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PLAN 281 Final > Lecture 7 - Raster Data > Flashcards

Lecture 7 - Raster Data Flashcards

1
Q

What is a raster data model?

A

Divides geographic area into regular grid of cells in specific sequence (identified by row and column)

  • each cell contains a single attribute value
  • space-filling: every location corresponds to a cell in the raster (regular tessellation that can be conceptualized as a matrix-like series of cells)
  • large file
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2
Q

How are feature coordinates expressed in raster?

A

They are implict

  • store grid origin (cell in upper left corner)
  • store grid resolution: minimum linear dimension of smallest unit of geographic space sampled
  • find coordinates indirectly
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3
Q

How are attributes expressed in raster?

A

They are explicit

  • often only a single attribute assigned to a cell
  • otherwise, key identifier in each cell links to related database files containing multiple attributes for each grid cell
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4
Q

How do you create a raster file?

A

Although this is rarely done, here are the conceptual steps:

  • choose grid resolution (choose raster cell size 1/2 length of smallest feature on map)
  • set data type (integer, real)
  • overlay grid over study area
  • assign attribute code to each grid cell
  • repeat process for each map layer
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5
Q

What are raster input methods?

A
  • manual raster coding
  • raster scanning
  • existing digital raster data
  • RS imagery
  • vector to raster conversion
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6
Q

What is the manual raster coding input method?

A

Uses spreadsheet, text editor, or digitizer (not popular)

  • overlay transparent grid on existing map
  • record attribute for each cell (decision rules for mixed cells)
  • some digitizer software allows coding of attributes from digitizer puck
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7
Q

What is raster scanning input method?

A

Scans maps or aerial photos

  • several scanner types: drum scanners for large docs and desktop for small docs
  • problems: resampling, editing, raster to vector conversion
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8
Q

What is the existing digital raster data input method?

A
  • elevation data commonly available in raster form (govt agencies)
  • much raster data already in digital form as images
  • resampling likely needed so pixels in images coincide with cells in other data layers
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9
Q

What is the remote sensing data input method?

A
  • airborne imagery: air photos

- satellite imagery: landsat, radarsat

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10
Q

What is the vector to raster conversion input method?

A
  1. coded polygons
  2. grid overlay with appropriate cell sizes
  3. Each cell is assigned the attribute code of the polygon which it belongs to
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11
Q

How would you convert back to vector from raster?

A
  1. each raster is assigned attribute value
  2. boundaries set up b/w different attribute classes
  3. polygon is created by storing x and y coordinates for the points adjacent to boundaries
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12
Q

What conversion errors can occur?

A
  • polygons turn blocky if converted back and forth

- may depict incorrect info

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13
Q

What does the type of cell value being used depend on?

A
  • depends on feature being coded and the GIS used
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14
Q

What kind of data is grid-cell representation often used for?

A
  • categorical data (nominal/ordinal scale)

- quantitative data (interval/ratio scale)

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15
Q

What can raster cell data be coded as?

A
  • whole numbers (integers)
  • real values (decimal)
  • alphabetic values (text)
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16
Q

What are the different cell measurement values?

A
  • nominal
  • ordinal
  • interval
  • ratio
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17
Q

Explain nominal cell measurement values

A
  • categories with no order
  • identifiers with no relation to a fixed point or linear scale
  • legend or linked table provides meaning
  • ex. postal codes, soil types
  • ex 2. 0 = no data, 1 = residential, 2 = commercial, etc.
18
Q

Explain ordinal cell measurement values

A
  • lists of discrete classes with inherent order, but without magnitude or relative proportions
  • cell value has meaning
  • ex. primary, secondary, undergrad, graduate
19
Q

Explain interval cell measurement values

A
  • classes not only with natural sequence, but also with meanings attached to distance b/w sequential values
  • cell values have meaning
  • ex. time of day, temperatures
20
Q

Explain ratio cell measurement values

A
  • same characteristics as interval variables, but have a natural zero as a starting point (can’t be negative)
  • cell values have meaning
  • ex. age, distance, income
21
Q

What is spatial resolution?

A

The area within a grid cell (cell size) defining how much and area the pixel covers

  • smaller the cell, greater resolution and accuracy is
  • always trade-off b/w resolution and cost of storage and processing
22
Q

How do coded grid cells work?

A
  • a line number and column number define cell’s position in raster data
  • data stored in table giving number and attribute value of each cell
23
Q

What are the methods for encoding cells?

A
  1. presence/absence
  2. centroid of cell
  3. dominant type
  4. percent occurence
24
Q

Explain the presence/absence encoding method

A
  • single feature like a well (point) or river (line) is identified as occurring in a cell, no matter how much space it occupies
  • for polygons, the polygon which covers highest proportion of cell is recorded
25
Q

Explain the centroid-of-cell encoding method

A
  • presence of entity is recorded only if portion of it occurs directly at central point of each cell
  • only good for areal (manmade areas) data
  • better for continuously variable quantities, like elevation
  • constraining, so not typically used
26
Q

Explain the dominant type encoding method

A
  • encodes presence of entity if it occupies more than 50% of cell
  • most used method for polygons
27
Q

Explain the percent occurrence encoding method

A
  • if 3 types land use occur in a cell, then each type would be represented as a percentage of cell it occupies
  • only good for areal data
  • can only show percentage for one variable, so how do we know what the other percentages are?
28
Q

Describe raster map layers

A
  • layer comprised of one set of cells and associated values (multiple items of info require multiple layers)
  • raster data can represent a multiplicity of things (visual images, discrete value, continuous value, null values)
  • ex. elevation, counties, roads all would be 3 layers in raster GIS
29
Q

What are the data organization methods and why do we want to organize data?

A

Useful to organize a raster into a 1D data stream for computer file storage and processing.

  1. band interleaved by line (BIL)
  2. band interleaved by pixel (BIP)
  3. band sequential (BSQ)
    - can convert b/w them all
30
Q

Explain the band interleaved by line (BIL) data organization method

A
  • rows follow each other for each characteristic
31
Q

Explain the band interleaved by pixel (BIP) data organization method

A
  • all values for a pixel grouped together
  • good if focus on multiple area characteristics
  • bad if you want to remove or add a layer
32
Q

Explain the band sequential (BSQ) data organization method

A
  • stores each characteristic in separate file (ex. elevation file, temp file, etc.)
  • good for compression and if focus is on one characteristic
  • bad if focusing on one area
33
Q

What is the main issue with raster data storage?

A
  • databases consist of many separate grid layers, thereby compounding the file size issue (large storage requirements)
34
Q

What are the common methods of raster data storage?

A
  1. run length encoding
  2. chain encoding
  3. block encoding
  4. quadtrees
35
Q

Explain run length encoding

A
  • code sequence of cells with same attribute value
  • save data storage space by counting runs of equal values in cells and storing counts
  • limited b/c file is read left to right, one row at a time
  • does not work for column redundancy
  • basically useless if there is no redundancy at all
  • ex. XXXXWWRRRX turns into 4X 2W 3R 1X
36
Q

Explain chain encoding

A
  • similar to run length, but scans rows and columns to define 2D regions with same cell values
  • defines region boundary by giving starting point (origin) and cardinal direction to follow as we progress around boundary
  • steps: assign number 1-4 to cardinal directions; assign how many grids to move in each direction; assign grid cel value for entire area
37
Q

Explain block encoding

A
  • 2D run length encoding where areas of common cell values are represented with a single value
  • square blocks used to tile the area to be represented (array - series of square blocks of largest size possible)
  • store origin (centre or bottom left) and radius of each square
38
Q

Explain quadtrees

A
  • recursive subdivision of raster cells into quadrants with the same cell value until a square is homogeneous
  • uses variable cell resolution to reduce data storage requirements
  • hierarchical tree where each level has four-way branching
  • efficient for relatively homogeneous areas (highly dependent on embedding of spatial objects in image space)
39
Q

What are the disadvantages of raster data structure?

A
  • reduced spatial accuracy of discrete objects (decreases reliability of area and distance measures)
  • need for large storage capacity
  • highly complex analyses can be slow
  • some spatial relationships (ex. contiguity and connectivity) may be altered or lost (linear features may be discontinuous, blocky, or merged with others; some features may not be represented)
40
Q

What are the advantages of raster data structure?

A
  • abundant data sources (RS, aerial photos, scanning)
  • easy to conceptualize as a method of representing space
  • raster programs (algorithms) often computationally simpler and faster than vector
  • sampling is done uniformly across space
  • better for modelling continuous features than vector
  • better for analyses that involve spread, flow, or diffusion processes (ex. surface modelling, overlay)

PLAN 281 Final (10 decks)

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