raster analysis and terrain analysis chapter 10 & 11 raster analysis
TRANSCRIPT
Raster Analysis and Terrain Analysis
Chapter 10 & 11Raster Analysis
Raster Data Model
•Raster cells store data (nominal, ordinal, interval/ratio)
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•Excellent for terrain and hydrological modeling•Complex constructs built from raster data
-Connected cells can be formed in to networks -Related cells can be grouped into neighborhoods or regions
Examples of Raster Analysis
•Predict fate of pollutants in the atmosphere•The spread of disease•Animal migrations•Crop yields•EPA - hazard analysis of urban superfund sites•Market analysis•Watershed analysis•Terrain analysis
Map algebra•Concept introduced and developed by Dana Tomlin and Joseph Berry (1970’s)
•Cell by Cell combination of raster data layers
-Each number represents a value at a raster cell location-Simple operations can be applied to each number-Raster layers may be combined through operations such as addition, subtraction and multiplication
Scope: Local operations
Many Local Functions
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Logical OperationsAND
Non-zero values are “true”, zero values are “false”N = null values
Logical OperationsOR
Non-zero values are “true”, zero values are “false”N = null values
Logical OperationsNOT
More Local Functions – logical comparisons
An Example of a Logical Operation
Reclassification
ConditionalFunction
Nested Functions
Overlay
Raster Clip Operation
Raster Addition
Be Careful of Ambiguity
Be Careful of Ambiguity
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Raster Overlay in Idrisi
1 0 1
1 0 1
1 0 1
1 1 1
0 0 1
0 0 1
1 0 1
0 0 1
0 0 1
First * Second
0*0=0
0*1=0
1*1=1
1 0 1
1 0 1
1 0 1
1 1 1
0 0 1
0 0 1
2 1 2
1 0 2
1 0 2
First + Second
0+0=0
0+1=1
1+1=2
Scope: Neighborhood operations
Neighborhood Operations
Moving Windows(Windows can be any size; often odd to provide a center)
Kernels vs. Moving Window
Neighborhood Operations: Separate edge kernals can be used
Neighborhood Operations
Example:Identifying spatial differences in a raster layer
Raster Analysis
Moving windows and kernals can be used with a mean kernal to reduce the difference between a cell and surrounding cells. (done by average across a group of cells)
Raster data may also contain “noise”; values that are large or small relative to their spatial context.(Noise often requiring correction or smooth(ing))
Know as “high-pass” filters
The identified spikes or pits can then be corrected or removed by editing
Zonal Functions
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Scope: Global operation
ArcMap’s Raster Calculator
Raster Calculator tool dialog box exampleFrom ArcGIS Help Files
Cost Surface
The minimum cost of reaching cells in a layer from one or more sources cells
“travel costs”Time to school; hospital; Chance of noxious foreign weed spreading out from an introduction point
•Units can be money, time, etc.
•Distance measure is combined with a fixed cost per unit distance to calculate travel cost
•If multiple source cells, the lowest cost is typically placed in the output cell
Friction Surface (version of a Cost Surface)
The cell values of a friction surface represent the cost per unit travel distance for crossing each cell – varies from cell to cell
Used to represent areas with variable travel cost.
Notes:•Barriers can be added.
•Multiple paths are often not allowed
•Cost and Friction Surfaces are always related to a source cell(s); “from something”
•The center of a cell is always used the distance calculations
Friction Surface
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Terrain Analysis
Digital Elevation Models (DEM)/Terrain Analysis
Terrain determines the natural availability and location of surface water, and hence soil moisture and drainage.
Water quality through control of sediment entrainment and transport, slope steepness and direction defines flood zones, watershed boundaries and hydrologic networks.
Terrain also strongly influences location and nature of transportation networks or the cost and methods of house and road construction.
Digital Elevation Models
Terrain AnalysisSlope and Aspect
•Used for: hydrology, conservation, site planning, other infrastructure development.
•Watershed boundaries, flowpaths and direction, erosion modeling, and viewshed determination all use slope and/or aspect data as input.
•Slope is defined as the change is elevation (a rise) with a change in horizontal position (a run).
•Slope is often reported in degrees (0° is flat, 90° is vertical)
Slope (continued)
Slope (continued)Measured in the steepest direction of elevation change
Often does not fall parallel to the raster rows or columns
Which cells to use?
Several different methods:
•Four nearest cells•3rd Order Finite Difference
Slope (continued)
Elevation is Z•Using a 3 by 3 (or 5 by 5) moving window•Each cell is assigned a subscript and the elevation value at that location is referred to by a subscripted Z value
The most common formula:
Slope (continued)
for Zo
ΔZ/Δx = (49 – 40)/20 = 0.45
ΔZ/Δy = (45 – 48)/20 = -0.15
Slope (continued)
•Slope calculation base on cells adjacent to the center cell•The distance is from cell center to cell center
for Zo
ΔZ/Δx = (49 – 40)/20 = 0.45
ΔZ/Δy = (45 – 48)/20 = -0.15
Generalized formula for
ΔZ/Δx and ΔZ/Δy
ΔZ/Δx = (Z5 – Z4)2*
ΔZ/Δy = (Z2 – Z7)2*
Using the four nearest cells
* = times cell width
Slope (continued)
ΔZ/Δx = (49 – 40)/20 = 0.45 ΔZ/Δy = (45 – 48)/20 = -0.15
Kernal for ΔZ/Δx Kernal for ΔZ/Δy
Multiply (kernal, cell by cell)Add (results)Divide by #cells x cell widthUse slope formula
Multiply (kernal, cell by cell)Add (results)Divide by #cells x cell widthUse slope formula
Slope in ArcGIS 10
From ArcGIS 10 Help
Aspect
Aspect
The orientation (in compass angles) of a slope
Calculation:
Aspect = tan-1[ -(ΔZ/Δy)/(ΔZ/Δx)]
As with slope, estimated aspect varies with the methods used to determine ΔZ/Δx and ΔZ/Δy
Aspect calculations also use the four nearest cell or the 3rd-order finite difference methods
Aspect in ArcGIS 10
From ArcGIS 10 Help
Curvature
Viewshed
The viewshed for a point is the collectionof areas visible from that point.
Views from any non-flat location are blocked byterrain.
Elevations will hide a point if they are higher than the viewing point, or higher than the line of site between the viewing point and target point
Shaded Relief Surfaces
From ArcGIS 10 Desktop Help
Flow Direction
Raster Analysis
High pass filters
Return: •Small values when smoothly changing values.•Large positive values when centered on a spike•Large negative values when centered on a pit
High Pass Filter
• Raster data may also contain “noise”; values that are large or small relative to their spatial context.
• A mean kernal is used to reduce the difference between a cell and surrounding cells. (done by average across a group of cells)
• The identified spikes or pits can then be corrected or removed by editing
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Watershed
•An area that contributes flow to a point on the landscapeWater falling anywhere in the upstream area of a watershed will pass through that point.
•Many be small or large
•Identified from a flow direction surface
Drainage network
•A set of cells through which surface water flows
•Based on the flow direction surface
Routing and Allocation•Routing
–Finding the shortest path between any nodes in a network–Optimal path
•Each link in the net can also be assigned an impedance value •Using an accumulated distance and the impedance factor
–Most efficient route can be found, rather than just the shortest
–Nodes can also be coded with stops and barriers•Preventing movement and forcing traffic along another path
–Although routing can be done in raster, it is much easier if performed in a vector system
Routing and Allocation
•Allocation –Process used to define the areal extent of services areas
–Service areas are defined around a site•Region is formed that includes a defined area
–Location/allocation model (optimizes network efficiency)•Technique for the evaluation of multiple facility locations
–Determining the configuration of facilities (location)–Assigning demand for the facilities (allocation)