Spatial data analysis Flashcards
analysis of massive data sets in search for _, _ and _
patterns, anomalies, trends
the centroid is the 2D equivalent of the _, for a set of points, the centroid is found by taking the _ _ of the x and y coordinates
mean
weighted average
what is dispersion?
a measure of the spread of points around a center (range, average deviation, variance/ stand-dev)
patters can be identified as _, _, or _
clustered, dispersed, random
how to identify spatial patterns in the data?
- looking at physical location/ geometric patterns of features
- looking at geographic patterns in attribute data of features
Tobler’s 1st law of geography “everything is related to everything else, but _ things are more related than _ things”
near
distant
spatial autocorrelation is the correlation of a variable with _ through space, and is found by comparing values of a sample with values of their _
itself
neighbors
if there is any systematic pattern in the spatial distribution of a variable, it is said to be _ _
spatially autocorrelated
T or F, positive spatial autocorrelation, all similar values are located far apart.
F, are located close together
T of F, in negative autocorrelation, dissimilar values appear in close association
T
random patterns exhibit no _ _
spatial autocorrelation
What are the 2 goals of spatial autocorrelation?
- measure strength of spatial autocorrelation in a map
- test the assumption of independence or randomness
What are the 4 indices for measuring spatial dependence? and what are they suppose to do?
- Moran’s I
- Geary’s C
- Ripley’s K
- Join count analysis
measure level of interdependence between variable, and the nature and strength of that interdependence
spatial models attempt to represent _ over the earth’s surface, and manipulate _ _ in multiple stages.
variation
geographic information
What are the 2 benefits of spatial modelling?
- allows experiemtns to be conducted on simulated systems
- allow alternative scenarios to be evaluated
