Week 10

I was unable to complete the final two deliverables, because I was unable to find the ll_coua_dem13.img to repair the data source.

Week 7

Week 6 Site selection

Selection for the client was based on geographic and demographic criteria in order to locate

a suitable region for their future home. In determining where the clients should ideally buy, I

examined Alachua County, Florida, the City of Gainesville and surrounding areas. After focusing

on this broad geographic area, I performed several tasks to narrow the field. Specifically, I looked

at locations in proximity to the following criteria: bus routes, community centers, the client’s

family, North Florida Regional Medical Center (NFRMC), and the University of Florida.

All of the maps based on geographic proximity use a ranking of one (1) being the closest

number, and the highest number being the furthest from the selected criteria. Each color ring

level is approximately 2.65 miles wide. After performing these filters, I moved on to performing

similar tasks on the demographic data of the median home value and the density of other people

in a similar age range (65 +). For these maps, the highest number represents the best choice and

one (1) represents the worst choice. Distance was not a factor in these.

Once the geographic and demographic data was examined for the best choice in each field, I

weighted each criterion individually and performed two overlays where all of the parameters

were examined in relation to each other. For the first overlay, each item was weighted equally.

The preferred location results are outlined in red, and the ideal locations having the highest

number. In the second overlay, I weighted the parameters differently. I put the main emphasis

on the location to the client’s family, with a secondary emphasis on the median home value; the

remaining criterion received lesser weightings. Again, the preferred location results are outlined

in red and the ideal locations having the highest number.

Week 5 Urban Planning

I thought I had already posted these up here. they must have only made it to the dropbox.

Participation Post

At 10 p.m., April 20, 2010, an explosion rocked the oil exploration rig, Deepwater Horizon, setting it ablaze, injuring 17, killing 11, and ultimately sinking the rig; all events leading to the worst oil spill in U.S. history.  In the aftermath of the initial tragedy, BP, the federal government, and thousands of volunteers have put forth an awesome effort to contain, clean up and fix the spill. One of the most important tools used in this effort is Geographic Information Systems (GIS).


GIS is being used to map the daily spread of the oil slick, track where oil is coming ashore and determining if the oil is landing as sheets or tar balls. The U.S. Coast Guard and BP are tracking the spill and using models with data input from hundreds of workers with GPS units and NOAA weather and tide models. They are using these models not only get accurate current positioning of the spill, but to be able to predict how the spill is growing, and where it will strike next which provides residents warning about the presence of oil nearby. These predictions are helping clean-up workers to target their efforts and helping them determine where to lay new boom to help protect the coastline. Volunteer groups like the Mobile Bay Keepers are using the GIS data, maps of the spill and its progress, along with information from coastal and marine wildlife rescue groups to help locate and track the local fauna to find and help injured birds and animals affected by the dark, sticky crude. Local and national news stations are using the maps and aerial photography of the spill to inform residents of the area and people all over the country about the severity of the spill and all that it has effected.


While no one wants another oil spill to happen, the data gathered from this terrible event can be used to help understand and respond to future oil spills and events similar to this. The GIS information and lessons learned will help make response time more focused, faster, and better prepared to handle these unfortunate situations. 

Hurricane Wilma

Hurricane Wilma devastated Key West leaving the greatest impact on developed land, this would greatly affect the businesses and people living on the island. Long term the damage from Wilma will have an effect on the economy and residents of Key West. The cost to rebuild, attract business and tourism back to the region could reach into the tens if not hundreds of millions and take years to get back to where the region was before the hurricane.

Since only 92 % of the island was flooded the damage to health facilities and infrastructure was devastating. Only two churches and one school were not in the area flooded by the storm surge, the majority of the roads were flooded and all of the hospitals were flooded. A portion of one of the non-flooded churches or school can be set up as a command center for emergency responders, and the remaining area can act as health facilities and shelters while restoration is under way. Priority for restoration needs to be on health facilities and roads; to treat and transport any injured persons. Secondary priority needs to be on schools and churches to act as temporary triage and shelter points.

While there is no way to completely prepare for every scenario that a storm like Wilma can throw at Key West, taking the information learned from past storms can help develop a strong game plan. Looking that the areas that flooded, and were damaged the most can help first responders target those areas immediately after the storm. Command posts can be established ahead of time to deal with the impact, and facilities can prepare for the onslaught that will be headed their way.

Same blog—Different name

You get the point, why re-invent the wheel when I can just change what I call it. I'm looking forward to another action packed semester of GIS.