It was quite a detailed project, involving downloading aerial orthographic raster images, shapefile data, and data from an Excel file. The aerial data was added first, so its projection defined the projection for the whole Dataframe. We then had to convert the Excel file to a shapefile, then reproject the all the shapefile vector datasets for Florida county lines, major roads, quadrangle boundaries and locations of petroleum storage tanks that were being monitored to make sure they were not contaminating their surroundings. I found that because of my sufficient preparation, organization, extreme attention to detail and paranoia, this was not difficult.
I had no problems with making the map and had time to add inset map dataframes and experiment with the format. It was so helpful to read the lab instructions very carefully ahead of time, and understand what needed to be done, then lay out a written procedure with necessary transformations of projections listed for all layers before starting.
The part that taught me the biggest lesson this week also involves organization: the best way to assemble all metadata and file paths as you proceed with making the map. I don't know that I would have known just what I needed to do before I started. I made notes, but they weren't quite good enough. It was a big job to get it all together at the end. In the future, I will now know what I need to do, and the way I need to list filepaths for all data, as I go along.
Just how important it is to continuously organize the metadata and list all the paths for all the files, as part of the map-making process, is the most useful lesson I learned this week.
No comments:
Post a Comment