Week 7 - Location Decision - On Your Own

Military Housing Location

The assignment was to create scenario “On My Own” of selecting a site based on criteria I selected. The topic I chose was potential areas for military housing near the bases located in Okaloosa County Florida.



The first map I created was a base (foundational) map of Okaloosa County. I selected data from the FGDL website and chose Albers Conical Equal Area as my projection. I added data layers for the military owned land, highways, municipalities and water features to complete the map.

Next, I asked the question, what are the factors that are relevant to selecting areas for potential new military housing? The primary needs were, distance from the installation access gates, proximity to sufficient schools, and distance to interstate travel.



A map was created depicting an overlay of distances from the main access gates of the military installations on the county. This map created by using the Spatial Analysis Tools, Euclidian Distance Tool. I created a new point feature file and added the points for the three main access gates of the military installations. I used this feature to overlay distances from, clipping them at the Okaloosa County boundary. I then reclassified the data using 10,000 meter intervals, creating five intervals.

Next I chose to evaluate distances overlaid on the County. I used the Euclidian Distance again, selecting the layer for I-10 as my feature with the County as the clipping feature. Once again I reclassified the data to create a scale of 1-9 for the interval.

The next map was a little tricky. I wanted to determine if a municipality had the schools sufficient to house kids associated with the new troops. For this I used two layers, the first one from the National Atlas for the United States for the community data and one from the Department of Education and clipped it to the county boundary. Next I summarized the data from the DOE by city name, selecting student population as a criterion. Then I joined the summary table to the Atlas data to give me a school population by community number. From this I used the Point Density Tool to give me a raster of the population. Once again I reclassified to nine different classes, with class 1 being 0-99 and up.

The last step of my analysis was the creation of the results. Map 1 is a depiction of creating a tool for performing a weighted overlay using an equal weighting factor for each of the criteria.

Map 2 was created by the same method only giving equal weight to distance from I-10 and bases with a greater weight to the schools.

The pros and cons. The pro of this method is that two areas that clearly meet the test are the Niceville and Crestview areas. They have substantial school capacity as well as being the closest in proximity to the base. Crestview rates high due to its location adjacent to I-10. The con to this method however is that available properly zoned properties were not factored into the decision. Neither was the capacity for the roadways to carry additional vehicular traffic without significant upgrades.

Week 6 - Location Decision - Gainesville

Gainesville Housing Location

The assignment was to analyze the prescribed data to ascertain the preferred location for housing for the couple interest in relocating to Gainesville, Florida. The wife, a cardiologist expressed a desire to locate near the NFRMC. The husband, a college professor, conveyed his desire to be near the university. The additional criteria offered was a certain level of affluency to the neighborhood and a 40-49 year old demographic. First I created a base map of Alachua County Florida depicting managed public lands.



Next a map depicting the four separate criteria was created. Four views were created showing the distance from the hospital, distance from the university, census block by home values, and census blocks showing the greatest concentrations of 40-49 year old occupants.









The third was a map that used two different weighting factors to analyze the criteria and produce an output to demonstrate areas that best fit the criteria. The first view shows three significant areas using a weighting of 25% weight on each of the preferences. The second view was adjusted to show an increased importance to relative distance to the work place. The second view showed a shift in the recommended location.

The pros of using this criterion for selection allow the end user to minimize a search area from accommodating housing. This allows the user to save time by dismissing areas that don’t fit their preferences.
The cons of this method are more subtle. Condominiums and apartments complexes could skew the numbers. Also, eliminating areas of town by this method prevent a purchaser from finding those potential gems that are in less obvious locations.

Week 5 ‐ Urban Planning and Impact Assessments

Week 4 - Participation

This is a two part participation.

1. Video of oil spill ... I took some liberties with this since it was extra credit.



2. Summary

GIS and the Disaster
It is 3:45 am on the morning of January 7th, 2011. The phone rings at the local police station and the night dispatcher answers the phone,
“H-hello … I mean, Jonesboro Police Department”, he answered in a shaken voice.
“Earl! Earl! What is going on?” a frantic caller exclaims.
“I’m … I’m not really sure” the Captain stammers, trying to regain his wits, “I think we just had an earthquake.”
This is how a natural disaster can occur, without warning, in the middle of the night, and in unexpected locations. The follow are some of the roles where GIS can play a role in helping recover and live through a disaster.
4:30 am, City Hall conference room, Jonesboro, Arkansas. A group of city officials, law enforcement and fire fighters that were able to be contacted are assembled. Joining them is a smattering of frightened citizens.
“All right, all right … lets all calm down and listen to what the Mayor has to say” shouted the Chief of Police.
“Thanks Tom … as we all know, we have just suffered a significant earthquake in our area and reports are coming in all over the county of widespread power outages and damages to structures. We are currently assembling a team to assess the damage and to start trying to determine where folks are that may be injured and need our assistance …” the Mayor stated.
“I can’t reach my husband at the factory in Lake City!” a voice rang out from the citizen crowd.
“Mary, we are trying to get a holt of someone from the plant as we speak … I will let you know as soon as we do,” the Mayor offered as reassurance. “We have contacted Little Rock and the Governor has issued an emergency order … help is on the way.”
Meanwhile, in Little Rock a group of emergency responders are meeting. The team has a map laid out on the table that depicts the underlying topography of Jonesboro, Arkansas and surrounding areas. Also, plotted on the map are the roads, hospitals, fire and rescue facilities, as well as schools.
“We need to assess the viability of these facilities ASAP … we may need to set up triage in as many as are still operational,” Bobby Miller, the operations leader directed. “And we need to know where any and all landing strips are available to us to get in and out the area.”
“I’m already on it,” answered Steve Thomas, the GIS specialist for the State Emergency Management Center. “We’ll have maps uploaded to your PDA’s by the time your on the ground in Jonesboro.”

The GIS specialist collects and analyzes data and information to provide it to individuals in a manner useful to their specific need. In the hypothetical case above getting outside responders the information on an area they are unfamiliar with allows them to learn about the location they are headed to before arrival so they can acclimate quicker thus potentially saving lives.

In the Gulf of Mexico, on April 20th, 2010, the Deepwater Horizon oil platform had an explosion that eventually lead to it sinking and an ensuing oil leak that threatens the entire Gulf of Mexico. Teams of analyst have been studying the inventories of everything from shoreline habits to intercoastal wetland fauna to try and prepare plans for protection and rescue of affected species. In addition, human affect is also being analyzed. Gulf dependant business and property damage is estimated from data compiled to project the long term effect on our economy. These evaluations give lawmakers the information they need to determine how resources are allocated to help in the cleanup and recovery.

In case you’re wondering, Mary’s husband that was working at the factory is alright. The designers of the plant had used GIS data to analyze sites when choosing a location for their new facility. Some of the layers provided with the evaluation were geohazards which indicated the fault lines near the area and the engineers designed the facility accordingly.

WEEK 4 - Environmental Sensitive Index

The week four activity involved collecting, analyzing and reporting on the data surrounding the Deepwater Horizon Oil Spill disaster in the Gulf of Mexico that occurred on April 20th, 2010. Data from LABINS was downloaded in the form of DLG images for a base map. I projected the TIFF image to NAD 1983 HARN State Plane Florida North FIPS 0903 Feet. I chose Destin from the index as my study area. I created three maps.

Map 1 was ESI Creature Habitat clipped to the Destin Index. I re-projected the data to the same NAD83. I used the imported symbology from the Alabama case study that was provided.



Map 2 was the Shoreline Habits which I re-projected and symbolized the same as before. I added the layer depicting Areas of interest and the Booming Plan.



The third map I created was State Managed Areas. I used the same projections and clipping areas as before. Similarly I added the symbology to be consistent with the ESI standards. In addition I opened the attribute table and created a summary, saving it to a database. I then generated a table for the layout displaying the areas of the Managed Areas.



I didn’t have many issues with this assignment other than the fact that it took an inordinate amount of time and in the end I still didn’t have enough time to complete the maps as thoroughly as I would have liked.

Week 4 - Natural Hazards - Oil Spill

This project hit all to close to home ... the first map is Part I
Importing XY Data from MS Excel to ArcMap to Google Earth.