1What are the two primary data models in GIS?
Raster data models and vector data models
2What is a data model in GIS?
A set of rules and/or constructs used to describe and represent aspects of the real world in a computer
3What is the main purpose of a raster data model?
To represent geographic space using a grid of cells or pixels
4What common digital image formats are based on the raster data model?
JPEG, BMP, and TIFF
5What is a raster data model composed of?
Rows and columns of equally sized pixels interconnected to form a planar surface
6What are the basic building blocks of a raster data model?
Pixels or cells
7What geometric shape is most commonly used for raster pixels?
Square
8Why is the raster data model called a grid-based system?
Because it relies on a uniform series of cells arranged in rows and columns
9What does each cell in a raster typically contain?
A single data value representing a characteristic of a spatial phenomenon
10What data types can a raster cell value have?
Integer or floating-point
11What is spatial resolution in a raster data model?
The size of one side of a pixel on the ground
12What does a 10 m spatial resolution mean?
Each pixel represents an area of 10 m by 10 m on the ground
13What happens when a raster uses an overly coarse pixel resolution?
Information is lost
14What happens when a raster uses an overly fine pixel resolution?
File size and computer processing requirements increase significantly
15What determines the appropriate raster pixel resolution?
Map scale and the minimum mapping unit of the other GIS data
16What value is often used as a placeholder when raster data are missing?
-9999
17How is elevation represented in a raster?
Each pixel contains an elevation value, usually in feet or meters
18How can qualitative information be represented in a raster?
By using numerical indices that refer to predetermined categories
19In a land-use/land-cover raster, what could the value 1 represent?
Grassland
20In a land-use/land-cover raster, what could the value 2 represent?
Agricultural land
21In a land-use/land-cover raster, what could the value 3 represent?
Disturbed land
22Where are point and line features assumed to be located within a raster cell?
Toward the center of the cell
23What is the minimum width of a line feature in a raster?
One cell
24What happens if a line feature is less than one cell wide?
It may not be represented and will be assumed to be absent
25What is cell-by-cell raster encoding?
A method that creates records for each cell value by row and column
26What is another name for cell-by-cell raster encoding?
Exhaustive enumeration
27What is run-length raster encoding?
A method that encodes cell values in runs of similarly valued pixels
28When is run-length encoding most useful?
When large groups of neighboring pixels have similar values
29For what type of data is run-length encoding less useful?
Continuous datasets such as elevation or sea-surface temperatures
30What is quad-tree raster encoding?
A method that divides a raster into a hierarchy of quadrants that are subdivided based on similarly valued pixels
31When does quad-tree division stop?
When a quadrant consists entirely of cells with the same value
32What is a leaf node in quad-tree encoding?
A quadrant that cannot be subdivided further
33What is one major advantage of raster data?
The technology required to create raster graphics is inexpensive and widely available
34Why is raster data relatively easy to analyze?
Its simple grid-based structure makes overlay analysis relatively easy
35What is a major disadvantage of raster data concerning file size?
Raster files are typically very large
36Why can raster images look less attractive than vector images?
They become pixelated when enlarged or zoomed
37What can happen to raster data during map reprojection?
Pixel size, shape, and values can change
38Why can different raster resolutions cause problems in spatial analysis?
Combining datasets with very different resolutions can produce nonsensical or uninterpretable results
39What types of spatial analysis can be problematic with raster data?
Some network analyses, directionality analyses, and geocoding
40What are the key characteristics of raster data?
A grid-based system of contiguous cells containing specific attribute information
41What does the spatial resolution of a raster represent?
A measure of the accuracy or detail of the displayed information
42What technologies outside GIS commonly use raster data?
Digital cameras, digital pictures, and LCD monitors
43What should be considered when choosing between raster and vector data?
Which data model is best suited to the data and analytical needs
44What is the vector data model?
A model that represents geographic features using points and their associated X,Y coordinate pairs
45How does vector data differ from raster data?
Vector data does not divide space into discrete grid cells
46What are the three fundamental vector types?
Points, lines, and polygons
47What is a point in vector data?
A zero-dimensional object containing a single coordinate pair
48What types of features can points represent?
Buildings, wells, power poles, sample locations, and other discrete features
49What is a node in vector data?
A topological junction representing a common X,Y coordinate pair between intersecting lines and/or polygons
50What is a vertex?
A bend along a line or polygon feature that is not an intersection of lines or polygons
51What is a line in vector data?
A one-dimensional feature composed of multiple explicitly connected points
52What types of features can lines represent?
Roads, streams, faults, and boundaries
53What property does a line have?
Length
54What are lines connecting two nodes sometimes called?
Chains, edges, segments, or arcs
55What is a polygon in vector data?
A two-dimensional feature created by multiple lines that loop back to form a closed feature
56What properties do polygons have?
Area and perimeter
57What types of features can polygons represent?
City boundaries, geologic formations, lakes, soil associations, and vegetation communities
58What is another name for polygons?
Areas
59What is the spaghetti data model?
A simple vector data structure in which each point, line, or polygon is represented as a string of X,Y coordinate pairs with no inherent structure
60What is a major disadvantage of the spaghetti data model?
It creates redundant data when adjacent polygons share boundaries
61Why does the spaghetti model lack topological information?
Spatial relationships are implied by location rather than explicitly encoded
62What is a major advantage of the spaghetti model?
Its simple structure allows efficient reproduction of maps and graphics
63What is the topological data model?
A vector data model that explicitly includes information about spatial relationships
64What is topology?
A set of rules that models relationships between neighboring points, lines, and polygons and determines how they share geometry
65What are the three basic topological precepts?
Connectivity, area definition, and contiguity
66What is connectivity in topology?
The arc-node relationship describing how arcs connect through nodes
67What is a node in arc-node topology?
An intersection point where two or more arcs meet
68What are the from-node and to-node?
The starting and ending nodes of an arc
69What is a link?
A line segment between a pair of nodes that has its own identification number
70What is area definition?
The principle that arcs surrounding an area define a polygon
71What is polygon-arc topology?
A structure in which arcs are used to construct polygons and each arc is stored only once
72What is the advantage of storing each shared arc only once?
It reduces data storage and prevents adjacent polygon boundaries from overlapping
73What is contiguity?
The relationship in which polygons sharing a boundary are considered adjacent
74What does polygon topology allow the computer to determine?
Which polygons are adjacent and which sides of an arc belong to each polygon
75What is the universe polygon?
The external area located outside the study area
76Why is topology important in GIS?
It allows rapid analysis of spatial relationships and efficient error detection
77What is an open polygon?
A polygon whose arcs do not completely loop back to form a closed feature
78What is an unlabeled polygon?
An area that does not contain any attribute information
79What is a sliver?
A topological error caused when the shared boundary of two polygons does not meet exactly
80What is an undershoot?
A line that does not extend far enough to meet another line
81What is an overshoot?
A line that extends beyond the feature it should connect to
82What is a dangling node?
A node left at the end of a line because of an overshoot or undershoot
83Are dangling nodes always errors?
No, they can occur legitimately at dead-end streets
84Why is topology important for network analysis?
It provides node and arc relationships needed to determine routes and distances
85What spatial analyses benefit from topology?
Network analysis, measurement, adjacency, clustering, and nearest-neighbor analysis
86What are the advantages of vector data compared with raster data?
Greater accuracy and precision, better visual appearance, smaller file sizes, and easier topology-based spatial analysis
87Why can vector data have smaller file sizes than raster data?
Vector data stores coordinate information rather than values for every grid cell
88What is a disadvantage of the vector data structure?
It is more complex than the raster data structure
89Why can vector spatial analysis be complicated?
Differences in accuracy and precision between input datasets can complicate analysis
90What are the key characteristics of vector data?
It uses points, lines, and polygons to represent spatial features
91What does topology describe in vector data?
Connectivity, area definition, and contiguity
92Can vector data be topologically explicit?
Yes, depending on the file's data structure
93What are satellite imagery and aerial photography primarily represented as in GIS?
Raster graphics
94How are satellite imagery and aerial photography commonly used in GIS?
They provide contextual information and are often used for heads-up digitizing
95What is heads-up digitizing?
Converting features visible in an image into vector datasets
96What are satellites used for?
Military and civilian earth observation, communication, navigation, weather, research, and more
97What are active remote sensors?
Sensors that detect reflected responses from objects irradiated by artificially generated energy
98What are examples of active remote sensors?
Radar, laser sensors, and sonar
99How does an active sensor determine distance to a feature?
It measures the time taken for the emitted signal to return
100What are passive remote sensors?
Sensors that detect reflected or emitted electromagnetic radiation from natural sources
101What is the usual natural energy source for passive remote sensing?
The sun
102What is an example of active remote sensing using a camera?
Taking a picture with a flash
103What is an example of passive remote sensing using a camera?
Taking a picture using ambient light without a flash
104What are the four types of satellite imagery resolution?
Spatial, spectral, temporal, and radiometric
105What is spatial resolution in satellite imagery?
The ground area represented by each pixel
106What determines spatial resolution?
The sensor's instantaneous field of view and the height and angle of the imaging platform
107What is spectral resolution?
The ability of a sensor to resolve wavelength intervals or bands within the electromagnetic spectrum
108What types of sensors can resolve many wavelength intervals?
Multispectral and hyperspectral sensors
109What is temporal resolution?
The amount of time between image collection periods
110What determines temporal resolution?
The repeat cycle of the satellite's orbit
111What is true-nadir imaging?
Imaging an area located directly beneath the sensor
112What is off-nadir imaging?
Imaging an area obliquely rather than directly beneath the sensor
113What is radiometric resolution?
The sensitivity of a sensor to variations in brightness
114What does radiometric resolution specifically describe?
The number of grayscale levels that can be recorded by a sensor
115How many unique values can an 8-bit sensor record?
256 values
116What range of values can an 8-bit sensor record?
0–255
117What range of values can an 11-bit sensor record?
0–2,047
118What range of values can a 12-bit sensor record?
0–4,095
119What range of values can a 16-bit sensor record?
0–63,535
120What radiometric resolution does Landsat-7 maintain for its bands?
8-bit
121What is the trade-off between satellite image resolutions?
Improving one type of resolution often requires reducing another
122What type of satellite generally provides high temporal resolution but low spatial resolution?
Geostationary satellites
123What type of satellite generally provides low temporal resolution but high spatial resolution?
Sun-synchronous satellites
124What are geostationary satellites?
Satellites that circle the Earth near the equator once each day
125What are sun-synchronous satellites?
Satellites whose near-polar orbit is synchronized with the Sun's illumination
126What platforms can be used for aerial photography?
Airplanes, helicopters, balloons, rockets, and others
127Can aerial photography use nonvisible electromagnetic bands?
Yes, including ultraviolet, infrared, and near-infrared
128What are two possible viewing angles for aerial photography?
Vertical and oblique
129What is curvature error in aerial photography?
Image distortion caused by the curvature of camera lenses
130What is relief displacement?
An error caused by the three-dimensional nature of terrain features that makes vertical objects appear to lean away from the center of an aerial photograph
131What happens to relief displacement as features become taller?
The error becomes worse
132What are orthophotos?
Vertical photographs that have been geometrically corrected to remove curvature and terrain-induced errors
133What is the most common orthophoto product mentioned in the text?
Digital Ortho Quarter Quadrangle (DOQQ)
134What does DOQQ stand for?
Digital Ortho Quarter Quadrangle
135Who produces DOQQs according to the text?
The U.S. Geological Survey (USGS)
136What spatial resolution do the described DOQQs have?
1 meter
137What radiometric resolution do the described DOQQs have?
8-bit
138What are DOQQs useful for in GIS?
Background display, data editing, and heads-up digitizing
139What are the four key types of resolution in satellite imagery?
Spatial, spectral, temporal, and radiometric
140What are the two main types of remote sensing described in the text?
Active and passive
141What are the two types of aerial photograph viewing angles mentioned?
Vertical and oblique
142What are the main differences between raster and vector data models?
Raster uses grid cells or pixels, while vector uses points, lines, and polygons