Intro to Raster GIS
description
Transcript of Intro to Raster GIS
![Page 1: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/1.jpg)
Intro to Raster GIS
GTECH361Lecture 11
![Page 2: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/2.jpg)
CELL
![Page 3: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/3.jpg)
ROW
COLUMN
![Page 4: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/4.jpg)
CELL with VALUE
![Page 5: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/5.jpg)
![Page 6: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/6.jpg)
NO DATA
![Page 7: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/7.jpg)
Raster Attribute Table
![Page 8: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/8.jpg)
NODATA
![Page 9: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/9.jpg)
Coordinate Space and the Raster Dataset
![Page 10: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/10.jpg)
Discrete and Continuous
![Page 11: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/11.jpg)
Resolution
![Page 12: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/12.jpg)
Realm of Analysis• Window
identifies spatial limits for future analysis and processing
• Mask further defines the cells for processing
• Cell size determines the size of the cells on the output grids; default is the coarsest input grid
![Page 13: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/13.jpg)
Window
![Page 14: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/14.jpg)
The Effect of a Mask
![Page 15: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/15.jpg)
Map Algebra
aka Cartographic Modeling
![Page 16: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/16.jpg)
Dana Tomlin 1990
Geographic Information Systems
and Cartographic Modeling
Prentice-Hall
![Page 17: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/17.jpg)
Map Algebra
Mathematical combinations of layers
Several types of functions: Local Focal Zonal Global
Functions can be applied to one or more layers
![Page 18: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/18.jpg)
Local Functions
Sometimes called layer functions
Work on every single cell in a raster layer
Cells are processed without reference to surrounding cells
Operations can be arithmetic, trigonometric, exponential, logical or logarithmic functions
As we are dealing with numbers, we can use a plethora of mathematical computations.
![Page 19: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/19.jpg)
Local Functions
new layer is a functionof two or more inputlayers
output value for eachcell is a function ofthe values of the corresponding cells in the input layers
neighboring or distant cells have no effect
![Page 20: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/20.jpg)
Local Function Examples
Multiply cells by a constant value
Use a multiplier grid
We can use a range of arithmetic functions
1 1 2
4 2 3
2 3 0 4
2 0 1 1
3 3 6
12 6 9
6 9 0 12
6 0 3 3
X 3 =
1 1 2
4 2 3
2 3 0 4
2 0 1 1
3 3 6
12 6 9
6 9 0 12
6 0 3 3
X
3 3 12
48 12 27
12 27 0 48
12 0 3 3
=
![Page 21: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/21.jpg)
Local Operations
Creating grids from nothing (0-ary operations)
Random Populate the cell values with independent identically distributed (iid) floating point values between 0 and 1
NormalPopulate the cell values with iid values from the standard Normal distribution (mean 0 and variance 1).
![Page 22: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/22.jpg)
Local Operations- unary operations -
Rescale: multiply all values by a constant
Compare a grid to a constant value. The result of a comparison is 1 for the cells where the comparison is true, 0 where the comparison is false
Apply a mathematical (or logical) function to a grid, cell by cell
![Page 23: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/23.jpg)
Mathematical operators
MOD * / + - ()exp
Logical operators AND OR XOR NOT
Local Operations- binary operations -
![Page 24: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/24.jpg)
Neighborhood Operations
(focal)
output cell value isa function of a groupof neighboring cellsin the input raster
operations could be- average (focalmean)- sum (focalsum)- variance (focalvar)- …..
![Page 25: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/25.jpg)
Focal Functions
Focal functions process cell data depending on the values of neighboring cells
We define a ‘kernel’ to use as the neighborhood for example, 2x2, 3x3, 4x4 cells
Sometimes in spatial analysis we use shapes to define the focal neighborhood
Around edges a reduced kernel size is used Types of focal functions might be:
focal sum, focal mean, focal max, focal min, focal range
![Page 26: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/26.jpg)
Focal Function Examples
Focal Sum (sums the value of a neighborhood)
Focal Mean (computes the moving average of a neighborhood)
1 1 3 2
4 2 2 3
2 3 0 4
2 0 1 1
8 13 13 10
13 18 20 14
13 16 16 11
7 8 9 6
=
1 1 3 2
4 2 2 3
2 3 0 4
2 0 1 1
2.02.22.22.5
2.22.02.22.3
2.22.01.81.8
1.81.31.51.5
=
![Page 27: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/27.jpg)
Another Focal Example
slope- steepness of slope in elevation layer- computed by comparing cell elevation with neighboring values- measured as the angle from horizontal
![Page 28: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/28.jpg)
Zonal Functions
Process and analyze cells on the basis of ‘zones’
Zones define cells that share a commoncharacteristic
Cells in the same zonedon’t have to be contiguous
![Page 29: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/29.jpg)
A typical zonal function requires two grids a zone grid which defines the size, shape and
location of each zone a value grid which is to be processed
Typical zonal functions include zonal mean, zonal max, zonal sum, zonal variety
also: sum of the values in different raster that fall into the same zone (e.g., mean district elevation)
results could be assigned to each cell in that zone, or written to a summary table
Zonal Functions
![Page 30: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/30.jpg)
Zonal Function Example
Zonal maximum - identify the maximum in each zone
Useful when we have some regions to classify with for example, different forest types
8 8 5 5
7 5
5 7 7 8
5 5 8 8
=
1 1 2 2
3 2
2 3 3 1
2 2 1 1
5 5 5 5
1 2 3 4
5 6 7 8
1 2 3 4
Zone Grid Value Grid
![Page 31: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/31.jpg)
Buffer as a Zonal Function
Can be thought of as spreading a feature by a given distance
Feature
Buffer
![Page 32: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/32.jpg)
Global Functions
The output value of each cell is a function of the entire grid
Typical global functions are distance measures, flow directions, or weighting measures.
Useful when we want to work out how cells ‘relate’ to each other
![Page 33: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/33.jpg)
Global Function Examples
Distance measures Euclidean distance computes distance
based on cell size
Use a ‘cost’ grid to weight functions
1.4 1 1.4 2
1 0 1 1
1.4 1 1 0
2 1 0 0
=2
1
1 1
2
1
1 1
Cost Grid
4.2 3 4.2 6
3 0 3 3
1.4 1 1 0
2 1 0 0
=
3 3 3 3
3 3 3 3
1 1 1 1
1 1 1 1
![Page 34: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/34.jpg)
Map Algebraon Multiple Layers
outgrid = zonalsum(zonegrid, valuegrid)
outgrid = focalsum(ingrid1, rectangle, 3, 3)
outgrid = (ingrid1 div ingrid2) * ingrid3
Map algebra can also be used for multivariate and regression analysis
![Page 35: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/35.jpg)
Application Functions
Surface Analysis
Hydrologic Analysis
Geometric Transformation
Generalization
![Page 36: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/36.jpg)
Surface Analysis Slope
Aspect
Hill shade
View shed
Curvature
Contour
![Page 37: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/37.jpg)
Hydrologic Analysis
Stream network
Watershed Discharge .. more under
modeling
![Page 38: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/38.jpg)
Generalization
Original satellite “Nibble” Majority filter
image
![Page 39: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/39.jpg)
GIS-based Spatial Analysis
Mapping distance
Mapping density
Interpolating to raster
Surface analysis
Neighborhood statistics
Cell statistics
Zonal statistics
Reclassifying data
Raster calculator
![Page 40: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/40.jpg)
Mapping Distance
Straight line distance (Thiessen/Voronoi)
![Page 41: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/41.jpg)
What Direction?
![Page 42: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/42.jpg)
Allocation Identifying the
customers served by a series of stores
Finding out which hospital is the closest
Finding areas with a shortage of fire hydrants
Locating areas that are not served by a chain of supermarkets
![Page 43: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/43.jpg)
Cost-weighted Distance
Cost can be money, time, or preference
Two input grids One regular distance grid One friction surface
Reclassifying your datasets to a common scale
Weighting datasets according to percent influence
![Page 44: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/44.jpg)
Cost Raster
![Page 45: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/45.jpg)
Shortest Path
Combination of (weighted) distance and direction
![Page 46: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/46.jpg)
Density Mapping
In a simple density calculation, points or lines that fall within the search area aresummed and then
divided by the search area size to get each cell’s density value.
![Page 47: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/47.jpg)
Interpolation
e.g. precipitation
![Page 48: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/48.jpg)
Surface Analysis
Contours Slope, aspect Viewshed
![Page 49: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/49.jpg)
Illumination at different times of the day
45° 315°
Viewshed analysis
![Page 50: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/50.jpg)
Cell Statistics
Majority Maximum Mean Median Minimum Minority Range Standard deviation Sum Variety
![Page 51: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/51.jpg)
Neighborhood Statistics
Neighborhood shapes
Application: ecosystem variety
rectangle circle annulus wedge
![Page 52: Intro to Raster GIS](https://reader035.fdocuments.in/reader035/viewer/2022062217/56813a21550346895da1fe8d/html5/thumbnails/52.jpg)
Zonal Statistics