Data Gathering

Introduction:

To understand the impacts of frac sand mining in western Wisconsin I needed to be able to download data from a few different sources.  The goals of this lab were to promote the skill of file management, use python code to create a geodatabase from the downloaded data, and be able to extract data from multiple sources. 

Methods:

I downloaded data from several different locations which include:

• The first was downloading the Railway systems from the US Department of Transportation statistics website.
• The next is the USGS National Map Viewer which allowed me to download data that included the National Land Cover and elevation from their website. 
• Next, I downloaded data from the USDA Geospatial Data Gateway which allowed myself to download cropland which comes from the U.S. Department of Agriculture. Website
• I then downloaded a Geodatabase for Trempealeau County, Wisconsin from the Land Records Office. Website
• Finally, I downloaded data from the Department of Agriculture once again, but from their Soil Survey website for soil data.

Data Accuracy:

• Scale - relationship between depiction on map and its actual size in the real world
• Effective Resolution - 
• Minimum mapping unit - The smallest plotable object at a certain scale. 
• Planimetric Coordinate Accuracy - How close the objects are to the real location on the Earth. 
• Lineage - a documentation that shows how the data was collected, used, and by who.
• Temporal accuracy - How up to date the data is, and when it was published. 
• Attribute accuracy - How accurate the data is represented when compared to real world.  The data is then recorded as a specific number for metric attributes and as an accuracy percentage for categorical data.

Conclusion:

This lab was one of the most difficult and frustrating yet.  It was challenging me in every way possible to figure how how to manipulate the data to correctly display it.  I was having trouble organizing, maintaining, and keeping it all together. I however did learn a lot from this lab and found it very important lab to go through. I learned many skills from this assignment that I will take with to future assignments. 

Python Scripts

Introduction:

Python is a computer programming program that is very user friendly is and is incredibly easy to pick up with a small amount of help along the way.  I found it easy to understand, and easy to find help using ESRI's online help function to guide myself through the process.

Script 1:

In Lab 5 I was able to create a script which allowed me to project, clip, and load rasters into a geodatabase, which used a loop code to go through the rasters and determine its datum.  The code will then decide if it needs to be changed and will apply the proper projection.

Script 2:

In lab 7 we had to select mines from the all_mines feature class that was given to us in the ex7.gdb.  These mines contained mines that are in Wisconsin that we also already worked on for geocoding. We had to select mines that are active and farther away than 1.5km from a rail road system.  Using this code allows us to find the mines that have a high impact on the road systems from trucks transporting their sand.

Script 3:

In lab 8 we utilized this script above to create a weighted model.  I decided to put weight onto the Schools because I feel they are a very important factor in deciding where to place a mine.  The point of this script is to show the difference of putting on different weights on the different variables that we used.  I noticed when I ran this one it really did put a larger impact on the schools area making it seem more important than the rest of the variables.