Lesson 12

Question 1

• The checking if the location of the points tends to cluster together, whether they’re more uniformly distributed or arranged randomly
• It provides fundamental clues about the underlying spatial processes and relationships

Answer 1

Point Pattern Analysis

Question 2

If the point pattern is identified as nonrandom, it can be further classified as more clustered than random or more
dispersed than random. (T or F)

Answer 2

True real omsim

Question 3

Results from a contagion process where one location attracts a number of points. Points are close to one another and there are large patches that does not contain any points.

Answer 3

Clustered Point Pattern

Question 4

Commonly results from some form of competition in space, where points repel one another. The dispersed patterns are seemingly regular over space; hence, it is called uniform.

Answer 4

Uniform Point Pattern / Dispersed Point Pattern

Question 5

Happens when points repel one another

Answer 5

Negative Autocorrelation

Question 6

Generated by an independent random process, wherein every location (or small area) of a study area has an equal probability of receiving an event or point, and for which the location of an event is independent of the location of all other events. In other words, the underlying generating process has no spatial logic.

Answer 6

Random Point Pattern

Question 7

Often engaged in examining departures from complete spatial randomness.

Answer 7

Point Pattern Analysis

Question 8

The distribution of points throughout a given study region follows a homogenous Poisson process

Answer 8

Complete Spatial Randomness (CSR)

Question 9

Properties of CSR

Answer 9

• Each event has an equal probability of occurring at any position in the study region
• The position of any event is independent of the position of any other.

Question 10

CSR Challenge: When examining absolute location, this is the variation of the observations’ density across a study area (no equal probability).

Answer 10

First-order property of pattern

Question 11

CSR Challenge: When exploring interactions between locations, this is the observations’ influence on one another (no-independence).

Answer 11

Second-order property of pattern

Question 12

Point Pattern Technique: Characterize the pattern in terms of its distribution vis-a-vis the study area (takes the first-order property).

Answer 12

Density Methods

Question 13

Point Pattern Technique: The interest lies in how the points are distributed relative to one another (takes the second-order property)

Answer 13

Distance-based Methods

Question 14

Density Method that measures a pattern’s overall density. Ratio of observed number of points, 𝑛 to the study region’s surface area, 𝑎

Answer 14

Global density

Question 15

Density Method: A point pattern’s density measured at different locations within the study area

Answer 15

Local density

Question 16

This is an example of a local density method that focuses on changes in the density of points across a study region i.e. the frequency of points occurring in various parts of the area. It is performed by overlaying a regular grid on the region of interest and then counting the number of points found in each quadrat (cell) of the grid.

Answer 16

Quadrat Analysis

Question 17

Limitations of the Quadrat Analysis

Answer 17

• It is a measure of dispersion rather than pattern (based primarily on the density of points)
• Results in a single measure for the entire distribution, variations within the region are not recognized. Thus, markedly different point patterns can give rise to identical frequency distributions of the points per quadrat
• Sensitive to grid size—changing the size of the quadrats may also affect the significance

Question 18

This method provides an alternative to quadrat analysis. It focuses on the distances between points rather than the density of points in an area. However, this statistic cannot be used to compare point pattern maps.

Answer 18

Nearest Neighbor Analysis

Question 19

A way to understand the geographical pattern or spatial order of phenomena across space.

Answer 19

Point Pattern Analysis

Question 20

Three Types of Point Patterns

Answer 20

Clustered, Dispersed, and Random.

Question 21

In theory, the distribution of geographical points follows the core principles of ___?

Answer 21

Complete Spatial Randomness (CSR).

Question 22

An example of a local density-based method

Answer 22

Quadrat Analysis

Question 23

An example of a distance-based method

Answer 23

Nearest Neighbor Analysis

Question 24

Quadrat Method Results Interpretation:
VMR > 1 to Infinity indicates ?

Answer 24

Indicates a clustered point pattern (a good
deal of variation in the number of points per cell)

Question 25

Quadrat Method Results Interpretation:
VMR = 1 indicates ?

Answer 25

Indicates a random point pattern

Question 26

Quadrat Method Results Interpretation:
VMR < 1 to 0 indicates ?

Answer 26

Indicates a uniform or dispersed point pattern (little variation of points from cell to cell)

Question 27

Nearest Neighbor Analysis Results Interpretation:
R Values close to 0 indicates a ?

Answer 27

Clustered point pattern

Question 28

Nearest Neighbor Analysis Results Interpretation:
R Values close to 2.15 indicates a ?

Answer 28

Dispersed point pattern

Question 29

Nearest Neighbor Analysis Results Interpretation:
R = 1 indicates ?

Answer 29

Indicates consistency with a random
pattern