Module Review Flashcards

1
Q

What are the 6 core components of a GIS?

A
  1. Network
  2. Software
  3. Data
  4. Procedures
  5. Hardware
  6. People
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2
Q

How can you define GIS?

A

“a system for capturing, storing, checking, integrating, manipulating , analysing and displaying spatial data from the real world for a particular set of purposes.”

“a set of tools for collecting, storing, retrieving at will, transforming, and displaying spatial data from the real world for a particular set of purposes.”

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3
Q

3 types of GIS systems

A

GIS
GIScience
GIStudies

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4
Q

What is spatial data?

A

Data that defines something about a location.
Location = where?
Attribute - what?

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5
Q

What is vector data?

A

A representation of the world using points, lines, and polygons.
Vector models are useful for storing data that has discrete boundaries, such as country borders, land parcels, and streets.

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6
Q

What are attributes?

A

A database or table linked to each vector feature

Can contain only an identifier or a large amount of additional data

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7
Q

What are spatial queries?

A
What is at A?
A can be 
- A single feature 
- Features defined by distance 
- Features within areas
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8
Q

What are attribute (aspatial) queries?

A

Where is B true?
Query attribute data
- Structured query language
- Raster attribute table can be called reclassification
- Create new raster data set from results

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9
Q

What is topology?

A

Looks at geometric characteristics and relationships.

  • connectivity
  • adjacency
  • containment
  • distance
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10
Q

What is raster data?

A

Useful for continuous data

A grid of pixels or cells where each cell has a single numeric value.

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11
Q

What is the resolution of raster data?

A

refers to the area/ size of the cell/pixel

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12
Q

Examples of raster data?

A

Scanned maps
Aerial photography
Surfaces (elevation, house prices)

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13
Q

Raster precision/ resolution

Higher precision =

A

…smaller cell size
More cells required for same coverage
More detail
More processing power

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14
Q

What are data layers?

A

Each layer references a dataset and specifies how that dataset is portrayed using symbols and text labels.
Location and attribute
Layers can be combined visually
Information can be extracted from attributes based on location

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15
Q

What are map projections?

Why?

A

Method to represent the surface of the earth.

Creates maps and enables easier measurement

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16
Q

Different types of map projections?

A

Cylindrical
Azimuthal
Conic

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17
Q

What is a tangent projection?

A

A projection whose surface touches the globe’s without piercing it.
At the point or line of tangency, the projection is free from distortion.

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18
Q

What is a secant projection?

A

Two lines of minimal distortion creating parallel secant lines.

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19
Q

Why is there no distortion in tangent/secant projections?

A

Scale at tangent and secant lines.

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20
Q

What is a transverse mercator?

A

Transverse cylindrical projection.
Distances are only true along the central meridian
Accuracy reasonable within 15 degrees of the meridian
Used for national to large scale mapping.

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21
Q

Spatial referencing

Geographic co-ordinate systems

A

Latitude and longitude

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22
Q

Spatial referencing

Cartesian co-ordinate systems

A

OS National grid

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23
Q

Spatial referencing

Geocodes

A

Postcodes (descriptive/ text location)

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24
Q

Raster symbology

A

Interval and ratio data
Colours/ shading = progression
Reinforced with legend

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25
Two main types of map
Topographic- reference maps with lots of different types of information Thematic- relates to a topic e.g crime
26
Representations of spatial data
3D visualisation Cartograms Schematics
27
Key elements of a map output
``` Reference grid Map body Title North arrow Legend Scale Inset map Map metadata Copyright acknowledgment ```
28
Large scale features
Covers small areas Large amount of detail 1:1000 1:25000
29
Small scale features
Covers large areas Small amount of detail 1:250,000 1:1,000,000
30
Types of scale
Ratio: Units do not matter as long as they are the same Verbal (nominal): 1 cm = 1 km Graphical
31
Types of generalsiation
``` Simplification Enlargement Displacement Combination Selection (elimination) Classification ```
32
Measurement of length
Pythagorean Great circle Manhatten
33
What is the pythagorean measurement of length?
Straight line (euclidean) distance between two points on a flat plane
34
What is the great circle measurement of length?
Gives the shortest distance between two points on a spherical globe given their latitudes and longitudes
35
What is the manhattan measurement of length?
Linked to raster data | The sum of horizontal and vertical components when measuring a diagonal.
36
What is an issue with vector length measurement?
Length of a true curve us almost always longer than length of poly line.
37
What is the raster measurement of area?
Area = no of cells x cells area
38
What is an example of a vector measurement?
Buffers
39
What is an example of a raster measurement?
Euclidean distance | Each cell gives a distance to the closest source cell.
40
What is reclassification?
Creation of new output later based on values in input layer. Input: may be categorical or continuous Output: Generally categorised
41
How to to reclassify something.
Spatial analyst > reclass > reclassify
42
Vector overlay
Comparison of layers which occupy same space Select by locations (select features) Used to create new data (geoprocessing tools)
43
Types of vector overlay
Clip Intersect Union
44
Basic cartographic modelling Simple case
Input layer -> Single operation -> output
45
Basic cartographic modelling Complex case
Multiple input layers -> multiple operations -> output
46
Data conversion | Raster to vector:
Vectorisation
47
Data conversion | Vector to raster:
Rasterisation
48
Data conversion | Change in feature type:
Points to area: Aggregation
49
Why are data storage: data base important?
For storing, organising, analysing and retrieving data
50
Types of data errors
Positional accuracy (precision- probable location e.g +/- 5m) Attribute accuracy Representations of reality
51
Errors in data collection
``` Sampling mistakes (technical difficulties, incorrect operation recording) Sampling bias ```
52
Remote sensing | Shadow =
Cloud distortion
53
Accuracy
The extent to which an estimated data value represents its true value Consists of two components: Precision Unbiasedness
54
Precision
Specificity (e.g number of decimal places or significant features) The dispersion of a measured or predicted value
55
Bias
Any systematic difference between the true value and the measured or predicted value.
56
Three key types of accuracy in GIS
Positional Attribute Topological
57
What is positional accuracy?
Are features in the right place?
58
What is attribute accuracy?
Do features have the correct value (continuous/ categorical)
59
Benefits of GIS | Direct
Savings Increased effectiveness Brand new products
60
Benefits of GIS | Indirect
Improved information sharing Greater understanding Better justification More competitive
61
Costs | Direct
Hardware/software Data Human and administrative costs
62
Costs | Indirect
Increased reliance on computers | Higher skilled workforce required
63
What is ecological fallacy?
Falsely attributing characteristics of a zone to individuals on the basis of their membership to that zone Very common problem in the social sciences Can lead to wrong conclusions about causality
64
Geovisualisation
What3words Traditional maps- limitations Cartograms Other visualisations