These are maps of Napa County California that show households and wine purchase along with liquor purchases from restaurants and liquor stores. Most of the liquor and wine purchases are in areas that have a higher number of households. They also show that liquor stores and restaurants are in locations that have a high number of households.

Project 3: GIS and Economic Development

Recommend a New Retail Site Report

Market Area Analysis

Project 2 Report

The follwoing is a link the project 2 Landscape design report



Report

These are maps of 5 neighborhoods in Marin City, California. The one map is shows the percentage breakdown of three types of landcover (trees, grass, and impervious surfaces). The other map shows carbon storage and carbon sequestration for each of the 5 neighborhoods. The reclassification from the original aerial photo was the most difficult part of this project.

Project 1: Report

The GIS department has been tasked with locating a target population to see where state funds need to be allocated in order to help fund health care costs for the uninsured populations of the San Francisco Bay Area. The first area of analysis was to determine if there is a correlation between the uninsured and the minority populations. The three population targets that were analyzed were Hispanics, Blacks, and Single mothers. The analysis results showed the black population within Alameda County would best benefit from the available state funding. The next part of the analysis was to determine which counties had the highest hospital admittance of asthma related cases and then see how it relates to ozone and particulates matter. The results of the analysis showed that Alameda County had the highest rate of asthma related cases and was on the high end of the spectrum for both ozone and particulate matter levels. The third part of the analysis determined where the highest concentration of the target population resided within the county. Using this data it was then determined if other pollution factors contributed to the high number of asthma hospitalizations. Toxic Release Index location and roads were given buffers so that overlaps with clusters of high black populations and nearby hospital locations could be analyzed. The last part of the analysis proved to be difficult because I could not get the Toxic Release index raster layer loaded into the weighted overlay. Although I could not get this part of the analysis completed it was easy to see on the map where there were multiple factors that cold have contributed to the high hospitalization rates. This project, by far, was the most difficult and frustrating since the beginning of the certificate program. I managed to get through it though and hope the coming projects are not nearly as unclear to me

Project 1: Air Pollution, Asthma, and Race in SFBA

These are the metadata files that correspond to the shape files that were created from various sources.

Demographics
Asthma
Ozone
Particulate Matter 2.5

Module 5 - LiDAR Imagery

This is a map of LiDAR Imagery that has been converted to a raster image. I changed the symbology a few different times to see what would best differentiate the features. I also checked the image against aerial imagery to make sure I had the road in the correct place. I used imagery provided by ESRI on the online resource center.

http://resources.esri.com/arcgisonlineservices/index.cfm?fa=content_detail&contentID=04E6611E-1422-2418-A0DDD0025BEBBF00

Click the "ArcMap" link next to "View Service In:". This will let you download a .lyr file that you can use in an .mxd to "link" to aerial imagery for the world (you must be connected to the Internet). I believe they update it twice a year so it is fairly current.

Module 4 - Supervised classification

Map

This is a map of Germantown, Maryland that shows current land use. It was created using supervised classification. It was pretty straight forward and I did not have any major problems with this excercise. I am getting more comfortable using this software, but I am looking forward to doing the future excercises in ArcGIS.

Pensacola Map

This a map of Pensacola that has been rectified to a UTM projection using a USGS topographic map as reference. This was a pretty straight forward assignment. The only issue I had with it was that I don't know how to tell if the UTM grid is correct.

Map 1
Map 2
Map 3

These are three multispectoral maps showing features that can be highlight with different combinations of scale and color. Map 1 and 2 show water features and map 3 shows shallow water features. The shallow water feature shown using TM False Color IR.

Module 1 Challenge

Map
This was my first time using the ERDAS software. for the most part this was an easy lab, but saving my assignment was a little confusing and I'm still not confident I did it right. I'm sure I will eventually get more comfortable with the software. A lot of the functionality is similar to ArcGIS and some things remind me of Adobe illustrator.

Final Project

This map shows the mean SAT score for high school graduates who took the test in the United States for the year 2009. The map also shows the percentage of participation of high school graduates for 2009.

Google Earth

This lab was fairly simple. Details of my windfarm are in the above photo. The hardest part of this lab was getting it to export to a jpg. When I tried to "save image" it would not show the details of the windfarm window. I ended up taking a screenshot and cropping out the edges.

Isarithmic Map

This is an isarithmic map of the mean average rainfall in Georgia. This map gave me some trouble at first, but after I figured out how to determine where the lines get drawn it wasn't so bad. I used the pencil tool to draw the contour lines and then used the smoothing tool smooth out the parts that didn't look good.

Immigration Flow Map

This is a flow map of 2007 immigration by regions. The most difficult part of this lab was figuring out how to classify the different ranges. I finally decide to go with an equal interval classification and then used a 30 pt maximum line width. I used the pen tool to create my arrows and "bent" the lines to make the map more visually appealing.

Dot Distribution Map

This is a dot distribution map of of the households in Florida. this lab was very time consuming. I used excel to calculate the number of housing units in each county by the total area. I then calculated the percentage of units in each county and divided by 1000 to get the number of dots in each county. Pinellas County had the largest number of dots at 115 out of 1000.

Proportionate Symbol Mapping

This is a proportionate symbol map of European Wine Consumption. This was a simple, but time consuming map to create. I don't know if I would ever use this method to create this kind of map outside of a classroom because this kind of map can be created in in ArcGIS much faster.

Chorpleth Mapping Lab

This a choropleth map of the percent change in population by census division between the years 1990 and 2000. The map used the same base map as the one below but was classified using 5 equal intervals. Using excel to create the equal intervals was very easy and straight forward.

This is a choropleth map of the percent change in population by state between the years 1990 and 2000. It is classified with a 5 class natural break. The hardest part of this lab was getting it in a layout that looked good. Since Alaska is such a big state it takes up a large amount of the page and had to be placed in such a way that allowed the continental US to be shown clearly as well.

Map Composition Lab

This is a map of the hispanic population percentage in Central and South Florida. Adobe Illustrator is getting easier to use each time I use it. Some of the newly learned features I like are the separating of layers and also being able to group things together. Changing individual elements was pretty straight forward.

Map Lettering Lab

This is map of the middle part of the Florida Keys. I have never used Adobe Illustrator so it took a little getting used to. I think this would be a good tool to use after creating a detailed map in ArcGIS and then bring it into Adobe Illustrator to improve on the typography elements.

Data Classification Lab

These are maps of African American population in Escambia County by census tract. I made sure that I used the same scale in each dataframe so that I only needed to display 1 scale reference and 1 scale bar instead of cluttering each individual map with the information. I also use the guides in the layout view to ensure I had equally sized dataframes.


This is the equal interval classified map of African American Population in Escambia County by census tract. I believe this is most appropriate for displaying the data because the change in color scheme stays consistent with the change in percentage.

Good Map

This an example of a good map. There is a title, a legend, a scale bar, and a north arrow.

Bad Map

This an example of a bad map. There is no frame of reference such as a north arrow and there is also no scale of reference for distances.