Special Topics, Week 3: Stats Analyze Week - Meth Labs

This week in lab we preformed an Ordinary Least Squares Regression Analysis.  This was done to identify and remove certain socio-economic variables that don't have a strong connection to the meth lab density.  The area of focus was Charleston, West Virginia.  Using specific measures, variables were removed to increase the Adjusted R-Squared value, or the accuracy of the model.  

This OLS Table displays variables that affect where a meth lab might occur.
This combination of variables resulted in an Adjusted R-Squared value of .727.

After running the OLS tool various times (about 22 times), I settled on these variables.  The above table displays the list of socio-economic factors which I thought were relevant to where a meth lab might be located.  Based on the Jarque-Bera statistic, my model does not appear to be biased.  

Next, we displayed this data in a map.  Below is a map of the study area with the results of my OLS.  The areas in yellow have a standard deviation of between -0.5 and 0.5 which means that it is an accurate prediction.  As you can see, other areas were over predicted while some were under predicted.

This map shows the resulting standard deviations.  The census tracts with a std value of
between -0.5 and 0.5 are accurate predictions of the number of meth labs in those areas.

Special Topics, Week 1 & 2: Stats Prepare Week - Meth Labs

This week was our first week of work in my Special Topics course.  First we had to manipulate some data within an attribute table.  This data contained information from two counties in West Virginia and were related to several Methamphetamine labs that were busted in the area between 2004 and 2008.  

We also had to create a base map of the study area.  It was kind of up to us as far as what's displayed in it.  I decided to display a basic outline of the study area and show the meth lab concentration.  I also provided an inset map to give reference to where in WV these two counties were located.

Base map of study area for meth lab distribution study in Charleston, West Virginia.

Finally, we had to start a report that will accompany this study.  We had to write an introduction about the drug, Methamphetamine and provide some background information about the study area and the data we'll be looking at.  I'm intrigued to see how this report will turn out in the coming weeks.

Remote Sensing & Photo Interpretation, Mod2: Visual Interpretation

For the second week of this class, we took a look at some aerial photographs.  The first exercise was to focus on tone and texture.  We were to identify various areas in the photo depicting 5 different levels on both tone and texture.  They are identified by color and then labeled by their varying degrees.  

Identifying various forms of tone and texture in an aerial photograph.

The second part of this exercise was to determine what things were in an aerial photo based on four different criteria.  They were: Association, Patterns, Shadows and Size & Shape.  We identified three in each category and two in the Association category.  Each category is designated by a different color.

Identifying features in an aerial photograph based on different criteria.

Applications in GIS, Final Project

Powerpoint Presentation: Here

Slide -by- Slide Commentary: Here

GIS Programming, Lab 11: Sharing Tools

Screen shot of the tool dialog box and resulting map in ArcMap 

This week we learned how to share custom tools.  We were given a script where we needed to make a few edits.  Once those edits were done, the script was embedded into the script tool.  This was done because it makes it easier to share.  We also learned how to password protect the tool.  The above screen shot is of the tool dialog box and the resulting map in ArcMap.

This was our last lab and I am grateful.  This course was definitely challenging but I did learn a lot.  Overall, it was a good experience and I can see how I can take away a lot from it and use in the GIS work industry.    

GIS Programming, Lab 10: Creating Custom Tools

This week we learned how to create a custom tool using a script.  We had to modify a script and set the parameters.  Below is the result of setting the parameters of the script tool.

MultiClip tool parameter window

Next we had to run the tool.  The print statements don't appear when running a script tool so we had to change them to AddMessage statements.  We also had to modify the arguments slightly as well.  The commas needed to be replaced with "+" signs.  After doing so, informative messages appeared in the dialog box - allowing users to see the progress of the script tool.

MultiClip tool dialog window displaying messages of completed actions and successful run

GIS Programming, Lab 9: Debugging and Error Handling

This week we worked on debugging and handling errors that I (tirelessly) encounter.  This lab was super helpful and I almost wish it came earlier in the semester.  

We were provided with two script templates which were littered with (okay, maybe not littered but had several) errors.  These errors were both syntax errors and and exceptions.  The first one, we had to fix these issues to allow the script to write the names of all the airports in the airport shape file from week six. 

Screen shot of my list of airports.

In the second script, again, we had to locate and fix errors that we came across while checking, debugging and attempting to run.  Once everything was fixed, the script printed each data frame's name and the layers it contained within the Austin_TX.mxd we worked with last week.

Screenshot of the data frames listed and the layer names they contain.

Overall, a very helpful lab!