Do I know you? pt.2

Question 1

Kernel density question

Answer 1

do you want to categorically summarize or analyze point density?

Question 1

Manhattan/nearest neighbor distance question

Answer 1

do you want to compare the overall clustering or dispersion of points?

Question 2

coefficient of localization

Question 3

geographic center

Question 4

k-plot

Question 5

location quotient

Question 6

mean center

Answer 6

(mean of x, mean of y)

Question 7

what is the purpose of a location quotient?

Answer 7

assesses concentration of an industry in a specific area compared to a larger reference area

Question 8

median center

Answer 8

minimizes the euclidean distance to any point

Question 9

quadrat analysis

Answer 9

1. divide area into cells
2. count features in each cell
3. average |average features - observed| for each cell
4. average / mean of points

Question 10

Ripley’s k function

Answer 10

compares the probability of detecting a difference in clustering compared to a specific probability threshold (expected line)

Question 11

standard distance

Answer 11

standard deviation applied to point data

measures dispersion of points and how far they are from the mean center