week 11: Google Earth

I chose this area to locate the Great Lakes Wind farm. It's located in the eastern part of Lake Michigan. This location is in a zone that has the most projected power output per turbine. It is close in proximity to major existing transmission lines. The distance is far enough offshore (15 km) to mitigate any noise or shadows cast by the towers but close enough for acceptable water depth.
Sunday, March 28, 2010
Week 10: Isarithmic Mapping

Tuesday, March 23, 2010
Week 9: Flow Maps

The above map was completed using the Week 9: Flow Maps lab. It shows the immigration to the United States by region. I chose a 30 point arrow for my largest value and calculated the rest using the equation in this lesson's pdf file. Since there is only seven arrows, I decided to used the specific values rather than range graded lines. I became very familiar with the pencil tool this exercise and seemed to get the hang of it. Deciding what went into the legend and how to show it was the trickiest part of the lab.
Sunday, March 14, 2010
Week 8: Dot Maps

Wednesday, March 3, 2010
Week 7: Proportional Circle Lab

The above map was created in the Week 7: Proportional Circle Lab. I enjoyed working with the data in excel. The process of calculating the circle size was interesting. I used the circle sizes in the legend because they represented even numbers and breaks in the data that would be easy for a map user to identify. I do feel I had room to make Europe larger in the map. I would change that if I had to do the exercise over. This did give me a change to practice overlapping circles. I placed a white ring around the circles and made them about 50% transparent so I could stack them. The larger circles were placed first on the bottom and the smaller circles on top. I used a symbol from the symbol library to indicate no data for countries with no data. It also allowed me to practice using groups and layers. Being able to edit all the circles at once was a huge help. I decided not to leave the country labels active because I feel they cluttered the map and took attention away from what the circles were communicating.
Wednesday, February 24, 2010
Week 6: Choropleth


The above maps were produced for the week 6 choropleth lab. They show the percentage change in population for the U.S. by state and census divisions for 1990-2000. I decided to round the numbers for each class. I thought this would be easier for a map user to read. I was not pleased with my Hawaii scale bar. I deleted part of it before I scaled the state thinking it would look better than a big bar. I then figured out how to scale down the numbers and bars without disturbing the length of the bars. If I could go back I would change that. I found the easiest way to change the states to grayscale was to calculate my classes first, then create the legend. Once I had the colors for the legend, I just clicked on each stated and hit the appropriate legend color with the eyedropper tool. The hardest part of the lab was dividing the data in excel. I found the best way was to give each state a division code then sort that way, as someone suggested in the discussions. I think this step had the most potential for human error. I had to double check this and indeed had to correct some errors.
Wednesday, February 17, 2010
Week 5: Map Composition

Tuesday, February 9, 2010
Week 4: Florida Keys

The map above shows a portion of the Florida Keys. It includes cities, key names, harbors and some points of interest such as airports and state parks. I found using Adobe Illustrator extremely difficult. I think this was do to me being on the road and having to use a laptop with no mouse. The dragging and scaling of objects was nearly impossible. I enjoyed picking out different fonts for label this map. I utilized existing symbols to enhance the labeling such as circles and airplane symbols.
Saturday, January 30, 2010
Week 3: Data Classification Lab

The above maps show the percentage African American population of Escambia County, Florida using census data from the year 2000. Each of the four maps uses a different type of data classification.

I chose the equal interval map as the best map to display this data. The evenly distributed breaks make it easy for the map user to identify and easily compare different areas of the black population. The quantile and natural break classification maps contain uneven breaks that make it difficult to compare different areas on the maps. The standard deviation classification map's breaks make it very hard for any map user, much less a novice to understand what each color actually represents.
Wednesday, January 13, 2010
Module 1 Lab Assignment

I chose the above map as an example of a bad map. This map was an attempt to represent North American cities with Swiss Airline flight destinations and cities that held partner airline operations. What makes this a bad map is the errors in geographic location for most major cities. For example Little Rock, Arkansas is located far north of it's actual location and Sacramento, California is depicted east of it's correct location. I would hope the Swiss Airline pilots do not use flight maps created by the same individual.

The map above is my choice for a good map. This map represents religion as it relates to regions in the United States. This map is labeled in a clear and detailed manner. The data is conveyed simplistically, with the use of different colors to represent the leading religious bodies in each county. The user is given all relevant information at the base of the map that they would need to effectively understand the data the map communicates.
Subscribe to:
Posts (Atom)