Module 8 Thermal and Multispectral Analysis

In Module 8 we created composite images and continued exploring histograms, breakpoints, and band combinations to better understand and view features. In this module we were task with locating a feature of interest within a given image and creating a map, using the skills gained in this module to display the feature on a map. The map above depicts Test Range B-70 located on Eglin, AFB in Florida.

Web Applications: Prepare Week

 

For this phase of project three, in Special Topic in GIS, we were tasked with exploring the workings of a story map.  A story map is a map that uses text, multimedia, and other interactive functions, to inform, entertain, and inspire viewers about a topic.

I intend to create a story map that shows eleven points of interest within Okaloosa County, Florida.  Originally, it was to be “points of interest in my town”; however, living in Holt, Florida that would be Brown’s Gas Station, a church, and an abandoned elementary school.  So, I expanded the area to include Okaloosa County.  I plan on starting with a base map of the area and show the location of the points of interest with configured pop-up icons  Once the user clicks on the icon, it will show a brief description, with a prompt for a more detailed description, such as address, schedule of events, hours of operation, or menu depending on the location.  I do not plan to have a route or tour of the sites, but by individualizing the icons, the user should be able to click on the location of interest and find all related information with a few clicks of the mouse.

 

Module 7 Multispectial Analysis

For this module in Remote Sensing we were to identify certain features of an image based on their pixel count in certain layers.  This was accomplished using the image histogram and the inquire cursor tool.

In layer four there was a spike between pixel values 12 and 18. This was on the left side of the histogram, and from the module I knew this would mean a dark area of the image.  From the image it appeared this may be deep water. Using the search cursor I verified that there was a correlation between pixels in the histogram and the area I had selected on the image.  Once this was done I used the Inquire box and the Subset & Chip tool to select an area that best depicted this feature in the image and saved this as new file. I then opened the file in ArcMap and created the map above.

In layers 1-4 there was a small spike around pixel value 200 and a large spike between pixel values 9 and 11 in layers 5 and 6. This was on the right side of the histogram, and from the module I knew this would mean a very light area of the image.  From the image it appeared this may be the snowcapped mountains. Using the search cursor I verified that there was a correlation between pixels in the histogram and the area I had selected on the image.  Once this was done I used the Inquire box and the Subset & Chip tool to select an area that best depicted this feature in the image and saved this as  a new file.  I then opened the file in ArcMap and created the map above.

  

 

 

 

In certain areas of the water, layers 1-3 are much lighter than normal.  Layer 4 was a little brighter and layers 5 and 6 were unchanged. From the image it appeared this may be several areas of shallow water. Using the search cursor I verified that there was a correlation between pixels in the histogram and the area I had selected on the image.  Once this was done I used the Inquire box and the Subset & Chip tool to select an area that best depicted this feature in the image and saved this as a new file. I then opened the file in ArcMap and created the map above.

 

 

Module 6 Spatial Enhancement

 

 

 

Week 6 of Remote Sensing covered Spatial Enhancement.  In this module we covered various methods used to enhance imagery. The map above is the result of starting with a LandSat image and using the convolution tool to enhance the image, using the trial and error method; I finally decided that using the 3x3Sharp5 filter worked best to remove the striping and still keep the image somewhat identifiable.  I am sure that with more experience I could do a better job, but for now this is the best I could come up with.  

  

Network Analyst - Report Week

This scenario involved developing three separate crude maps for the distribution of emergency supplies by the U.S. Army National Guard to three designated storm shelters.  The map above depicts the supply route to one of those shelters. All data to complete this map had been created during the analysis week of this project.  This route is from National Guard Armory to Oak Park Elementary School.  Written directions were also produced, copied and reformatted.  This map was created in ArcMap, for ease of use, the route was shown in its entirety in one data frame, then other data frames were added showing the route in shorter segments; the reformatted driving directions were then added to the appropriate map segments then exported to Adobe Illustrator where some text was fine-tuned and it was put in a Grey-Scale format, as this would make the map easier to reproduce.  Once this was complete the map was exported as an image file.    

Network Analyst - Report Week

This map was created for a scenario which involved developing an informational pamphlet for patients and their families that required evacuation from Tampa Bay General Hospital to two other hospitals in the city. The map above depicts the evacuation route from one of those hospitals. In this case, the pamphlet was provided; however, maps and directions to the receiving hospitals needed to be created and added to the pamphlet.  All data to complete this map had been created during the analysis week of this project.  This route is from Tampa Bay General hospital to St. Joseph’s hospital.  Written directions were also produced, copied and reformatted.  Once the map was completed it was exported as an image file and placed in the pamphlet.  The reformatted driving directions were also added to the pamphlet.  Once the map was placed in the pamphlet, minor modifications were made to have the map and driving directions appear as uniform as possible while still proving useful.

Network Analyst-Analyze Week

This was the second week of my Network Analyst project.  After preparing the data last week, I calculated two evacuation routes from a hospital in the flood zone to hospitals that were close by and at a higher elevation.  Then I calculated supply routes from the National Guard Armory to the three designated Storm Shelters.  Both the evacuation routes and supply routes were then assigned a name and separate color.  This was all completed the “Routes” tool in the Network analyst toolbox in ArcGIS.  Next, using the “New Service Area” function also located in the Network Analyst toolbox, I calculated the nearest Designated Storm Shelter for areas within Tampa Bay.  Once the polygons were created they were each also given a different color.  Once the routes and storm shelter areas were calculated I created the map above and like last week shared it as a map package. Then I wrote an addendum to my E-mail explaining what I have done to date.   The map package, and e-mail were then zipped into a single file and put into the dropbox.

Intro to ERDAS Imagine and Digital Data

Week 5 of Remote Sensing covered the basics of ERDAS Imagine.  For this module we were given an opportunity to explore where some of the tools were located and how to use them. We also used the viewer to view data in ERDAS Imagine.  We then preprocessed an image for making a map in ArcGIS. I am however a little leery because the lab instruction mentioned “crashes” and using “work arounds” to make ERDAS Imagine work properly.    But with that said, I was able to create the map above without much problem.  The map depicts a sub-section of an image of forested area in Washington state which was classified into different types of ground cover.  

Network Analyst - Prepare Week

For this week in Special Topics in GIS, Project 2, I started to prepare data for a Network Analyst project. Project 2 is a hurricane evacuation scenario for the Tampa Bay, Florida area. First I clipped and re-projected all data sets into the same area and projection.  This was completed using a provided mass clipping and re-projection tool.  Then a DEM was reclassified and converted into a vector file format. From that I created a “Flood Zone” layer.   New fields were added to the streets layer in anticipation for upcoming network analysis.  After that I edited and exported the metadata.  I created a base map of the area (above), and shared it as a map package. Then I wrote an E-mail to my “employer” and a “Coworker” explaining what I have done to date, and what I think the next steps should be.  The map package, metadata, and e-mail were then zipped into a single file and put into the dropbox.