Lab 2 - Lahars

GIS 4048

 

 

 

In this weeks lab we learned about Lahars and how these Natural Hazards that are typically produced by volcanos can cause damage as they sweep down hillsides carrying rocks, mud, water, debris and whatever else they may pick up along their travel path.  Due to their destructive nature we learned how to design a map that could forecast the flow direction and help provide those in it's path a way to be informed of the dangers.  Above you will see a map that I created for a study area around Mount Hood.  Utilizing Analysis Tools in GIS I was able to take a Digital Elevation Map and produce an expected flow path.  With this data in hand I was then able to see what Census Blocks would be affected and provide an accurate measurement of the people the flow may affect along the path.  I was also able to provide a visual for certain schools that fall within the hazard zone as well.

 

Overall I enjoyed this lab.  I learned several new tools that will help me in my daily work and I now can see how to effectively use DEM's to predict flow patterns.



Cub Scout Popcorn Sales in South Plainfield, New Jersey

The application that I would like to look into is how to utilize GIS to track and improve sales of popcorn for South Plainfield, New Jersey, Cub Scout Pack 207.  Popcorn sales are a way that the Cub Scouts can do fundraising that will finance their future endeavors for the year.   This fundraiser typically is quite large and the scouts go house to house, as well as setting up locations in front of stores.  I would like to track where the sales are productive, and see what types of goods are selling the best in locations. 

I believe this application will work directly with marketing and retail.  With a better understanding of where the sales are most productive, as well as knowing what type of product is selling, we can focus our efforts and spend more time in the areas that raise the most money. 

I believe one of the challenging issues with this task will be with teaching the scouts how to gather data properly, as well as coming up with a way that this can be simplified so that the data can be used in the future.  I believe one of these solutions would be to come up with a mobile application through GIS Online, or perhaps a spreadsheet through Google docs that all the children can access while doing sales.

I find this project to be interesting because as a Cub Scout leader I can introduce the young scouts to a great technology, and at the same time allow them to focus on earning more money that will be utilized in projects and trips for the next year.

I would like to see how this application can be put into place for little to no cost, and also learn the best way to gather and present the data for future use.  I believe this can then be shared to other packs and help the scouts become more productive in this fundraising project.  My hope is that they will also see where GIS can be used in other projects that they may do in the future.

GIS Dream Job

I went outside the normal searching locations to find my "dream job".  The location is not where I would want it to be, but it's on the right track of where I would like to be.  The website that I found this position is linked here.  Some of the requirements for this position include good experience with ESRI SDE GeoDatabase file structure and integration with SQL and Oracle.  With my 10+ years experience as a Computer Administrator and working with multiple databases including ESRI GeoDatabases I feel this would be a great fit for me.  I have found all of the classes to be very interesting in my UWF schedule.  I think the Introduction to GIS course spent a good amount of time introducing students to the file structure of a GeoDatabase.  Unfortunately for my dream job, I have not come across a good course at UWF that will enforce the ESRI SDE GeoDatabase file structure and the building of a GeoDatabase from the ground up for an organization.  I would love to do a lab that focused strictly on the building of a SDE environment. 

Below are the requirements for the career I linked above:

• A four year degree in Computer Science or equivalent work experience
• A minimum 5 years recent experience managing Oracle and SQL Server databases in a production environment
• Ability to write triggers, functions and procedures
• Knowledge with PL-SQL and T-SQL scripting
• Windows 2008/2003 server and server applications
• Experience working with virtualization technologies (Hyper V and VMWare).
• IIS Knowledge, installation, configuration and troubleshooting skills
• Esri ArcGIS Server knowledge specifically with ArcSDE
• Proactive self-starter with the ability drive projects through to completion
• Strong analysis and troubleshooting skills including experience with related tools

I meet all of these requirements with the exception of the ArcSDE Server knowledge.  All of the organizations I worked for did not have SDE capabilities, but I am looking into ESRI classes that may give me the experience I need in the future.

Unfortunately the link does not provide a salary listing, but I am pretty sure this type of position is competitively marketed.

Lab 10 - Supervised Image Classification

GIS 4035

 

 

The map above is of Germantown, Md.  In this weeks project we were to work with Supervised Image Classification.  I worked to create spectral signatures and AOI features within EDRAS.  I was then able to produce a classified image from the satellite image that identified key areas of Land Use so they could be monitored moving forward.  This exercise also reinforced the ability to identify spectral confusion by identifying features that might have similar characteristics, but when viewed in different bands became more unique to identify.

 

Bringing all these elements together I was able to produce the above map, and show where there may be discrepancies in the classification with the distance inset provided.

 

Overall I enjoyed this lab, and it allowed me to gain a better knowledge of how images can assist in land classification through automated processes and tools in the EDRAS program.



Lab 9: Unsupervised Classification

GIS 4035

 

 

In Lab 9 we let the computer do some of the work.  Unsupervised Classification was my introduction to automated classification of an image based off of different spatial and spectral resolutions.  There was a little manual work to be done, but overall the program assisted greatly.  I was able to use both ArcGIS as well as ERDAS to reclassify and code images simply based off of the pixel colors and grouping like pixels together. 

 

In ArcMap I utilized tools like Maximum Likelihood Classification tool, and the Iso Cluster tool, while in ERDAS I utilized tools such as Unsupervised Classification found in the Raster tab, Classification group.

 

Ultimately using the tools provided I was able to generate the map above which shows each Class by name, and from this I was able to calculate the total Permeable and Impermeable surfaces.



Lab 8 - Thermal and Multispectral Analysis

GIS - 4035

 

 

In this weeks lab I was given the opportunity to interpret radiant energy, and utilize both ArcMap and ERDAS to interpret thermal infrared data from a multispectral image.  The map above highlights the merger of two rivers in Ecuador, the Daule River and the Babahayo river.  I approached the area with two questions:  Is there a lot of Vegetation at the Daule River delta?  Which river is warmer, the Daule River or the Babahayo River?

 

Utilizing a NIR band combination (R-4, G-3, B-2) I was able to show that there is little to no vegetation at the river delta, as this area is mostly urban.  I was then able to utilize the Thermal Band (band 6) and show that the Daule River (darker blue) is in fact warmer than the Babahayo River (lighter blue). 

 

Overall I found it quite interesting all the data you can gather and show utilizing the multispectral images.  I feel that the information that a person can gather from these images can be put to many uses and offer the viewer an opportunity to see information that isn't visible to the naked eye.

 

Lab 7 - Multispectral Analysis

GIS 4035

In this weeks lab we looked at image histograms, how to operate the inquire cursor, interpreting images, utilizing the help function, and interpreting digital data.  When then utilized the skills that we learned in the exercises to properly locate and accentuate a specific location within an image that was provided.  In this case, an image of forest surrounding the Olympic Mountains in Washington State.

The first Figure located was a dark waterbody.  Utilizing near infrared RGB settings to make the water darker, the reader can easily identify the dark waterbodies.  As described in the map the pixel values ranged from 12 and 18 in band 4.  This was observed utilizing the inquire cursor in ERDAS.

The next Figure that I located was the snowcapped mountains.  These features produced pixel values of 200 in the 1-4 band layers.  These features also had a large spike between pixel values 9 and 11 in Bands 5 and 6.  These features can be observed in the image above as yellow.

My final figure was an area of water that layers 1-3 seemed much brighter than normal, with layer 4 become slightly more brighter. Layers 5 and 6 stayed unchanged.  I utilized the band selection to set up 1-3 and then changed the blue band between 5 and 6 to identify the location that the description was illustrating.  In this case the description identified shallow waterbodies that could be seen as a greenish color.