GIS Final Project

http://students.uwf.edu/pmw5/FinalProjectGIS/GISFinalPresentation_PW.pptx

http://students.uwf.edu/pmw5/FinalProjectGIS/Commentary_PW.pdf  

   These two links connect to my I Drive and contain the PowerPoint and the commentary to my final project. The final project required us to make a PowerPoint presentation and commentary around the analysis of 4 map objectives. The project had us analyze the feasibility of the Bobwhite-Manatee transmission line placement in Manatee and Sarasota Counties, Florida, based on 4 criteria: It impacted few environmentally sensitive lands, it impacted few homes, it impacted few schools and daycares, its length was not too long.

Final Project

Introduction

For my final project, I chose the U.S. Department of Education scenario in which a map of the 2014 SAT scores and participation rate for each state would be created for the purpose of submitting to the Washington Post alongside an article on high school seniors and college entrance scores. I chose this option because I was curious about what regions of the U.S. were more likely to take the SAT, considering I grew up in the Central U.S. and the ACT was encouraged more than the SAT. My objectives going into the project were to: create my own tabular data, convert that data into something visibly tangible (i.e. shapefile), determine how to display each dataset thematically, choose an appropriate projection, determine how to classify the datasets, create appropriate labels, utilize inset maps, and determine how to present the most of my data without cluttering my map.

Thematic Methods

For my thematic map I chose a choropleth theme for SAT scores and graduated symbols for participation rates. I got a lot of my inspiration by looking at other standardized test score maps online, while searching for a common theme among them. The majority of them had in common the usage of graduated colors. Furthermore, the majority used a monochromatic color ramp, contrasting light and darker hues of the same color. I followed the same path and chose a blue light to dark color ramp. I chose graduated symbols because it allowed me to produce a range of symbol sizes and values close to the values on the sheet of data we were provided.

Data Classification Methods

For the SAT score data, I used graduated colors with a quantile classification of 5 classes. I used this method because most of the data was not of identical values and could be easily rank-ordered. I chose 5 classes so the viewer could easily observe the map in 20 percent fractions. I was conflicted on whether or not to include the SAT score ranges, as the College Board “strongly discourages the ranking of scores between states”. Every map I came across for my inspiration only indicated ‘high’ and ‘low’ as score ranges. However, this map was created in mind with the intention to display information, and with the quantile method I could leave out the numbers and indicate ‘high’ and ‘low’ in case concerns of state comparisons were holding back publication.  I used graduated symbols for the participation rates because it gave me more control over how to group the percentages through symbol size.

Design

 I wanted to achieve contrast, yet the map be easy on the eyes to decipher and follow. I also wanted it to be simplistic and easy to understand, considering it would reach a wide audience. I stuck with a theme of varying shades of blue with white borderlines, and labels colored appropriately to the hue. Label sizes vary with state size. ArcMap was used to produce the bare bones and data of the map, I carried out the rest of the design, typography, and neat lines in AI, where I would have better font, border, and artistic capabilities.

Google Earth

   In this lab, a previous dot map assignment was converted into a KML file in ArcMap and then used to create a Google Earth tour.

   The ArcMap conversion tools Layer to KML and Map to KML were used to create KML files for the recorded tour. One layer shows the dot map density of population for South Florida while the other shows surface water types of South Florida.  An additional unseen layer is added to provide the attribute table information. The dot map and its data were created from a previous assignment. 

Georeferencing, Editing, & ArcScene

   In this lab, the objectives were to: georeference data using the Control Points tool in order to distribute control points, georeference an unknown raster image of the UWF campus to known vector data (buildings and roads of the campus), interpret Residual and Root Mean Square errors, digitize a new building and road feature, practice polynomial transformations, create a hyperlink in ArcGIS to data stored on a personal drive, create Multiple Ring Buffers, customize an ArcMap toolbar, and overlay vectors and rasters to a 3D environment. In this lab, 2 maps were created.

Georeference of the UWF Campus

   This map shows the UWF campus georeferenced on the right, and an eagle nest buffer zone on the left. For UWF map, control points were used to align the raster with the vector points in order to assign a spatial reference. Two new features were also added through the Editing toolbar. The eagle nest map utilized the MBR tool in order to create a buffer of 330 feet and 660 feet around the nesting site. The buffer represents the distance the nest site needs in order to be undisturbed by development.

3D Map of the UWF Campus

   For this map, ArcScene was used to overlay the rasters and vectors to a DEM. Vertical Exaggeration was added to enhance the height of the buildings. The 3D map was exported as a 2D image and imported into ArcMap to add the final map elements. The POV is of the two new features created in the lab.

3D Mapping

   In this lab, the learning objectives were to: perform techniques to visualize raster and feature data in 3D, convert 2D feature to 3D using elevation values derived from lidar data, utilize the 3D Analyst Extension in ArcMap, demonstrate proficiency in ArcScene, and export data to a KMZ file to be viwewed in Google Earth. Below is a screenshot of one of the 3D labs I completed in ESRI's virtual campus course training.

   In this part of the ESRI training, vertical exaggeration was implemented through ArcScene. It is used to give a more dynamic appearance to terrain that has small changes in elevation. Here, the terrain in Minnesota is enhanced. The other ESRI training labs demonstrated how to: set base heights for raster and feature data, set illumination and background color, and extrude features based on height or other attributes. 

   3D mapping is beneficial in many ways. It is as easy to share as 2D data and has useful applications for simulations. It can present vertical information as cant be seen in 2D and has intuitive symbology. It is easier to recognize terrain and location because of its human-centric aspects. However, it is easy to get disoriented while navigating. Map content can be hidden underneath surfaces or in building interiors. There is also the issue of performance. Since 3D mapping entails a lot of data, performance issues with computer hardware can arise. Overall, 3D mapping is a unique and immersive way to communicate data and information.