Week 7-8: The Data Hunt

This week was the midterm for Intro2GIS and it was definitely a piece of work. By piece of work I mean it was a two week period of hunting down data, trying it out in ArcMap, and then searching for more data. My task was to find nine different pieces of data for Highlands County, FL and then create a graphic displaying all of it. The data consisted of the county boundary, cities and towns within the county, public lands within the county, all surface water within the county, major roads within the county, wetlands within the county, invasive plants within the county, one DOQQ inside the county, and one DEM file covering the entirety of the county. Fortunately all of the data was available from labins.org or the Florida Geographic Data Library website (http://www.fgdl.org/metadataexplorer/explorer.jsp). It took me a long time to find all of the data but it was all there from reputable publishers complete with metadata and spatial references. I tried a couple of quick Google searches for data and checked the county GIS page but I had more faith in the data I found from FGDL so I dedicated my time to looking at a lot of their files. The final product is pictured below.

There was a lot of information to include and the whole region was covered in water so I created three separate data frames to display it all. Besides finding the data the other two big aspects of this project were ensuring all of the data was displayed in the same projection and and clipping large files to work with a smaller extent. The projections part was pretty simple since we spent the last two weeks practicing with spatial references. I was lucky and most of the data I found was already projected in Albers Conical Equal Area. Clipping data files was also a simple process once I worked through it the first time and found the Clip Tool in ArcToolbox. Almost all of the files I downloaded covered the entire state of Florida so I clipped them all the the county boundary for Highlands. Not only does clipping the data make for a prettier picture, it also makes the map layers load faster in ArcMap. This was not a big issue when we were working with two or three layer but when I had 6-12 layers open in three different data frames it made all the difference in the world.

I have one other thing I'd like to note from this week that cannot be seen in this graphic. Data organization and naming conventions are crazy with GIS data. Every file ii clipped was given a straightforward name and placed in a separate folder from all of my downloaded data. I did not want to have to search through all the funny named files again after I found the one piece I needed.