Lab 2 – Coordinate Systems & Map Projections

Lab 2 – Coordinate Systems & Map Projections

 

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Focusing specifically on projections, this lab involved exercises in choosing a correct projection for a given task, determining what projection a given dataset was in, changing a dataset’s projection using the Project tool, defining a dataset’s projection using the Define Projection tool, and creating a custom projection for a custom task. To model ashfall risk from a potential Yellowstone Caldera eruption, we modified the standard parallels and central meridian of a USA Contiguous Equidistant Conic projection in order to maximize accuracy of distance in the Northwest USA region. The United States Geological Survey (USGS) has determined there is potential for 1.5 centimeters of ash fall within 500 kilometers of the Yellowstone Caldera. In the event of the Yellowstone Caldera eruption, ash would cover a much greater area of the United States, though we are interested in the areas at highest risk. Shown below is a map depicting the towns that fall within 500 kilometers of the eruption site. To begin analysis, it was important to identify issues of projection in the data given. Manually editing the USA Contiguous Equidistant Conic projection to better fit our area of study was the first step. Our Central Meridian and Latitude of Origin were changed to the coordinates of Yellowstone, with our Standard Parallels two degrees North and South of Yellowstone. Editing these aspects minimized distortion at the location of interest. To re-project all data layers, the ‘Iterate Feature Class’, ‘If Coordinate System Is’ and ‘Project” geoprocessing tools were used. The ‘If Coordinate System Is’ tool read through each file in our geodatabase to identify which data needed to be re-projected. If the data was not correctly projected, it fed into the ‘Project’ tool, changing it to our custom projection. With analysis created, 35 towns were identified in the 500 kilometer buffer around the Yellowstone Caldera.

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Lab 2 Practical Exam

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Our task for this practical exam was to create a map showing the closest National Park or Preserve to any given area in the U.S. We were given all of the data necessary to run this analysis, but there were issues with the projections for the datasets that we had to sort out. This included redefining a projection for a dataset that was in the wrong projection, figuring out the projection for a dataset which had lost its .prj file, and then reprojecting all the data so that it was in an appropriate projection for our analysis. I then used the Thiessen Polygon tool to find the areas closest to National Parks and Preserves in the United States. I then clipped the Thiessen Polygons to a US shapefile and created an annotation feature class for all labeling. This was one of the most enjoyable exams for me I had a lot of fun with the cartography side of this project and using the Thiessen Polygon tool.

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