Individual Report

Keith Perry Does Proximity To Natural Preserves Effect Household Income? Overall this project was a success. I feel that I was part of one of the best teams within the class and we all coordinated well and got the project done without a whole lot of obstacles encountered. Sharisse had several inside connections with obtaining data and getting some of the maps printed out for the in-class presentation Each person did their part to get the project done in a timely fashion and with quality. I have no complaint to file against anyone within the group. The group as a whole had several meetings on Wednesday afternoons. Although I was frequently unavailable due to job restrictions and life's occasions, I still contributed to the group's overall success via e-mail and in-class studios. I offered assistance in the creation of the PowerPoints, maps, and paper writing and editing. The literature review was made more probable by my suggestion to look through the works cited sections of each of the papers that were tracked down and try to track down some of the sources those authors used. The literature review was at a standstill until that point. I also fulfilled the request of my peers by searching out orthophotos of the South Mountain preserve area. This was the first time I have ever had to do something like this project so it was a challenge for me. If there has to be a slacker within the group, it would be me in the sense that I was unable to make just about every meeting. However, I did make my contributions to the project as stated above. I learned a great deal throughout this project. Being able to geocode and reference some of the data was an experience I will never forget. I think that task is time consuming and difficult even for an experienced person. The other tasks such as creating buffers and running statistics on the data and loading the shapefiles into ArcGIS, were all tasks that I learned throughout the lab exercises within this course. However, it was pretty cool to get to use these method and techniques for a project. It was an excellent way to collaborate with peers and conjure up the lessons learned within the context of the lecture and lab portions of the course. A flowchart illustrating the process of how this project was made possible is displayed on the next page.

Keith Perry

First, we had to obtain the shapefiles and data tables from the U.S. Census website and the Maricopa County website. Next the shapefiles had to either be joined, updated using the update polygon tool, traced onto a new shapefiles, and then exported to a new shapefile. In the preserves shapefile, we had to create the six individual buffers (one layer for each buffer) of 0.5, 1, 2, 3, 4, and 5 miles. For the median census block household income values we had to convert the features to points or centroids in order to use the near tool to calculate distances the points were from preserves. Then we used the table generated from that to run statistical analysis to build scatter plots and generate graphs to analyze the correlation. The individual household income census block group was a slightly different process. We clipped each shapefile to the preserve's boundary and used it the Phoenix and South Mountain X distance buffer shapefile. Then we erases all other buffers to create a one mile ring around the preserves and created the Phoenix Ring and South Mountain Ring shapefiles. There are six files of

Keith Perry each because it had to be done for each individual buffer. All buffers were erased except for the buffer that we wanted. Again we used the attribute table created from this process to create scatter plots and analyze the correlation between proximity to preserve and household income values. As you can see the project took some effort and time from the entire group to complete. The study was only done for the Phoenix Mountain preserve and the South Mountain preserve. It was limited to just these two locations because they were close by and everyone within the class could relate to what we were talking about. We were certain that nearly everyone has at least been around one of these two areas and can get a scope of what we were talking about. After completing this project I now have a much deeper understanding of ArcGIS and my appreciation for this software and the people who use it to make our lives easier from day to day. I would have never known that so much work goes into making GPS devices and Google maps products. That textual information does in fact need to be geocoded by someone sitting hunched over a computer for several hours clicking on each individual little point. Although this project was exceptional, it was not perfect. There could have been a lot of thing done to improve the project. The data used was secondary data from the 2000 census. If we would have gone door-to-door and surveyed the residents, we would have gotten more current data. The work would have been much more because we would have had to have created the shapefiles ourselves and enter in all the raw data before we could geocode it and create an image. That would have given us a more in depth understanding of what is going on and would have introduced new factors to us that we did not consider in this project. Factors include, the number of adults (individuals over 18) living in the household, how many members of the household have jobs, have members of the household been laidoff recently due to economic struggles, are the members within the household retired, and do the people within the household do or even need to do anything for money. I am curious about the last factor because there were several homes within five miles of the Phoenix and South Mountain

Keith Perry preserves that recorded a zero household income value. We only looked at incomes as they are related to annual salaries. We did not investigate whether or not these people are retired or receive income from other sources such as owning their own business or gratuities of some sort. Some of these people could have investments in the stock market that we are unaware of just looking at annual salaries. All of this information could have been obtained using primary data. The project could further be improved by looking at preserve locations in other parts of the state, country, and the world. Doing this project on a national scale, especially with primary data, would have given us a much more profound correlation between household income values and proximity to natural preserves. Doing this project with individual incomes yielded slightly different but similar results. There still was a negative correlation between the income values and distance from the preserve. The income values for both individuals and households by census blocks decreased as the distance from the preserve increased. Although there was a correlation between income values and proximity to a preserve, the results were typical when broken down into individual income values. There were a lot of people within the median value around $50,000 and the number of values in that range decreased and we looked away from that value either higher or lower. This created a bell curve which is very typical when looking at the distribution of a variable within a sample. Even though bell curves were not included in this project, it was pretty interesting to see my knowledge of bell curves come to life in a real example that I was a part of examining and analyzing.