Projections and Data Collection

The lab this week consisted of two parts: projections and data collection.  Both of these things important for being able to create useful and meaningful maps.

Projections 

For the projections I downloaded a map of Florida's counties from FGDL.org, a resource for managing and distributing GIS data for the state of Florida.  The initial map I downloaded used the Albers projection.  Projections transform GIS data so that it can be mapped on a two dimensional surface.  The projection used determines how things like the shape or area, so it is important to use the correct projection when designing a map.

To explore how different projections looked, the task was to reproject our Florida map to the UTM 16 and Florida State Plane N projections.  This was done using the geoprocessing tool "project" tool and inputting our original map and choosing the new coordinate system to create the reprojection.

A map with three projections of Florida highlighting the differences in area between the projections.

The different projections looked fairly similar, but we further investigated the differences by considered the area in square miles of four different counties: Alachua, Escambia, Miami-Dade, and Polk.  Between the three projections the area of the counties was not always calculated to be the same.  This is especially apparent when looking at the Albers versus the UTM 16 projection.  The UTM 16 projection is best for the western part of Florida, so eastern counties like Miami-Dade are more distorted and thus the measurements are less accurate.  The Albers projection is designed to consider the entirety of the state of Florida so no one part is considerably more distorted than the rest.  Florida State Plane North has a similar problem to UTM 16, though it is less exaggerated.

We also learned how to handle raster projections and input their correct coordinate system to have them properly display on the map so the image doesn't show up in the middle of the ocean.

Data Collection

The other half of this lab involved data collection.  To begin, I downloaded the ArcGIS collector app onto my smartphone.  The assignment was to collect location data on public safety features and describe their condition (good, fair, and poor).  I chose to gather data on the fire hydrants located in the Oakland neighborhood of Pittsburgh, PA.

Before going out into the field I had to set up my map so that it was ready to collect data.  To do this, I created a condition domain and which had the three different choices with a description of what the choices meant.  I then created a new feature class for the fire hydrants I would be documenting.  This consisted of the condition domain, a raster field for photos, and a text field for any notes I may have.  I also set the symbology for the symbols, with blue being the best condition, green being fair, and red being poor.  I enabled editing on the file so I could collect data using my phone and I was all set to begin my field work.

I choose fire hydrants because they are plentiful and by their nature have to be accessible so I didn't have to worry about trespassing.  I collected just over 40 data points and only got a couple of funny looks when I took pictures!

A collection of fire hydrant locations and conditions in Oakland, Pittsburgh.

Did you know that the colors on fire hydrants have meanings?  There are no national regulations on fire hydrant colors, but in Pittsburgh the color of the body of the fire hydrant relates to the size of the main that the hydrants connection to (source).  Red connects to the smallest, yellow the medium, and green the largest pipes.  Dark blue also exists in Pittsburgh, but only for waterworks purposes which probably explains why I did not see any.  The caps relate to how much pressure the hydrant provides with orange being the lowest, followed by white, and then blue.  So having hydrants with unambiguous coloring is important to the ability to fight fires.  In cases were a white cap was badly discolored by rust to the point of it being orange I would mark these as poor quality as in an emergency ambiguity is the last thing you would want to deal with.  If I was doing this as a formal survey I could add additional domains for the body color and cap color so that someone could easily query the different types.

We were instructed to try out creating map packages via ArcGIS Pro and also importing our data into Google Earth via .kml files.  Of the three, ArcGIS Online was my favorite to use because it is straightforward and intuitive. 

Cartography Lab

In our second lab for the Intro to GIS class, our goal was to make a map that shows the location of the UWF main campus.  It shows the relation of the campus to the major cities, interstate highways, and rivers in Escambia county.  There is also an inset map of Florida to show where the county is in the state.

The primary goal of this lab was to familiarize ourselves with basic cartographic principles such as layout, use of color, and essential map elements.  Additionally we were encouraged to think of things such as who the map's target audience was in order to create the best possible map.

To make the map itself, I imported the files for Florida's counties, Escambia county itself, Florida's cities, interstate highways, and major rivers, as well as a point file for UWF's main campus.  The map of Florida's counties and Escambia county were used to make the inset map that shows the whole state. 

For the central map, I used Escambia's boundary file along with the other files.  To only show the interstate highways and major rivers within the county I used the clip layers tool to create new files that only show the pertinent features.  To have the map only show the two cities desired, I created a clause where only Pensacola and Ferry Pass were selected using "select by attributes."  This created a new layer with only those two cities.  I used the label feature to label these elements so the viewer would know what they were.

I had the opportunity to choose colors for the map at this point.  I went with fairly traditional coloring based off of establish principles such as having the roads as red and the rivers as blue.  Having an intuitive map helps the viewer easily understand what is going on.  I then added in the necessarily map elements: the title, scale bars, north arrow, legend, cartographer's name, and sources.  The final set was to properly lay out all the elements so that the map was clear to read.

Orientation Lab

The first assignment of the introductory class is intended for us to familiarize ourselves with the basic operations and terminology of ArcGIS Pro.

This week involved mastering the basic tasks of making data folder connections, setting a base map, adding data to a map, and the basics of setting symbology,  The end result was a map with the countries of the world with the cities marked.

2020 UWF GIS

This year I started a graduate certificate program at University of West Florida to learn GIS.  Check back on this blog to see my progress as I learn the software and to see my future projects.