Remote Sensing & Photo Interpretation, Mod8: Thermal & Multispectral Analysis

For this lab, I utilized both ERDAS and ArcMap to combine several layers of imagery into one single multispectral layer.  In order to get my specific feature, the city of Guayaquil, to stand apart from the rest of the image I needed to find the right band combination.  By working in ERDAS and ArcMap, I was able to fool around a bit with the bands and histograms until I found a combination that I liked.  This combination then needed to bring out the urban areas of the city and provide an obvious distinction between urban and vegetation, agricultural and even the river. 

I think my final combination of R: 3, G: 1, B: 6 and adjusted breakpoints really creates an image that allows you to see the urbanized areas of Guayaquil, Ecuador.  These areas appear as a bright yellow-ish green color which contrasts nicely with the dark greens, blues and pinks of the other parts of the land.  This also allows the river to be a lime color with a smooth and constant texture.  

Urban areas of Guayaquil, Ecuador using the band combination of R: 3, G: 1, B: 6.

Special Topics, Week 8: GIS Web Applications - Prepare Week - Storyboard Development

This week we started a new module and we're focusing on GIS web applications.  We're working on story maps.  Story maps are interactive maps that are generally less technical and more descriptive.  They are designed to tell a story but they also include pictures or images, descriptive texts, attached documents and even helpful hyperlinks.  For prepare week, I put together a storyboard for what I want my story map to show and how I want my story told.  The basis of my map is going to be my move from Wisconsin to Hawaii.  I'll be flying out of Chicago, have an extended layover in San Diego to see some sites and friends and I'll land in Honolulu.  I'll see some classic Honolulu sites before my final flight to the island of Maui.  I want my map to show my trip and the sites that I am going to visit along my way.

I plan on using various images and configured pop-ups to convey information about the individual sites.  Below is an example of one of the images I might use for my stop in Honolulu.

Diamond Head Crater State Park, Honolulu, HI

Remote Sensing & Photo Interpretation, Mod7: Multispectral Analysis

This week we worked with multispectral analysis.  We used various techniques to locate and identify three different features based on their histograms of each layer.  Once the features were identified, we changed the bands in order to make that one feature more prominent.  As you can see in the first map, the feature was deep water.  I decided that bands - R: Layer_5, G: Layer_2 and B: Layer_3 worked best to emphasize the deep water.  The dark blue/black lakes really stand out against the red land.

Deep water is the prominent feature in this map - clearly standing out as the black/dark areas.

The second feature we needed to identify based on histograms and an Inquire Cursor was snow-capped mountains.  To be sure that the mountains that are snow-capped really stood out and became the prominent feature in the map, I worked with the bands to create the following image.  The snow, keeping white, really pops against the green/brown landscape.  I went with: R: Layer_3, G: Layer_2 and B: Layer_1.

The snow-capped mountains are the prominent feature in this map.  Keeping the snow white and mountains green really gives a good perspective. 

The third and final feature that was identified was shallow water.  As you can see, the show water is displayed as a light and bright blue.  It distinctly stands out against the dark, almost black deep water and the red land.

The shallow water in this map stands out as it is a much brighter blue compared the the dark, almost black deeper water and red land.

This lab seemed to be pretty unclear.  There was a lot of trial and error and communication between classmates in order to figure things out.  I felt that maybe more detail or insight needed to be included in this lab.

Remote Sensing & Photo Interpretation, Mod6: Spatial Enhancement

This week we mainly worked with ERDAS and learned about spatial image enhancement.  We had a few exercises (one that had to be cancelled due to the wonderful government shutdown) that taught us about the various tools in ERDAS to create image enhancement.

We were provided with an image that had significant striping and image distortion.  Working with the Convolution filter, we used different kernel settings to manipulate the image.  Another tool that was utilized as the Fourier Transformation function.  This function greatly reduced the distracting striping in the image.  Playing around with the different kernel settings and the Fourier transformation editor, a final image was created that has limited striping, yet still maintains a certain amount of image clarity and detail.  

Spatial image enhancement after various kernel setting adjustments in the Convolution filter and a run through the Wedge tool.

Special Topics, Week 7: Network Analysis - Report Week - Hurricane Evac. & Supply Route Map Distribution

This week wraps up our venture into Network Analysis.  This week we created more specific maps for different aspects of a hurricane evacuation.  The first maps we created were evacuation routes from Tampa General Hospital to nearby St. Joseph's and Memorial hospitals.  These were inserted into an informational pamphlet to be distributed to patients and their families.  

The second maps we created were for the emergency workers and supply delivery drivers.  Three shelters were established throughout Tampa Bay and supplies needed to be delivered from the Armory located downtown.  These maps were crude maps in gray scale to be only distributed to workers and drivers.  There was a view of the overall route and close-ups or zoomed versions at intersections.  Step-by-step directions were also provided.  One example is provided below.

Route map for supply drivers and emergency workers leaving the Armory and heading to the Tampa Bay Blvd Elementary School shelter.

The final scenario that was provided was to create a map that would be distributed to the media.  This provided a very basic and simple map of a polygonal area and which shelter was located the closest.  Very little detail was added to this map, as simplicity is key when conveying information to the public.  This map was initially created in ArcMap and then exported to Adobe Illustrator for the addition of final details.  The title is printed in red as that color is often associated with emergency and "something to which to pay attention."  The shelter names and addresses are then printed in the correlating color of that area polygon.  

Map to be distributed to the media.  Attention grabbing, simple and easy to understand.  Which shelter is nearest to you?

Special Topics, Week 6: Network Analysis - Analyze Week - Hurricane Evac. & Supply Routes

During the second week of our Network Analysis project, we created driving routes.  There were three different scenarios that needed to be planned out.  Tampa Bay is about to be hit by a hurricane and there is one hospital (Tampa General) that falls within the flood zone.  The patients at this hospital will need to be evacuated and moved to hospitals on higher ground - St. Joseph's and Memorial.  Using the Network Analysis toolbar, routes were established from Tampa General to St. Joseph's and Memorial using only roads that will most likely be open and won't be flooded.  

The second scenario is that the U.S. Army National Guard needs to distribute supplies to three local shelters.  They will be departing from the armory and traveling to Tampa Bay Blvd Elementary, Middleton High School and Oak Park Elementary to deliver supplies.  Routes needed to be created from the armory to these locations.  The same methods were used as the patient evacuation routes.  

The third and final scenario was informing the public.  Areas needed to be created that were within a certain distance of a shelter.  The color coded sections on this map, allow those people to see which shelter is closest to them.  People living within the blue shaded region should head to the Tampa Bay Blvd Elementary shelter.  People within the pink area should head to the Middleton High School and people located within the green area should head to the Oak Park Elementary School.

It was an interesting week of work and I hit a snag when trying to create the color-coded polygon's.  I figured out that last week, during prepare week, I used incorrect equations when calculating driving times and distances of the streets.  I had to go back and fix that and re-create a new network dataset.  Once I realized my mistake, figured out how to fix it and created a deliverable that I needed, I was happy.  I actually enjoyed the troubleshooting (after the fact).

This is a map of patient evacuation routes, supply routes and location of nearest shelter.