GEOG 328 Definitions

Question 1

Inverse Distance Weighted (IDW)

Answer 1

Inverse distance weighted (IDW) interpolation is an exact method that enforces
that the estimated value of a point is influenced more by nearby known points
than those farther away.

Question 2

Trend Surface Analysis

Answer 2

A global polynomial interpolation that fits a smooth surface defined by a
mathematical function (a polynomial) to the input sample points

Question 3

Kriging

Answer 3

An interpolation technique that uses regionalized variable theory to
incorporate information about the stochastic aspects of spatial variation
when estimating interpolation weights.

Question 4

Semivariance

Answer 4

A measure of the degree of spatial dependence between samples at a specific point.

Question 5

Semivariogram (Hint: 2 types)

Answer 5

The experimental Semivariogram provides a description of how the
data are related (correlated) with distance.

An empirical Semivariogram is a smooth function defined by a model
equals that represents the experimental Semivariogram.

Question 6

Spatial Analysis

Answer 6

A subset of analytic techniques whose results depend on the spatial
frame, or will change if the frame changes, or if objects are repositioned
within it (Goodchild and Longley, 1999).

Question 7

Location

Answer 7

Describes where a “thing” is in space.

Question 8

Attribute

Answer 8

Provides information about the “thing”.

Question 9

Vector Data Model

Answer 9

Uses points, lines, polygons to represent
spatial features or objects with a clear
spatial location and boundary

Question 10

Raster Data Model

Answer 10

Uses a grid to grid cell to represent a

continuous field e.g. elevation, temperature.

Question 11

Spatial Data

Answer 11

Data which are a representation of our behavior,
indicative of an underlying process which governs
the pattern.

Question 12

Spatial Pattern

Answer 12

Spatial pattern = spatial distribution of objects.

Spatial patterns are a realization of a spatial process

e.g. locations of people infected with West Nile virus

Question 13

Spatial Process

Answer 13

Spatial process = a spatial phenomena that results in a spatial pattern

e.g. mosquito infection and transmission.

Question 14

Ecological Fallacy

Answer 14

The belief that relationships observed for groups necessarily hold true for individuals.

e.g. If countries with more fat in the diet have higher rates of breast cancer, then women who eat fatty foods must be more likely to get breast cancer.

Question 15

Model

Answer 15

A model is a simplified representation of a phenomenon or a system

Question 16

Multi-criteria Model

Answer 16

A model of the real world, incorporating spatial data and relationships,
used to aid understanding of spatial form and process

Question 17

Binary Model

Answer 17

A Binary model uses a boolean output to present explicit data which denotes either suitable/unsuitable outputs.


Question 18

Interpolation

Answer 18

The process of estimating (predicting) values at unsampled sites within an area for which there exist some sampled (point) observations.

Question 19

Deterministic Model

Answer 19

Deterministic techniques are based on surrounding measurements (mathematical functions) to calculate the surface. Does not use any probability theory.

e.g. Thiessen polygons, IDW and spline interpolation.

Question 20

Stochastic Model

Answer 20

Stochastic techniques use both mathematical and statistical functions for prediction. They incorporate the concept of randomness: the interpolated surface is conceptualized as one of many that might have been observed, all of which could have produced the known data points

e.g. Polynomial regression and kriging are stochastic interpolation methods.

Question 21

Global Interpolator

Answer 21

A global interpolator derives a surface model using all of the available data to
provide predictions for the whole area of interest by applying a single function
across the entire region.

Question 22

Local Interpolator

Answer 22

A local interpolator calculates predictions from the measured points within neighbourhoods or smaller spatial areas within a larger study area to ensure that interpolated values are determined only by nearby points.

Question 23

Exact Interpolation

Answer 23

Exact interpolation honours the data points upon which the interpolation is based
so that the interpolated surface passes through all points whose values are known.

Question 24

Approximate Interpolation

Answer 24

Approximate interpolation is used when there is uncertainty in the given surface values. In
many data sets there are global trends and local variation that produces
uncertainty (error) in the sample values.

Question 25

Gradual Interpolator

Answer 25

Gradual interpolation produces a surface with gradual changes by applying the
same rules over the entire data source.

Gradual interpolation is appropriate for interpolating data with low local variability.

Question 26

Abrupt Interpolator

Answer 26

Abrupt interpolation can involve the application of different rules at different
points by including ‘barriers’ in the interpolation process.

Question 27

Thiessen Polygon

Answer 27

Thiessen polygon interpolation divides the entire area into polygons with one polygon per observed point and every location within the polygon is closer to that point than any other point.

Question 28

Moving Average

Answer 28

Moving Average interpolation calculates the value at the centre of the neighbourhood based on the average value of all values shown within the window.

Question 29

Semivariogram - Range

Answer 29

The distance at which the curve approaches the process variance is called Range.
• Within the range, closer sites are similar
• Greater than range, data point not useful to interpolation – too far away

Question 30

Semivariogram - Sill

Answer 30

The Sill represents the range at which there is no longer spatial dependence (i.e. constant variance) between data pairs

Question 31

Semivariogram - Nugget

Answer 31

The Nugget represents the short range randomness in a data set, resulting from either microscale processes or measurements errors.

Question 32

Co-Kriging

Answer 32

Kriging which uses information from more than two or more regionalized variables which are correlated.

eg. ‘soil toxicity’ and ‘distance from Mine’ or ‘precipitation’ and ‘elevation’

Question 33

Terrain

Answer 33

Also known as relief, this is the third dimension (elevation) of the land
surface. Also known as the “lie of the land”.

Generally expressed as elevation, slope, and aspect

Question 34

Bathymetry

Answer 34

Underwater Terrain

Question 35

DEM

Answer 35

A regular array of elevation points.

Question 36

DTM

Answer 36

DTM is a bare earth model of elevation.

Question 37

DSM

Answer 37

DSM is an elevation model made up of the DTM + human made elements (buildings, roads, etc.) or natural features (trees, vegetation, etc.) that are on the bare earth.

Question 38

TIN

Answer 38

Triangulated Irregular Network is a vector surface representative of a continuous surface consisting entirely of triangular facets, used mainly as primary elevation modelling.

Question 39

Watershed

Answer 39

A watershed represents a given area where the flow of water is forced to move at the surface as a result of the elevation.

Question 40

Cost Surface

Answer 40

A Cost Surface is essentially the cumulative cost based on the origin point. cost is added as a result of moving an a given direction.