Hurricane Damage to Historical Structures of St. John's County

The history of St. John's County, Fl is vital to all parts of society. The tourism to this area of the First Coast is evidently dependent on the existence of its historically important sites. What would happen to the historical sites of this area if a major hurricane were to make a direct landfall?
This is a vital question to everyone who lives here. Fortunately, St. John's County has not had a direct landfall from any hurricane since 1964 (Dora Cat. 2) and has never seen a major hurricane directly impact the area. We might be overdue. I hope not. This study is to see what would happen to these historic sites if a Category 3,4, or 5 hurricane were to ever strike this area. Lets hope this never occurs.

Final Project: Hurricane Study of Historic Sites of St. John's County

Final Project Summary

I hope everyone has a great couple weeks off and I am excited to get started on my internship which starts tomorrow and our final class.

Week 10: Line of Sight Analysis

This is week 10 deliverable 3. This was by far the hardest map for me to produce. I had to reproject the necessary data so that the calculations would come out correctly. I probably spent have of the time this week on this map alone. That being said. I believe this would be a good tool in homeland security of critical sites like NORAD.

The map shows 5 observation point which I established along the hillsides surrounding the NORAD tunnel. These 5 sites would be vital in an emergency. We then used the line of sight tool in the 3-d Analyst toolbar to establish areas outside of the image where visual observation would not be possible due to hills and valleys. The tool allows us to interpolate where good sites are for additional observation through camera surveillance. The red in the lines show areas a;ong the line where visibility is obscurred. The blue dots show exactly where 5 new camera surveillance post should be set up to optimize the surveillance of the area in case of an emergency. In addition, the graphs of each of the line of site analysis are included to better understand the position along the line where the new surveillance camera network is to be set up. The graphs illustrate the elevation of the surrounding lands along the line of site and show how visibility would be obstructed. They also give us a good idea as to what areas the new sites will be observing such as hills and valleys.

Week 10: Ingress and Egress Routes

This is week 10: Deliverable 2 The map shows the local roads around the Cheyenne Mountain Heliport. It shows the 500 ft. buffer zone around the heliport. It would be very important to keep this heliport in operation during a homeland security crisis. It could be a vital transport station for high ranking officials in our government. So I believe it is important to show where roadblocks along these routes would have to be set up. The map shows the five locations of police mandated roadblocks that would have to be established to ensure the operation of the heliport. They are located at point where the local roads intersect with the 500 ft buffer zone around the Cheyenne Mountain Heliport.

Week 10: Buffer Zones

This is week10 Deliverable 1 for GIS 4048 Applications in GIS for summer 2010 at UWF online GIS. The map shows the areas around NORAD that are essential in case of a homeland security threat. The critical infrastructure around NORAD are also detailed. There is only one airport within the 3 mile buffer zone(Cheyenne Mountain Heliport). It would be very critical to keep the heliport running in an emergency. The map illustrates the 3 mile buffer zone around NORAD as well as a 500 ft. buffer zone around the Cheyenne Mountain Heliport. I have done an enlay of the larger area so that both buffer zones aree easily displayed on one map.

Week8: Crime Time Graph

This is Week 8 Deliverable 4. The graph shows an hour by hour breakdown of number of crime occurring during the month of August 2009 for the Washington D.C. area. You can see a spike in activity for the month during the hours between 6 P.M. and just after Midnight. I did not want to add this to my map layout as it was not required and I have had problems with clarity of graphs within my maps in the first 2 assignments this week.

Week3: Burglary, Homicide, and Sex Abuse Crime Density

This is Week 8: Crime Density Map

This map includes 3 distinct maps showing crime density within Washington D.C. The 3 maps show Burglary crime density, Homicide crime density, and Sex Abuse crime density. I have included major highways and interstates to show location within the area. I put Sex Abuse at the top because that is what I would look at if moving to the area. So I thought it was very important. I tried to keep the map as simple as possible because of the number of elements that were already on it.

Week8 Deliverable 2: Multi-ring Buffers

This is Week8: Crime Proximity Map

I took more time on this map than any other this week. I was able to distinguish between types of Police Stations, including District Headquarters, Liason Units, ROC Headquarters, and Substations. I included multi-ring buffers to show crime within .5, 1, and 2 miles of existing police stations. I allowed transparency on the buffers to determine where would be the best areas to place 4 new proposed substations. I produced a new layer from this data called proposed substations and added the points to my map to easily show where I thought the new substations should be built. I included a graph to show the number of crimes within existing stations jurisdiction. Unfortunately, this graph did not come out looking like it did in ArcMap. I don't know why my graphs look bad. I guess from looking at others, I probably needed to make them larger for clarity.

Week8: Washington D.C. Basemap

This is my Basemap for Week 8: Washington D.C. Crime Analysis. I have included the required graph which breaks down area crime by type and gives totals for the month of August 2009. I have also included the major interstates and highways, location of the police stations within Washington, locations of where crimess took place, and census blocks. I tried to get the graph to come in better with no luck. I don't know why it came out so bad.

David Renna Apps in GIS: Week 7: St. John's County Home Site Selection

David Renna Apps in GIS: Week 7: St. John's County Home Site Selection

Week 7: St. John's County Home Site Selection

This is my week 7 Deliverable for Home Site Selection in St. John's County, Fl. I had a few problems with licensing on the server 2. I know I'm not the only one. After many hours of checking my Environments and looking through the ESRI website for answers I was able to perform all calculations just like Week 6. The size of the map only became a problem when I had an extra page in my pdf. I thought this was the least of the problems. Had problems linking pdf file to blog.

Week6: Map Overlays

This is Deliverable3 for week 6. The map consist of 2 maps. The one one the left show a equal distribution of the 4 parameters. The second shows a more accurate depiction 40/40/10/10 percentage of what the couple thinks is important in buying a house. I have chosen the same color ramp for this project Green - Red to emphasize the green areas as good. I also adjusted to most desirable areas to clear to highlight them. This gave me a good idea on both maps as to desirable areas and the tract data so I could pick 3 areas in each to have as the top 3 areas.The one area on both is just SW of the hospital and is where I beleive the couple should search.

Week6: 4 Maps Approach to Decision Making

This is Deliverable 2 for week 6 in Applications in GIS. This map is composed of 4 different maps. Each map is associated with a known parameter for the couples decision making process.
The first is proximity to North Florida Regional Medical Center. I used the same color ramp for all my maps. Green to Red. Green being good. I altered the closest proximity for easier visual impact.
The second map is of the proximity to UF. I used the same techniques to highlight the closest region.
The third map is of the percentage of people in each area 40-49 years of age. The couple wanted this to be their third evaluating parameter as they want to be around people their own age.
The fouth map is of mean home values as the couple want to be in a good area with high mean home values.

Week 6 Basemap of Alachua County Florida

This is Deliverable 1 for Week 6 project in Applications in GIS. This is the basemap for Alachua County, Florida. It details the different public land areas and ownership of those areas for the study area.I have included Census 200 tract, places, and roads to get your bearings of Alachua County.

Week 5 : Urban Planning and Impact Assessment

This map shows the various areas and their LQ value which is a value assigned to different industries by the amount of financial gain they provide to the local community through exportation of products. Any 1 and higher are essential businesses due to exporting of goods.

Week 5 : Urban Planning and Impact Assessment

This shows the student occupancy rates for the living areas around Pewter University. I describes the amount of students living within each building area. The map also divides the areas into percentage of students to total populated for each area.

Week 5 : Urban Planning and Impact Assessment

In this map we are assessing what sort of impact the new building being proposed is going to have on the road that its is located on. You can see that the area closest to the proposed site(Local Area) is impacted much more than any other area on the street.

Participation 2-4: GIS Role in Oil Spill

GIS plays a vital role in disaster response. It can be used to assist in the efforts of first responders, Environmental and Federal Agencies, National Wildlife and Fishing Agencies, and in the efforts of local business to be prepared for natural disasters.

With respect to the Deepwater Horizon Oil Spill, GIS has been used by first responders to track the extent of the oil and its movement. GIS has played a key role in the efforts of first responders. It has done a great job in showing areas of concern for people on ground zero. Maps have been made to show the flow of the oil with respect to landfall.

Environmental and Federal Agencies have used GIS to produce ESI index maps of the various species and conservation areas that are going to be effected by the oil spill. National Fishing Agencies have used GIS to map out the oil spill in order to close boundaries for fishing both in offshore and inland waters.

Finally, local governments and businesses are using GIS to access the economic impact that this catastrophe is having on the region. GIS might not be the cure for a natural disaster like the Deepwater Horizon Oil Spill, but it sure has played a vital role in the initial efforts in the area to make decisions based on the latest data available.

Horizon Oilspill: Booming Operations

This is my map for the booming operations in the Fort Walton Beach Area. I have divided the operations into five categories. I have also included a chart to show the types of operation, how many booms in each, and the length in feet of the booms.

Horizon Oilspill: ESI Species Areas of Concern

On my second map, I have detailed the areas where susceptible habitat and species are located. I used the guidelines for Alabama from the readings to use appropriate horizontal hatched colors to represent each types of species and the areas where they are known to survive or have been spotted in the last year as per Alabama guidelines. I found that I could not represent each species as a symbol. So this is how I did it. I also included a chart with identifyable species of each type on the map.I also included my Socecon point data to show that there are 26 points. 21 marinas, 4 beaches, and 1 airport.

Horizon Oilspill: ESI Areas of Concern/Management Areas

I chose the area around Fort Walton Beach. It is actually tile 17 in the South shoreline and bay area of Oskaloosa County, FL.This is the first of 3 maps. I have highlighted the ESI Areas of greatest susceptibility to oil. I tried to use appropriate colors for the areas. I also have included Management Areas for easier access to Fedeeral and State help.

Fishery Areas Closed Due to Oil Present: 05/25/10

This is my Google Earth image of my FisheryClosing.KZM file. I worked on this for over ten hours, running into problemson just about every step. Then on my last attempt it worked perfectly. I don't exactly know what I was doing wrong. But I sure am glad to be through.

Hurricane Katrina:Types of Lands Affected by Storm Surge

I have included the approximate areas which flooded during Hurricane Katrina. I have indicated the land types that flooded includ Agricultural,Barren,Developed,Forest,Not
Flooded,Water, and Wetlands. The chart also shows a visual representation of the types of lands which flooded and the associated percentages.

Hurricane Katrina: Map of Important Features

Hurricane Katrina was devestating to the coastal regions of Mississippi. The map includes the elevation/bathymetry of Hancock,Harrison, and Jackson counties along the Mississippi coast. I have included places were census data is collected,types of water(Marshland),barrier islands, and hydrography.

Final Project Powerpoint

Final Project Summary

Facebook

Facebook: "The video is under 1024 MB and 20 minutes."

Week 11: Fun Map 3-D

This is a 2-D jpeg image from the 3-D image in ArcScene. I adjusted the image to reflect the elevation. I have added hillshade and adjusted the color ramp to enhance the image. I also rotated the image so that the 3-D aspect can be more easily scene. This is hard to do in 2-D, but I could not find a way to capture the image in 3-D and export it to the blogger without problems.

Week 11 Map 3: Zonal Reclassification

This is deliverable 4 for week 11. The assignment was to reclassify vegetation for study area only. So following instruction from module we used the remap to reclassify the drought tolerance for vegetation in the study area.I chose the color ramp because it is easily distinguishable between levels of tolerance. The no data areas are white. I was able to add all reqquired elements of the map including a legend, neatline, scale bar, north arrow, and source data.

Week 11 Deliverable 3: Model Snapshot

This is the snapshot of my model. The model was run in ArcMAP with modelbuilder.

Week 11 Map 2: Recreation

This is second of 5 deliverable for the week. It showcases the ability to label features using ArcMap 9.3 I followed the instruction in module 1 " add custom text to your maps" to include feature labels of water bodies and recreation features.

Week 11 Map 1: Cities and Roads

This is the first of 5 deliverables for this week. I have followed instructions layed out by Module 1 on Labeling and Annotation. I included all of the required map elements except for a legend which was too excessive.

Week 10: Spring Break Lab

In this lab, We used raw data from tables which were created in ArcMap. We joined the data from the tables to already existing shapefiles.I then exported the data to become a new layer in ArcMAP. The last thing I did was categorize the data with the top 4 landowners of Gulf County, FL. By changing the background color of the layout, you can easily see each parcel and its owner, while leaving the other parcels owned by people or companies not in the top four a neutral color.

Map Overlays and Buffers

Question 1: Which tool did you use? Was there any noticeable difference in its result and the results from the instruction?

I used the Intersect Tool because the description of what the Intersect Tool seem to do is what is being asked of us.This seemed to work much faster and with no noticeable difference in its results. This tool work much quicker than all of the steps taken in the instructions.

Question 2: Which tool did you use here and Why?

I used the Erase tool becaquse we want to keep everything in our original area while getting rid of the aarea within the conservation areas so that the people and the plants are safe from harm.

Question 3: How many features are in this layer? What is the are of the largest feature? What is the are of the smallest feature?

I got 78 features. The largest area was 7765034.5 Square Meters. While the smallest feature was 748.1 Square Meters in area.

Week 8: Image Editing

This is the edited image of the University of West Florida. It is the same image that we worked with last week with a few edits. There is a new shapefile layer named Athletic_fields and Ihave digitized the Athletic Fields into this layer and displayed the layer in my legend. There are also edits to the building layers where the two building have been editied to fit the image. Also I digitized the maintenance road in the lower right portion of the image to the roads layer.

Week6 Georeferencing Repost

I was able to finally get it to work. I updated my second map. In this map I used 27 points to produce a 3rd linear equation map. It was reported an RMS of 18.58516.
As I mentioned inj my first post. The top map uses 10 critical points and has a 1st order equatioon RMS of 15.89071. I beleive that both maps are of good quality with RMS values under 20 as requested.

Week6: Georeferencing

In this lab, we are georeferencing a unknown aerial to a known buildings and roads map. In order to do this, I added ten control points from the known maps to the georeferenced map or unknown map. After adding the ten points, I displayed data as a table in order to see how similar the two maps were in a 1st ordeer polynomial reference frame. In order to make sure the maps line up we are looking at the RMS or Residual Error. For the map to be a good fit, we are looking for a RMS of under 20. I was able to reduce this number through trial and error to 15.89071 on my maps. This seems to be a very good fit by visualization and the fact my RMS is low.
The second map is a raster map of the same general area.I used a third order polynomial reference frame. I had to use 21 different control points for this map. I got a RMS of 17.83217. A good fit for this size data set.
I don't know why the image is black. When I did the assignment it raster image was fine and matched up well. I even tried to reload the data to my map and it looked like this. I could not remedy the problem. Though you can see by the distortion of the map that it has been Georeferenced.

Week5 Map 2

Inb the second map of this assignment. I downloaded and extracted the DRG for Lake Jackson Quad 5335. Then I downloaded and added each of the four quadtants of the South Havana 5336. I found two different version of the information. For the top half I used the Black and White data and on the Southern two I used the color version of the data.
I was not able to convert the DEM for Midway 5236 to the south of South Havana. I did put alot of effort into this assignment and I hope that the time spent is considered.

Week 5 Map 1

This was by far the hardest assignment to date. I had real problems with understanding where to find files that were not corrupt.
This is a map of Gadsden County, Fl. I was able to produce this map with shapefiles downloaded from FGDL website. I then clips the size of each piece of information down to the size of Gadsden County using ArcToolbox.

Haiti Map Post

Week 4 Maps: Projections

Week 3 Map 3

I have made a map that depicts the elevation for Central Mexico and I have assigned the best color scheme I could find in order to express the elevation on the map.

Week 3 Map 2

This is a map of Mexico in which I have highlighted the major and primary rivers, roads,railways and urban area. This is a good map for finding out where traffic problems might occur on the roadway system and to find alternatives to the roads.

Week 3 Map 1

In this assignment, we have produced a map showing the population density of Mexico.
We have devided mexico into 7 different categories of population density and have added appropriate colorization so that it can be seen easily.

Module 2 Countries by Population

Map 1

Module 1 Youth Center Map

As per instructed, I have produced two maps in ArcMap. The first one is of San Diego for planning a trip. I have decided to stay at the Marriott Resort and Marina because it is closest to the ocean but I can still use the trolley system to get to Qualcomm Stadium and I can walk to Seashore Village.
The second map I have defined the available buildings for a potential youth center that fit the profile of high youth population in residential areas. There are six to choose from. I ran into a couple of problems in the second map. When I joined the two layers in step 3 Union of City Zones and Census Block Layers, it appeared to only bring in the information from the Census Block. However, after scrolling down passed parcel number 300 I found this not to be a problem. The information was there. So I learned to look at the whole attributes table not just what apppears on the screen.

Module 1 San Diego Zoo

I did not have any problems with this assignment. However, it was good practice in getting use to the GIS environment again.

Question Answers:

1. Why would this hotel be a desirable location?
It is the closest hotel to the ocean, yet still has access to the trolly system.

2. What is the hotel's telephone number?
(619)234-1500

3. What is the address of Seaport Village?
849 W. Harbor Dr. San Diego, CA 92101

4. Approximately how far is it from the Marriott Hotel and Marina to Seaport Village?
.33 miles

5. Approximately how far is the nearest trolley stop?
.14 miles

6. What is the name of the trolley stop next to Qualcomm Stadium?
Stadium