Network Analysis: Report Week for Tampa Evacuation

It has been a very long week. Lots of excitement and drawing of Storm Drains with Brevard County GIS Dept. I am learning a great deal and keeping busy. For this Special Topics assignment, I completed my work on the Tampa Bay Evacuation project by compiling a Pamphlet that could be used to inform relatives and hospital patients of the Tampa General Hospital of critical information in the event of an evacuation. Below is one page of the pamphlet I created.

Another Network Analysis I performed was to compute multiple evacuation routes from downtown Tampa to Middleton High School Shelter. This involved setting-up the Network Analysis to load or account for fifteen different locations in the downtown Tampa area. Here;s my results:

Another Network Analysis I ran was to generate multiple polygons to find the closest shelter, there were three to consider, for residents in the Tampa area. The analysis was interesting  because I cannot remember using this tool before though I do recall using the Multiple Ring Buffer. This was better. Here's my map for the Closest Shelter:

Land Use Land Cover: Pascagoula, Mississippi

Another fun week! This week I worked with the USGS Andersonian system for classification of  Land Use Land Cover. I continue to hone my skills for using, Shape/Size, Shadows, Patterns, and Association, for identifying various land features. In this exercise, we used the USGS Anderson framework for naming Land features. The area we examined was Pascagoula, MS. This location has loads of water features. Digitizing the water or the river, was my biggest challenge. I took a large cut at trying to draw my initial polygon around as much water as I could only to have the polygon distort or completely disappear. I finally got the Create Features to work by digitizing smaller areas at a time. This work can be tedious, but I enjoyed it very much. As it happens, I am working on a similar project at my internship with Brevard County, where I am digitizing and updating storm drain pipes throughout the county.    

Network Analysis Week 2 - Tampa Evacuation Routes

This week it was time to analyze our data from the Prepare Week for the Tampa Evacuation exercise. The objective was to find the closest shelter for residents in specific areas in Tampa. Additional objectives included finding the best routes to supply the Shelters from the Tampa Armory and where and how to best evacuate patients from Tampa General Hospital located on Davis Island.

I learned a lot using the Network Analyst Toolbar and the Network Analyst Window. I created a new Network Dataset and set-up the network using Time (seconds) as the Scaled Cost to be evaluated relative to the route selection. I also used the Flood Zones layer (grid code) to group the Scaled Cost to be evaluated in the route selection. I created additional polygons to form the three sections around the Shelter facilities where residents would evacuate to in the event of flooding. I believe this was the most important message to convey, not that a hospital evacuation nor delivery of needed supplies from the Armory aren't important, it's just that I felt informing thousands of potentially panicking people (the triple "P" threat) where to go for safe shelter seems more important to me. Below is the map I created this week.

GIS 4035 - Visual Interpretation

This has been another busy week. The Lab for Photo Interpretation and Remote Sensors was actually a three for one.

The first Exercise for Visual Interpretation was to use Tone and Texture to discern various features using an aerial photo. I used an aerial photo that showed features such as a runway, housing subdivisions, water and vegetation. Tone is defined as the  brightness or darkness of an area and the first part of the lab had us classify areas from very light, to very dark. Using the "Convert Graphics to Features" went smoothly for the first Exercise, but I had some technical challenges for the second Exercise. Another objective of this lab was to look critically at the features you are given in an aerial photo so that you can distinguish the subtle differences between organic and man-made features. Below is the map I created for Exercise 1:

  Exercise 2 consisted of Identifying Features by using Shape & Size, Shadows, Patterns and Association. The objective here was to use all available information to ensure you correctly identified the object or feature you were looking at. As I said above, I had some technical challenges with part 2 with the "Convert Graphics to Features" option. It  seemed as though each time I needed to convert my selection (Shape & Size, Shadows, Patterns and Association) the option was greyed-out and not available. I tried Starting an Editing session and Stopping Editing; I tried opening and closing AcrMap. I walked away for a while and when I came back, the Convert option was still not available. Somehow, I did get the Convert Graphics to Features to work....mostly. But I do not know why the option was greyed-out.  Below is my map for Exercise 2:

The last portion of the Lab, Interpreting Color, had us use two .tif's to compare the indicated color of features using True Color and False Color. False Color is also called Color Infrared. I found various features including land, water, healthy vegetation and distressed vegetation. The colors I found matched closely, but were not exactly the same as what the "legend" for "False Color IR vs True Color" stated in the Lab instructions.

GIS 4930 Special Topics: Project1 Network Analyst

I know I had a Summer break but where did the time go? It feels like it's been a very long time since I have done Lab Work, while at the same time, where did the Summer Break go to?

This week, I start GIS 4930 Special Topics, with a Network Analyst project. The project, is broken into three one week phases - good thing too.  So, this week, I begin with reviewing my data and commencing the "Prepare Week." The following weeks I will actually conduct the "Analysis" and write the "Report."

The scenario is that I have been hired by the city of Tampa Bay to conduct an analysis of roads that could be used for evacuation in the event a hurricane causes flooding. I will use the following information:

1. Classified DEM polygon layer (with appropriate color scheme)
2. Flood Zone layer with appropriate color scheme
3. Hospitals, police stations, fire stations, shelters, national guard armory
4. Roads

This week's objective was to organize and prepare by assembling and preparing all my data. I used a Clipping tool (MassClip) and Re-projection tool (MassProject) and I re-classified a DEM and converted it from a Raster to Polygon. The Python work was very cool as I just finished GIS 5103, Python Programming; I could actually understand and appreciate the Tools written using Python. The last part of the exercise was to make a map package and share my map with a colleague. This included writing an email to let this person know what I had done and solicit feedback. I think writing the email was a challenge since I did not know the level of detail required for this fictitious colleague. Here's what my "Prepare map" looks like at this point. I can always spend much more time on any lab and I am sure I will tweek this map as I conduct the next Phase of Project1 - Analysis Week.

GIS5103 - Sharing Tools

I have somehow made it to the last Module of GIS 5103 - GIS Programming, otherwise known as "Python."  I must admit, I have learned more than I could absorb and the journey has been a hoot. I have learned more about coding and how to use Python for GIS applications than I ever thought possible. 

In this last Module we covered how to create a tool and then securely share it. The basic process to make a script tool involves writing the script, making a toolbox and then "importing" the script to the toolbox. In this way, you can share the tool and even provide a password to securely transmit the tool to colleagues.  Below is the tool dialog window for the tool I created:

This tool takes an input feature class and adds random points then places a buffer around the points. When successfully run, the output of the tool looks like this:

Another cool thing we learned was the basic steps to make Python scripts or other files visible in ArcCatalog, First, you must add the file extension (PY in the case of Python files) to the File Types tab. First, select “Customize” from the main menu with ArcCatalog open; select “ArcCatalog Options” from the dropdown menu and then select the File Types tab. From this point you can select “New Types” and from the list, (I had no list and had to manually type in my file extension) select the file extension you want to add. 

As I said, I learned quite a bit during this course. I enjoyed the entire semester and all aspects of learning how to use Python. My challenge each week had been and remains, that I could spend countless hours going over a script and there always seemed to be at least one item that caused me to stall; I just could not get that last block of code to run properly like in Module 8, “Working with Geometries.” I was off to a good start with that script but I just could not get the darn thing to work properly.  On the other hand, one of the best things about this course was the “Discussion Board” and the “Helping Each Other” section of each Module. I don’t feel as though I posted too many questions, but I guarantee you that I read each and every question and answer, and that is the only reason I was able to accomplish as much as I did. I know we are all in this together and I couldn’t be happier about the company I am keeping nowadays. Thank you to everyone who posted a question and answer and occasionally “a glimpse of the working code.”  Good luck to all of us in our future GIS endeavors.    

GIS4048 Final Project-Brevard County Solar Project

This Final Project was awesome! This project was a lot of work but it was a great experience. The task was to conduct a Location Decision analysis for a subject of your choice. I was excited to tackle this project and I decided to do my Location Decision analysis for a proposed Solar Center in Brevard County. I was partially influenced to select this subject because I feel strongly that we should aggressively pursue Solar Energy production and the fact that I live in Brevard County.

My "client" was the "Special Project Coordinator for Brevard County, Mr. Estrella Sol (Star Sun, pretty clever, if I do say so myself). Brevard County, through new leadership, wants to become known as the "Solar Coast" as well as the "Space Coast." At least, that is the scenario I invented for this Final Project. In reality, FPLis building new Solar Centers in DeSoto, Charlotte and Manatee Counties, and I am saying that Brevard County wants to be a part of this opportunity.  The criteria for this Solar center is:

                                   #1 The parcel must be owned by Brevard County

                                   #2 The parcel must be within 1 mile of a major road

                                   #3 The parcel must be at least 1000 yards from schools

                                   #4 The parcel must be greater than 100 acres

                                   #5 The parcel should avoid disturbing areas of 

                                        environmentally sensitive lands 

For this project I used, Geoprocessing tools such as Clip, Buffer, Euclidean Distance, ModelBuilder and Weighted Analysis. The data I used was as follows:

 


I was also fortunate to have the Brevard County Appraiser website available for my reference. I was able to view aerials of the Parcels I was considering for this project.

After establishing the environment and setting my projection, I used a couple of Select By Attribute searches to limit the field of possible Parcels for consideration; Brevard County has 287,853 parcels . I selected Parcels owned by Brevard County (Select By Attribute > ONAME = Brevard County; this gave me 1806 parcels) and then Parcels greater than 100 Acres (this left me with only 48 parcels). Then, I used ModelBuilder to run  a process to find the Parcels that are near (within 1 mile of) a Major Road, I-95.

  
The last portion of the Project Analysis was to create a Weighted Analysis model. I used the Feature to Raster tool on three datasets:

Parcels_100Acres to ConvertParcelsBC100

MajorRoads_I95 to ConvertMajorRoads

BC_schools_selection to ConvertSchools

The Weighed Analysis model produced a map that seemed to favor the largest parcels, but it was not as conclusive as I had hoped.  

Finally, I was able to use the Brevard County Appraiser's website to review aerials of several of the Parcels. I found some Parcels that looked like they met the criteria, but the aerial image showed that the parcel was actually underwater; easy to eliminate that parcel from consideration. In the end I was able to find three great parcels that met all the criteria including avoiding sensitive lands.  Here's my final map and a link to my final presentation:

This exercise and the entire course of GIS 4048 Applications in GIS, has been very illuminating. I thoroughly enjoyed studying the different GIS applications such as HomeIand Security, Natural hazards and Urban Planning. Once again, I feel like I could have spent even more time working on this final project and all of the projects throughout the semester. If I had more time on this Final Project, I could have provided a written report that included all the information from the Brevard website and I believe this would have been greatly valuable to my customer, Mr. Estrella Sol.  Also, if I had found data about soil type and slope, that too would have been very useful. We take for granted, living in Florida, that slope is not a factor, however, I know, for instance, that in the Tallahassee area “rolling hills” seem to be the norm. A solar site on the wrong side of a hill would be disastrous (better use hillside shading for this analysis). I know I have learned a lot from this course; now my challenge is to continue to use the skills I have gained. To that end I am doing volunteer work with the Brevard County GIS Department and I hope to find full-time employment in the not-too-distant-future.