The following post is out of order. Creating a geodatabase and acquiring data would be the first logical step. Due to a federal government shutdown shortly after our class began this exercise, we were forced to put this important step on hold as most of our data was to be accessed from federal government websites. Please keep in mind that, under normal circumstances, this post would precede my geocoding post.
Goals
The goal of this exercise was to become familiar with acquiring geospatial data from various sources on the Internet, then importing this data into ArcGIS for use and interpretation. During this process, we were required to design and set up a geodatabase for storing all this data, as well as make sure everything was projected in the same coordinate system.
Methods
The first data set I downloaded was the railroad data from the National Atlas website. This data, like the others, was compressed in a zip file and had to be unzipped before use. Next, I visited the National Map Viewer website at http://nationalmap.gov/viewers.html. Here, using the interactive web map, I selected Trempealeau County. There were several data sets available, but I downloaded only landcover and DEM (Digital Elevation Model) data. From the USDA Geospatial Data Gateway (http://datagateway.nrcs.usda.gov/), I downloaded cropland data for Wisconsin. Lastly, I downloaded soil survey data from the USDA soil survey website (http://websoilsurvey.sc.egov.usda.gov/App/HomePage.htm).
Other than just unzipping it, some of the data had to be manipulated somewhat before it could be used. The elevation data was sent in two separate raster files so that a singe image wasn't too large of a file. In order to make one DEM raster image, I ran the mosaic to new raster tool. This created a single, uniform image that covered Trempealeau County.
I decided to use NAD 1983 Wisconsin Transverse Mercator for my projection, as this one would work best to display the whole state of Wisconsin. After I had that decided, I created a geodatabase and imported all of the data I had acquired. I also created a feature data set for the natural resource feature classes.
Results
Figure 1 - Data obtained from government websites |
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