3426midterm Flashcards
(111 cards)
1
Q
which type of attribute distinguishes one from another, like names
A
nominal
2
Q
which type of attributes have an order, like small to large
A
ordinal
3
Q
what type of attribute has a 0 point, the difference between values makes sense?
A
interval
4
Q
what type of attribute has ratios between values that make sense
A
ratio
5
Q
what type of attribute describes flow direction, compass direction, or longitude
A
cyclic
6
Q
what represents the geographic world as objects with well defined boundaries in otherwise empty space
A
discrete objects
7
Q
in what type of data structure is detail about variation within cells lost, and instead are given a single value
A
raster
8
Q
in raster format, properties and attributes are applied to the
A
cells
9
Q
what type of data structure has points, lines, and polygons
A
vector
10
Q
what model doesn’t allow spatial analysis
A
spaghetti model
11
Q
what shows relationships using points and nodes
A
topology
12
Q
what type of data has a finite number of variables, each one defined at every possible position
A
continuous
13
Q
small scale has a ___ area
A
large
14
Q
large scale has a ___ area
A
small
15
Q
What types of scale are used?
A
absolute, bar scale, representative fraction
16
Q
high resolution means that each pixel is a ___ area
A
smaller
17
Q
low resolution means that each pixel is a ___ area
A
larger
18
Q
what is a reference or base for other measurements, the center of the Earth from which a coordinate system is projected
A
a Datum
19
Q
what is the means of representing a spherical surface in a flat surface
A
map projection
20
Q
What are the families of map projections
A
cyllindrical, conic, planar
21
Q
Distance (absolute/relative), direction, arrangement, orientation, scale, regular, random, clustered, are all ___
A
geographic patterns
22
Q
what are some different types of topology
A
adjacency, connectivity, containment
23
Q
what is the spread of attributes from one area to another
A
dispersion
24
Q
what are different types of expansion/diffusion
A
contagious expansion, hierarchical expansion, relocation diffusion
25
what is the time distance decay
the presence decreases as the time and distance increases
26
intersection, union, and identity are all forms of
overlay
27
line, point, and polygon are all types of
buffers
28
remotely sensed images, and digital aerial photos are types of
raster primary data
29
GPS points, and field survey are all types of
vector primary data
30
what is data gathered and organized by someone else?
secondary data
31
what are types of open gis?
OpenStreetMap, CoCoRaHS, Nature's notebook
32
what are different types of scanning
flatbed, drum, line
33
what is the first step of digitizing
map preparation, assign unique identifiers, mark tic locations
34
what is the second step of digitizing
begin digitizing, registration and transformation
35
what is the third step of digitizing
ensure the continuity of features across map sheet boundaries
36
one of a set of ordered xy coordinate pairs that defines the shape of a line or polygon feature
vertex, euclidean geometry
37
point representing the beginning or ending point of an edge , topologically linked to all the edges that meet there
node
38
what analysis involves selecting, counting, and selective statistics
simple spatial analysis
39
what analysis often must link to other software and/or significant programming by user
advanced spatial analysis
40
what determines attributes from data (not stored in the data)
higher level objects
41
centroids, point patterns, landscape metrics are all types of
higher lever objects
42
What is essentially the center of gravity for point distributions, weighted point distributions
centroids
43
what are the three major types of networks
straight line, branching, circuit
44
what is used to measure concentration
hoover index
45
what does a negative hoover index mean
concentrated
46
what does a 0 hoover index mean
uniform
47
what does an above 0 hoover index mean
deconcentrated
48
centroids, central features, standard distance, directional distribution, point density (kernal density) are all types of
higher level point objects
49
What do these nearest neighbor values mean
R= 1
R=0
R>1
random
"perfectly" clustered
uniform/dispersed
50
what is the first step of nearest neighbor analysis
find the nearest neighbors
51
what is the second step of NN analysis
find the distances
52
What is the third step of NN analysis
find the average NN distance
53
what is the fourth step of NN analysis
find R =NND(A)/NND(R)
54
What function shows how similar
G function
55
what is the exhaustive regular or irregular partitioning of space
tessellation
56
What is the most common tessellations
squares, from remote sensing: pixel, raster
57
what is the map of the direction the slope is facing
aspect
58
what is the statistical measure of how proximate objects are related
autocorrelation
59
what are the two types of autocorrelation
spatial and serial
60
what is the creation of a surface from point data and their attributes
surface interpolation
61
what are types of surface interpolation
thiessen polygons, linear interpolation (trend surface analysis), weighted distance, kriging
62
what kind of interpolation uses all known sample points to estimate a value at an unsampled location
global
63
what kind of interpolation uses neighborhood of sample points to estimate
local
64
what surface takes into account the sun azimuth abd sun zenith
hillshape
65
What surface has a DEM start, then calculates the flow of accumulation
watershed analysis
66
what are some types of statistical surfaces
DEM, Isolines, TINs, other rasters
67
what is a set of polygons that represent the closest area to a point
veroni diagram
68
what produces edge effects
extrapolation
69
what tries to create a nonlinear surface that fits through every point in a dataset
spline
70
what is the z value field in a spline
numerical attribute of points
71
using a regularized spline, a higher weight means
smoother surface (W= 0-5)
72
using a tension spline, a higher weight means
coarser surface (W>0)
73
what takes a weighted local average to interpolate the points
inverse distance weighting
74
what tells us how much near things are related, a quantitative number
the power in
| Weight= 1/distance^power
75
what measures how different point pairs are
semivariance cloud
76
if points are similar they have a ___ semivariance
low
77
what tells us that beyond this distance, the points do not affect the points nearer. (the distance the model first flattens out)
the range in a semivariance cloud
78
The value that the semivariogram model attains at the range
the sill
79
what is the partial sill
the sill minus the nugget
80
what are the outputs of a variogram
prediction map. standard error, quantile map, probability map
81
what type of kriging does not have a trend
ordinary kriging
82
what type of kriging has a trend without known model parameters
universal kriging
83
what type of kriging has a trend with known model parameters
simple kriging
84
what type of kriging has a binary predictio surface
indicator kriging
85
what type of kriging has multiple inputs
cokriging
86
what type of interpolation often results in a more realistic interpolation but estimating missing data values is more complex
nonlinear interpolation
87
which analysis requires which operations and in what order to be thought out in advance
multifaceted analysis
88
how many commands does ArcGIS have
7000
89
multifaceted analysis is not linear, but
iterative
90
what aids the modeling process bu diminishing the complexity of the task, permits planning in an organized manner, provides documentation
flowcharting
91
what type of model illustrates existing condition and isolates specific factors to clarify what is going on
descriptive model
92
what type of model asserts a causal relationship
predictive model
93
what type of model employs a known causal relationship to engineer a desired result in a specific instance
prescriptive model
94
what are two types of model perspective
objective (streamflow modeling)
| subjective (preserving farmland while allowing urban growth
95
What are the four major steps in a typical GIS project
1. determine objectives and design the model/design the database
2. build the database
3. perform the analysis
4. present the results
96
what is used to group features for separate mean center computations
the case field
97
what is constructed from the average x and y values for the input features
the mean center
98
in mean center computation, what is any numeric field in the input feature class
the dimension field
99
what creates standard deviational ellipses to summarize the spatial characteristics of geographic features
directional distribution
100
in directional distrbution and standard distance, the case field is used to
group features prior to analysis
101
what measures the degree to which features are concentrated or dispersed around the geometric mean center
standard distance
102
what interpolates a raster surface from points using a two dimensional minimum curvature technique
spline
103
what spatial analyst tool results in a smooth surface that passes exactly through the input points
spline
104
T/F IDW can extrapolate values outside of the known range
false
105
what is the measure of how different points are
semivariance
106
what does 0 mean on a variogram?
there is no difference
107
what is the lag distance
how far apart the two points are
108
what is the space between 0 and the actual semivariance of a pair with lag distance 0
the nugget
109
what value determines how much of the population would have to be redistributed
hoover index
110
what is the measure of whether there is a directional difference in the variogram
anisotropy
111
what projection is best for areas of wide ranges of latitude but poor for areas with wide ranges of longitude
UTM
