Raster Data Model
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Transcript of Raster Data Model
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Raster Data ModelRaster Data Model
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How to Represent Point Features in How to Represent Point Features in Raster Data ModelsRaster Data Models
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How to Represent Line Features in How to Represent Line Features in Raster Data ModelsRaster Data Models
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How to Represent Polygon Features How to Represent Polygon Features in Raster Data Modelin Raster Data Model
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Raster Data ModelsRaster Data Models
For Raster Model there are ◦Array of pixels (each pixel representing a
specific value)◦A matrix consisting of rows and columns with
each grid or pixel representing a specific value
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Raster Data ModelRaster Data Model
Raster data is an abstraction of the real world where spatial data is expressed as a matrix of cells or pixels with spatial position implicit in the ordering of the pixels
They store each cell in the matrix regardless of whether it is a feature or simply 'empty' space
Typically these cells are square and evenly spaced in the x and y directions
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Raster Data Model - ExampleRaster Data Model - Example
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Cell ValueCell Value
Cell values can be either positive or negative, integer, or floating point
Integer values are best used to represent categorical (discrete) data
Floating-point values to represent continuous surfaces
Cells can also have a ‘No Data’ value to represent the absence of data
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Grid Size and ResolutionGrid Size and ResolutionPixel/cell refers to the smallest unit of
information available in an image or raster map
Cell dimension specifies the length and width of the cell in surface units, e.g. the cell dimension may be specified as 30 meters on each side
volume of data increases as the cell dimension gets smaller
Reducing the cell dimension by four causes a sixteen fold increase in the number of cells
Smaller cell size provides greater spatial detail
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Grid Size and ResolutionGrid Size and Resolution
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Generic Structure for a GridGeneric Structure for a Grid
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Raster Data ModelRaster Data Model
Smaller Cell Size
• Higher resolution
• Higher feature spatial accuracy
• Slower display
• Slower processing
• Larger file size
Smaller Cell Size
• Higher resolution
• Higher feature spatial accuracy
• Slower display
• Slower processing
• Larger file size
16 m
Larger Cell Size
• Lower resolution
• Lower feature spatial accuracy
• Faster display
• Faster processing
• Smaller file size
Larger Cell Size
• Lower resolution
• Lower feature spatial accuracy
• Faster display
• Faster processing
• Smaller file size
16 m
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Data Accuracy with CellData Accuracy with Cell
Value is correct when variable value is uniform over the raster cell
In case of within cell variation then average, central or most common value prevails
Mixed Pixel Problem
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Types of Raster DataTypes of Raster Data
Thematic Raster◦ Like a map describes the features
and characteristics of an area and their relative position in space
◦ Cell values are measured quantity or classification of a particular phenomenon (either integers or real numbers
◦ Stored in a single bandImage Raster
◦ Cell values represent reflected or emitted light/energy
◦ Usually in 3 bands◦ Satellite image or scanned
photographs
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Rasters – As Thematic MapRasters – As Thematic Map
By grouping the values of multispectral data into classes (such as vegetation type) and assigns a categorical value
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Rasters – As Base MapRasters – As Base Map
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Raster – As Surface MapRaster – As Surface Map
Rasters provide an effective method of storing the continuity as a surface
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Rasters – As Attributes of a FeatureRasters – As Attributes of a Feature
Rasters used as attributes of a feature may be digital photographs, scanned documents, or scanned drawings related to a geographic object or location
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Raster Attribute TableRaster Attribute Table
Raster values and other attributes are stored in the Value Attribute Table (VAT)
A thematic raster contains at least two items in its VAT◦Value:
Represents some characteristics being mapped◦Count:
Number of cells that share the same value
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Raster Attribute TableRaster Attribute Table
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Zone and RegionZone and Region
Cells with same value makeup ‘Zone’ ◦The size of the zone is
defined by the ‘count’ item
A set of contiguous cells with the same value is called a ‘Region’
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Raster OverlayRaster Overlay
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Raster OverlayRaster Overlay
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Raster OverlayRaster Overlay
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‘‘NoData’ ValueNoData’ Value
Represents missing or unknown information
When a cell is vacant, it’s assigned ‘NoData’ value
‘NoData’ remain always ‘NoData’ for ESRI rasters unless specifically requested
Combining 2 or more ESRI rasters will retain ‘NoData’ values in the outer raster
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Acquiring Raster DataAcquiring Raster Data
Satellite Remote SensingAerial ImagingUSGS Raster sources
◦DOQQ: Digital Orthophoto Quarter Quads are rectified scanned aerial photographs
◦DRG: Digital Raster Graphics are scanned USGS topo sheets
◦DEM: Digital elevation model (DEM) is a digital representation of ground surface topography
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Data SourcesData Sources
Digitizing existing mapsScanning existing mapsDigital photogrammetric map productionEntry of computed coordinates from field
measurements
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PRODUCT NAME DATA TYPE
DESCRIPTION SCALE
USGS DEM "Digital Elevation Model" Raster grid Elevation x,y,z values used for 3 dimensional display and topographic analysis.
1:24,0001:100,0001:2,000,000
USGS DOQQ "Digital OrthophotoQuarter Quad"
Raster TIFF Georeferenced digital orthorectified aerial photography
1:12,000
USGS DRG "Digital Raster Graphic" Raster TIFF Georeferenced digital scans of USGS topo sheets.
1:24,000
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DEM
DOQQ
DRG
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Raster Data – A Simple Data StructureRaster Data – A Simple Data Structure
A simple data structure—A matrix of cells with values representing a coordinate and sometimes linked to an attribute table
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Advantages of Raster Data FormatsAdvantages of Raster Data FormatsCan represents different types of continuous
surfaces and ability to perform surface analysisComputing/processing is fastSurface data faster to displayOverlaying maps is easyIntegration of remotely sensed imagery is
straightforwardTiling facilitates easy handling of large dataGood for accomplishing complex analysis
operations through complex raster expressions (A huge variety of complex spatial and advanced statistical analyses are supported)
Only solution for some application which can not handled by vector◦ Hydrologic modeling, spread of wild fire, air pollution
dispersion etc.
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Disadvantages of Raster Data Disadvantages of Raster Data FormatsFormats
Spatial inaccuracies due to the limits imposed by the raster dataset cell dimensions.
Very large datasets needs more memory space and more processing time◦ Changing cells to one-half the current size
requires as much as four times the storage space
There is also a loss of precision
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Advantages/Disadvantages of Advantages/Disadvantages of Raster and VectorRaster and Vector
Raster Vector
Precision in graphics
Traditional cartography
Data volume
Topology
Computation
Update
Continuous space
Integration
Discontinuous
Source: http://www.geom.unimelb.edu.au/gisweb/GISModule/GIST_Raster.htm
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Homework 1 (T)Homework 1 (T)1. Read Chapter 2 of the Text Book (Bolstad) –
(specially the sections covered in class lectures)
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Conversion Between Raster and Conversion Between Raster and Vector Data ModelsVector Data Models
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http://web.pdx.edu/~jduh/courses/geog492w09/Week2b.pdf
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Spatial Data ConversionSpatial Data Conversion
Vector to Raster or RasterizationRaster to Vector or Vectorization
Converted data is less accurate than original data
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Vector to Raster (V2R)Vector to Raster (V2R)Assign a cell value for each position
occupied by vector features
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Vector to Raster Encoding Vector to Raster Encoding MethodsMethods
Center Cell Method◦The center location of the cell determines the
raster value encoded from the vector dataMajority of Cell Method
◦The value in the vector dataset that covers the majority of the cells determines the cell value
Weighted Cell Method◦Analyst determines which vector value is most
important by weighting the optionsPercent of cell method
◦Encodes the cell by multiple values based on the percentage of the cell taken up by each feature
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Vector to Raster Encoding Vector to Raster Encoding MethodsMethods
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Conversion of Vector Conversion of Vector PointPoint FeatureFeature
Represented by a value in a raster cellAssigned to the cell containing the point
coordinateHave at least the dimension of the raster cell
after conversion
Problem:Problem:
If the cell size is too large, two or more vector points may fall in the same cell
To avoid this problem a cell size is chosen having the diagonal dimension smaller than the distance between the two closest point features
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Conversion of Vector Conversion of Vector LineLine Feature Feature
Output depends on the input algorithm used
Raster cells may be coded using different criteria/rules
1. Assign a value to a cell if a vector line intersects with any part of the cell– Line connections maintained– Wider lines
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Conversion of Vector Conversion of Vector LineLine Feature Feature
2. Assign a cell as occupied by a line only when the cell center is “near” a vector line segment
– May lead to discontinuity in lines– Thinner linear features
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Conversion of Vector Conversion of Vector AreaArea Feature Feature
Boundaries among different polygons are identified as in vector to- raster conversion for lines◦Assign the cell to the area if more than one half
the cell is within the vector polygonOR
◦Assign a raster cell to an area feature if any part of the raster cell is within the area contained within the vector polygon
Interior regions are then identifiedEach cell in the interior region is assigned
a given value
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Raster to Vector (R2V)Raster to Vector (R2V)
Point, line, or area features represented by raster cells may be converted to corresponding vector data coordinates and structures
The quality and resolution of the raster image are key factors for the quality and accuracy of the vectorized data
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R2V - Point FeatureR2V - Point Feature
A single raster cell represents point feature
Each vector point feature is assigned the coordinate of the corresponding cell center
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R2V - Linear FeatureR2V - Linear Feature
Linear features represented in a raster environment may be converted to vector lines
Conversion to vector lines typically involves identifying the continuous connected set of grid cells that form the line.
Cell centers are typically taken as the locations of vertices along the line
Lines may then be “smoothed” using a mathematical algorithm to remove the “stair-step” effect.
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R2V - Linear FeatureR2V - Linear Feature
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R2V - Area FeatureR2V - Area Feature
Each raster cell is assigned an attribute value
Boundaries are set up between different attribute classes
A polygon is created by storing x and y coordinates for the points adjacent to the boundaries
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R2V - Conversion ErrorsR2V - Conversion Errors
Example:
Vector to raster conversion generally involves a loss in precision
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ArGIS Tools for ConversionArGIS Tools for ConversionSpatial Analyst, ArcScan and ArcToolbox
Conversion Tools◦Raster to polygon conversion◦Contour Generation◦Surface Interpolation from point data◦Etc.
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Raster Operation in ArcGISRaster Operation in ArcGISSimple Mathematical Operations
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Conditional AnalysisConditional Analysis
Conditional Tool: ArcToolbox> Spatial Analysis Tools > Conditional Toolset
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ExtractionExtraction
Extraction Tool: ArcToolbox> Spatial Analysis Tools > Extraction Toolset
◦Extract by Attribute
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ExtractionExtraction
◦Extract by Mask
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ReclassifyReclassify
To reassign raster values in order to create new values
Spatial Analyst > Reclass Toolset
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Single Output Map AlgebraSingle Output Map Algebra
Spatial Analyst > Map Algebra toolsetTo write single line equations with map
algebra expressions Examples:
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Cell Statistics ToolsCell Statistics Tools
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ReferencesReferencesChapter 2 of the text http://mason.gmu.edu/~mvenigal/David P. Lusch, 1999Ron Briggs UT Dallashttp://www.sli.unimelb.edu.au/gisweb/http://bgis.sanbi.org/GIS primer/page_15.h
tmhttp://webhelp.esri.com/arcgisdesktop/9.2/http://gis.esri.comhttp://www.satimagingcorp.com/characteri
zation-of-satellite-remote-sensing-systems.html