GIS 4930 - Statistical Analysis of Meth Lab Locations

We're starting a new project this week that involves doing statistical analysis of meth lab locations as an attempt to find correlations with population, geography and economic factors that may aid in predicting trouble spots for meth preparation.

The map below is a basic map of the study area showing methamphetamine labs that were interdicted over the course of 2004-2008 in and around Charleston, West Virginia. The study area layer has attributes for census tracts that will be correlated with the location of the labs. Preparations were made this week to create further attribute fields for use in the analysis stage of this project.

Meth Labs in Charleston, WV (2004-2008)

GIS 4930 - Completed MTR Story Map

The work of the past two weeks involved coordinating amongst my group as we all took a LandSat image from 2010 that covers a portion of our study area to analyze for evidence of mountain top removal. The analysis was fairly basic, and in all likelihood did not produce a robust set of MTR location data. See the previous entry for details of the analysis. I ended up doing my analysis over and got better, but still iffy, results.

Each of our team produced a layer package with our analysis as a polygon layer. I merged these into one unit and produced a calculation for acres covered by our MTR zones as well as an estimate of its accuracy, which was based on only a sparse number of randomly selected points. The sparsity was an artifact of the time it would take to do a thorough accuracy assessment.

Once the layers were merged, they were shared back with the entire group and we used them in our final story map.

Two layers [MTR zones & drainage] sans context - as they were uploaded to arcgis online.

GIS 4930 - Mountain Top Removal - Analyze Week - Unsupervised Classification

This week an analysis of LandSat imagery from 2010 within the study area was performed. After inspecting a raster from 2005 and a shapefile associated with it that showed mountain top removal from that time period, an unsupervised classification was performed on the 2010 imagery. With the previous data as a guide, classes were then designated as either MTR (areas where mountain top removal occurred) or non MTR. A new raster was then generated from this that only showed the MTR areas. The screen shot below shows the result, which will be integrated with reclassifications from classmates on my team as this project continues.

Screenshot showing reclassified raster image