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.

Bobwhite-Manatee Transmission Line

Timeline (XLS)

Presentation (PPT)

Presentation Notes (PDF)

Week 10-

This lab was very clear about what needed to be accomplished, join a database file with a shapefile, to calculate the acreage of parcels, and then use the select by attribute functions to determine the four largest landowners. I wish I had done this over spring break.

Week 9 - Overlays

Q1: I used intersect to create my layer, visually I didn't notice a difference. However; in the attribute table I did notice there were two records with intersect, compared to four with union.

Q2: I used the erase tool for my results, because I needed to subtract the overlapping areas to eliminate them from being candidates for possible camp sites.

Q3: I ended up with 81 features, my largest area was 775,304 sq. meters, and my smallest was 748.11 sq. meters.

Week 7

This was a great, quick assingment, that helped me recharge my batteries quite a bit. Everything clicked with this project, the only complaint I have is that ESRI spoon feeds you through thte entire exercise, so it makes the challenge dissapear, I know for me just reading and following everything step by step, makes it harder for me to actually learn something. I wish their assignments didn't hold my had as much as they do.

Week 6 Georeferencing

This assignment was a lot of fun, it would have been even more fun had I read the instructions all the way through before starting on it. I added my control points and updated the georeference before I wrote down the RMS value for the first part of the lab. I tried to fiigrue out f there was a way I could find out the info I hadd added again, but I didn't have much lusck with that, so I started over and did it again. This time I read all the instructions.

My RMS Values are:
UWF_n: RMS= 7.43321, 1st Order
UWF_s1: RMS=2.77766, 3rd Order

Week 3: Mexico

The first map of Mexico depicts the States and their population.

The second map is of Central Mexico, showing its urban areas, railroads, federal highways, and rivers. This portion actually caused me some troubles. Not with the map, but with the legend. I'm still not sure why the legend style changed, but I had to go in to the styles and play around to get them to dispay properly.

The third and final map shows the elevations in Central Mexico.

This post was accidentally posted on my Cartographic skills blog on 2/3/2010. You can view it by clicking the following link. Cartographic Skills

Week 4 participation post

This was a map on the ESRI site showing and overview of the hospital damage in Port au Prince.

Week 4- Coordinate Systems

The area, in square miles, was calculated for four counties (Escambia, Alachua, Miami-Dade and Polk), using three different projections system. Each system had differnet area values for each county, with UTM seeming to vary the most between the thres systems.

World Map

Week 2

A quick overview map and lay out of the countries of the world.

Module 1

Tourism Map

From Module 1 on ESRI site, Learning ArcGIS, this is the first part of the exercise. The tourism map for San Diego, with a focus on locating the trolley route to the Zoo. 

Youth Center

This portion of module 1 focuses on finding a youth center, this image of the map show the locations on the city grid.

This is the same youth center map as above, but instead of the focus of the locations being on the city grid, it shows the suitable locations based on the concentration of youths at each location.

First Post

Welcome to my Into to GIS bog