Spatial analysis: Raster features Flashcards

Lecure 17

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1
Q

what is raster analysis?

A

spatial analysis of raster data
Use integer beased grids to represent discrete data and f,oaring-points to represent continuous data.

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2
Q

Integer rasters?

A

VAT tables (value attribute table)
Record stores unique values and the number of cells in the grid represented by that value.
Can have cells with no data = not 0!!

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3
Q

Floating-point grids?

A

No VAT
cells in grid can assume any value within a given range of categories.
No discrete categories.
Elevation data.

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4
Q

Raster analysis in ArcGIS

A
  1. Spatial analyst is activated
  2. Specifed raster environemnet set
    Area can correspond to specific raster, area defined by min and max co-ordinates, combination of rasters.
  • Analyses are performed using GUI tools
  • Spatial Analyst Tools < Map Algebra

<Raster Calculator

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5
Q

What are raster operations?

A

Various spatial analyses can be perfomred on raster data:
1. Local
2. Neighborhood / Focal
3. Zonal
4. Global

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6
Q

What are local raster operations?

A

cell-by-cell operations
New raster from a single or multiple raster inputs
new cell values are computed by relating inout to output raster.
Local functions apply an indepndant calculation to each individual input raster cell - use Map Algebra.

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7
Q

Types of local raster operation

A

Reclassification
Multiple raster layers

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8
Q

What is reclassification?

A
  • Creating new rasters through classification
  • Recoding / transforming
  • 2 ways:
  • one-to-one
    *range-to-one

purpose?:
Simplifying raster
Creating new rasters
Shows ranking

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9
Q

What are multiple rasters?

A
  • Composting, overlaying, superimposing.
  • Numeric data to calc output values
  • No-data in input = no data in output
  • Summary stats = max,min,ave, median,sum, SD
  • use numeric or categorical data to calc output
  • combine assigns a value output to each unique combination of inpout vals
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10
Q

What is focal raster operations?

A

Focal cell and set of its surrounding cells
Surrounding cells are sued for distance and directional relationship of focal cell.
common neighbourhood shapes = rectangle, circle, annulus, wedge.
Some cells may only be partially covered by defined neighbourhood.
General Rule include cell if its centre falls within defined area
focal cell marked with x

works on single rasters
function applys one calculation to all input raster cells within a neighbourhood.

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11
Q

Examples of focal operation?

A

simplification and generalizaion = reduces the level of cell value fluctuation.
smoothing = calculate the majority statistic using 3x3 neighbourhood assigning most frequent value.
Feature manipulation = uses range measure the different between min and max, high values indicates an edge.
Variety = tabultes the number of idfferent cell values in the neighbourhood and assigns a new value to the focal cell.
site selection = Ability to summarize stats in a
defined area
terrian analysis = Slope, aspect and surface
curvature measurements are all derived from
neighborhood operations using elevation data

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12
Q

What are raster zonal operations?

A

work with groups of cells of the same value or like
features
may be contiguous or non-contiguous.
are defined as a group of cells having the same value
Zonal functions apply one calculation to all input raster cells within each zone.
Summary stats and measures include: area, min, max, range, sum, mean,
standard deviation and median, majority, minority, variety [if the input raster = Integer]

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13
Q

zonal functions?

A

Useful for studies of landscape ecology

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14
Q

What are raster global operations?

A

Extended neighborhood operations
Global functions apply a calculation considering all cell values in the
raster

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15
Q

What are distance measure operations?

A
  • Physical distance can also be called neighborhood or global operations
  • Physical distance measure straight-line (Euclidean) distances away from cells (Via Pythagoras).
  • Cost distance - considers time, cost, speed, etc
  • “Buffers” source cells with wavelike continuous distances over the entire raster
  • Reclassify can convert a continuous raster to one with discrete distance zones
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16
Q

What is the definition of distance?

A

The physical distance measures in cell units from each cell to the closest source cell.

17
Q

Calculating distance surfaces and buffers?

A

allocation - closest source cell
direction - to the closest source cell

18
Q

Other raster operation examples?

A
  1. Raster Data Management
    – Mask: Is kind of like clipping
    – Mosaic: Combining multiple rasters into a single raster
  2. Data extraction (like CLIP in Vector data analysis)
  3. Data generalization
19
Q

What are raster generalisations?

A
  • Aggregate/ Aggregation
  • Resampling technique that lowers resolution of raster.
  • Calculates output cell value of all input cells that fall within the new (larger) output cell.
  • Summary stats like min, max, range, sum, mean, median and standard deviation apply.
  • RegionGroup -> aggregate per zone.

Map algebra:
Map algebra is calculated with the Raster Calculator Tool
output raster is always binary.

20
Q

Calculations accross multiple rasters?

A

Multi-raster analyses is possible because of spatial registration multiple raster layers share the same X, Y coordinate space cell values are calculated across multiple raster layers to create a single output raster layer.

21
Q

Map querying across various raster layers?

A
  • Raster Calculator is easy to use and gives rapid results
  • Results of overlay depend on cell size & relative precision
  • Multiple rasters can be simultaneously queried (whereas only 2 vector layers can be compared in vector overlay)
  • Output represents cells that meet and do not meet query criteria.

in Arc GIS
Map Query - Find cells where:
1.distance to streams < 300 ft and
2.elevation > 1500 ft and
3.timber volume > 60 mbf/ac
Result is a new temporary raster
Cells that meet all three criteria identified (value = 1)

22
Q

Vector vs raster analysis overlay comparasin.

A

Vector:
* Intersection must be computed
* Vector overlay can only combine attributes from input layers.
Computation must follow overlay
* All attributes from input layers can be combined, then queried and analysed
* Efficient if large number of attributes share same geometry

Raster:
* Same cell size and area extent
* Many mathematical functions available through Raster Calculator
* Each input raster is associated with a single spatial variable, i.e. one raster for each attribute
* Computationally more efficient

23
Q

Vector vs raster buffer analysis comparasin.

A

vector:
* Uses x-, y- coordinates in measuring distances
* More accurate buffer zones
* More flexible buffer options
– Multiple ring buffers
– Separate / dissolved buffers

raster:
* Uses cells in measuring distances
* Continuous distance measures
– requires additional data processing (reclassify/slice) to define buffers
– Difficult to create and manipulate separate distance measures