PLAN 318Spatial Analysis
- Faculty
- Environment
- Offered
- Spring
- Credit
- 0.5
- Last listed
- 1993–94
No longer offered. It’s in Waterloo’s scanned calendars from 1971–72 to 1993–94; the 1995–96 to 2023–24 calendars are on ucalendar.
Advanced quantitative analysis and sampling in a spatial context. A selection of techniques from gravity models, linear programming, nearest neighbour analysis, Markov chain analysis, graph theory, simulations, and trend surface analysis.. Students may receive credit for only one of PLAN 318 and GEOG 318
As printed in the 1985–86 to 1993–94 calendars, read by OCR; the scanned page is the original.
Requirements, as last listed
Prereq: ES 278
Cross-listed as GEOG 318
Check it elsewhere
In the scanned calendars
How it read in each calendar from 1971–72 to 1993–94, newest first. The text is OCR of the scanned pages; years whose wording matches are shown once, from the clearest scan. Each year links to its page on uwloo and to that page of the scanned PDF.
1985–86 to 1993–94 9 calendars
Advanced quantitative analysis and sampling in a spatial context. A selection of techniques from gravity models, linear programming, nearest neighbour analysis, Markov chain analysis, graph theory, simulations, and trend surface analysis..
Students may receive credit for only one of PLAN 318 and GEOG 318
Prereq: ES 278
Cross-listed as GEOG 318
Offered Spring · 3 class hours a week · 0.5 credit
- 1985–86 PDF p. 446
- 1986–87* PDF p. 418
- 1987–88 PDF p. 431
- 1988–89 PDF p. 429
- 1989–90 PDF p. 452
- 1990–91 PDF p. 429
- 1991–92* PDF p. 439
- 1992–93* PDF p. 431
- 1993–94* PDF p. 434
* Listed that year without a description, or as not offered.
1971–72 to 1984–85 13 calendars
Advanced quantitative analysis of spatial patterns and interactions. Focus on a selection of techniques from gravity models, linear programming, nearest neighbour analysis, Markov chain analysis, graph theory, simulation and trend surface analysis. Cross-listed as Geog 318.
Prereq: Env St 271, or consent of instructor
Offered Winter · 3 class hours a week · 0.5 credit