Data Downloading, Interoperability, and Working with Projections: Sand Mining Suitability Project

Goals and Objectives: The goal of this exercise was to become more familiar with downloading data from multiple sources and importing that data correctly.  Another goal was to write a python script to project, clip, and load that data into a geodatabase.  This exercise really challenged our ability to organize and manage data as well.  Without proper data management, the Python script we wrote would not work.


General Methods:

The first step in creating sand mining suitability maps was to download the necessary data.  The data we need originated form several sources so I had to download the zip files from each source.  After downloading the zip files, I extracted all the data to my exercise 5 working folder.  The sources were United States department of transportation, the United States Geological Survey (USGS), United States Department of Agriculture (USDA), and Trempealeau County land records (Refer to sources below).  I then had to complete several table joins with this data.  The next step was to write a Python script that would project, clip, and load all the data into a geodatabase. After the Python script completed running, I now had several layers that were clipped and loaded into my geodatabase.  The next step in the process was simply to create a map depicting the layers that were just clipped.  The final map (figure 1) shows four maps:  Railroads, land cover/usage, crop land, and a DEM model for Tempeleau county.  Figure 2 is the python script I wrote to project, clip, and load my data into the geodatabase.

Figure 1

Figure 2

Conclusion:  Overall, this lab was complicated at first, but it taught me a lot about data management and it's importance.  We used several data sets in this exercise.  One thing to be concerned about when using multiple data sets is non-interoperablity.  When data comes form multiple sources, the format may not be completely universal, or it may not function well (or at all) with ESRI software.  It's always important to make sure your data is interoperable, especially when using multiple sources.  Overall, this lab informed me on the importance of data management and improved my ability to use Python.  

Sources

http://www.usgs.gov/

http://www.usda.gov/wps/portal/usda/usdahome

http://www.tremplocounty.com/landrecords/