SOC 4650 & SOC 5650 - Lecture 05

Slides for Lecture 05 of the Saint Louis University Course Introduction to GIS. These slides introduce basic cartographic practices using R and ArcGIS.

Transcript

1. Update the stlData package from GitHub:
 devtools::install_github(“chris-prener/stlData”) Install the measurements, RColorBrewer, and viridis packages from CRAN WELCOME! GETTING STARTED Check out the stlData package’s README for how the package has changed: https://github.com/chris-prener/stlData
2. CARTOGRAPHIC DESIGN INTRO TO GISC CHRISTOPHER PRENER, PH.D. SPRING, 2018 WEEK 06 LECTURE 05
3. AGENDA INTRO TO GISC / WEEK 06 / LECTURE 05 1. Front Matter 2. GISc & Public Policy 3. Types of Maps 4. Cartographic Design 5. Working with Color 6. Design in R 7. Design in ArcGIS 8. Back Matter
4. 1 FRONT 
 MATTER
5. PS-03, Lab-04, and LP-06 are due next Monday. 1. FRONT MATTER ANNOUNCEMENTS Make sure you keep the final project at the forefront of your attention! Keep checking Sack and GitHub Issues!
6. ▸ .data is a data frame, a tibble, or a simple features object ▸ varlist is an optional list of variables to look for duplicate observations in ▸ .keep_all = TRUE will retain all variables if a varlist is supplied; if FALSE (the default), only the variables in the varlist will be retained Available in dplyr
 Download via CRAN 1. FRONT MATTER DEALING WITH DUPLICATES Parameters: distinct(.data, varlist, .keep_all = TRUE) f(x)
7. ▸ .data is a data frame, a tibble, or a simple features object ▸ varlist is an optional list of variables to look for duplicate observations in ▸ .keep_all = TRUE will retain all variables if a varlist is supplied; if FALSE (the default), only the variables in the varlist will be retained 1. FRONT MATTER DEALING WITH DUPLICATES Parameters: distinct(.data, varlist, .keep_all = TRUE) f(x)
8. DEALING WITH DUPLICATES 1. FRONT MATTER distinct(.data, varlist, .keep_all = TRUE) Using the stl_tbl_water data from stlData: > waterUnique <- distinct(stl_tbl_water) The resulting data frame or tibble will contain one observation for every unique observation in the original data. f(x)
9. DEALING WITH DUPLICATES > library(dplyr) > library(stlData) > nrow(stl_tbl_water) [1] 179
 > waterUnique <- distinct(stl_tbl_water) > nrow(waterUnique) [1] 154 1. FRONT MATTER
10. DEALING WITH DUPLICATES > library(dplyr) > library(stlData) > nrow(stl_tbl_water) [1] 179
 > waterUnique <- distinct(stl_tbl_water, WATER_BODY, POLLUTANT, 
 .keep_all = TRUE)
 > nrow(waterUnique) [1] 37 1. FRONT MATTER
11. GISC & PUBLIC POLICY 2
12. TYPES OF MAPS 3
13. 3. TYPES OF MAPS REFERENCE MAPS SLU North Campus SLU Medical Campus Shaw St. Louis Missouri Botanical Garden Shaw Market Flora Place Mullanphy Elementary
14. 0 1-4 5-8 9-12 13-17 p < .99 p < .95 p < .90 no sig. p < .90 p < .95 p < .99 hot spot cold spot Hotspot Analysis (Inferential Map) Choropleth Map (Thematic Map) MAPPING MURDERS IN ST. LOUIS, ’08-‘15
15. 0 1-4 5-8 9-12 13-17 Choropleth Map of Count Data MAPPING MURDERS IN ST. LOUIS, ’08-‘15 Normalized by Area 0.00 - 
 0.0000035 0.0000115 -
 0.0000237 0.0000035 -
 0.0000115 0.0000237 -
 0.0000398 0.0000398 - 
 0.0000572
16. 0 1-4 5-8 9-12 13-17 Choropleth Map of Count Data MAPPING MURDERS IN ST. LOUIS, ’08-‘15 Normalized by Square Miles 0-9.28 9.28-30.00 30.00-57.14 57.14-94.12 94.12-142.86
17. 0 1-4 5-8 9-12 13-17 Choropleth Map of Count Data MAPPING MURDERS IN ST. LOUIS, ’08-‘15 Graduated Symbols 0-1 2-4 5-8 9-12 12-17
18. 0 1-4 5-8 9-12 13-17 Choropleth Map of Count Data MAPPING MURDERS IN ST. LOUIS, ’08-‘15 Dot Density 0.656 
 murders =
19. QUALITATIVE MAP Missouri
 Botanical
 Garden Tower Grove Park Zoning Codes by Parcel
 St. Louis, MO
20. CARTOGRAPHIC DESIGN 4
21. VISUAL CONTRAST Missouri
 Botanical
 Garden Tower Grove Park Zoning Codes by Parcel
 St. Louis, MO
22. VISUAL CONTRAST Missouri
 Botanical
 Garden Tower Grove Park Zoning Codes by Parcel
 St. Louis, MO
23. VISUAL CONTRAST Missouri
 Botanical
 Garden Tower Grove Park Zoning Codes by Parcel
 St. Louis, MO
24. VISUAL CONTRAST Missouri
 Botanical
 Garden Tower Grove Park Zoning Codes by Parcel
 St. Louis, MO
25. VISUAL CONTRAST Percentage of Population Between
 18-64 Years Old by County, 2010
26. VISUAL CONTRAST Percentage of Population Between
 18-64 Years Old by County, 2010
27. ▸ Assign bright colors (red, orange, yellow, green, blue) to important graphic elements (features) ▸ Important features are known as “figure” ▸ Assign drab colors to the graphic elements that provide orientation or context ▸ Contextual features known as “ground” 4. CARTOGRAPHIC DESIGN VISUAL CONTRAST All features in figure Circles in figure, squares and lines in ground
28. GRAPHIC HIERARCHY Murders in Walnut Park East, 2008-2015
 St. Louis, MO
29. GRAPHIC HIERARCHY Murders in Walnut Park East, 2008-2015
 St. Louis, MO
30. VISUAL CONTRAST
31. VISUAL CONTRAST