CS 128/ES 228 - Lecture 5a1 Working with Rasters.

CS 128/ES 228 - Lecture 5a 1

Working with Rasters


Spatial modeling in raster format

Basic entity is the cell

Region represented by a tiling of cells

Cell size = resolution

Attribute data linked to individual cells


Issue #1 - resolution

Larger cells: less precise

spatial fix

line + boundary thickening

features too close overlap - less detail possible

Fig. 3.10, 3rd ed.


Why not always use tiny cells?

Data inputs may have limited spatial resolution - pixel size for aerial, satellite photos- reliability of coordinate measurements

Size of data files

Speed of analysis


Issue #2 - determining cell values Data inputs may already

contain cell values: aerial, satellite photos

Cell values may be assigned: “pseudocolors”

Ultimately all cell values must be coded numerically


Image depth

minimum = 1 bitB/W image or P/A data

8-bit image = 256 levels of gray (can be pseudo-colored)

24-bit image = true-color. Each primary color has separate layer


Determining cell values


Filtering raster data

Neighborhood averaging

Smoothes “holes” and transitions

Other techniques available

Chang 2002, p. 203


Issue #3 - layers in raster format

Each layer must be referenced in common coordinates

Thematic data can be combined and revised (reclassified)


Analysis by raster overlay

Fig. 6.17, 3rd ed.


Lack of spatial registration


Georeferencing raster images

Spatial coordinates may be absent or purely map coordinates (i.e. inches from one corner)

Control points: point features visible on both the image and the map

Linear or nonlinear transformations

“Rubber sheeting”


Issue #4 – mosaicking rasters

http://www.microimages.com/featupd/v57/mosaic/


Mosaicking: mismatched tiles

Ex. Aerial photographs of Kinzua Reservoir

What do you suppose caused the drastic differences in water clarity in the lake?

Google map of Onoville, NY. Accessed 6 Oct 2008


Mosaicking: adjusting color values

Histogram matching:

Computer compiles histogram of color (or gray) values in 1 tile

2nd tile’s colors adjusted to match


Raster data editing


Clip to rectangle ...


… vs. clip to shapefile


Summary A huge amount of spatial

data are available in raster format

Rasters make excellent “base maps”

Easy to layer but watch coordinate systems!

Difficult/impossible to edit or reproject USGS Digital Raster Graphic (DRG) Quadrangle

(1:24,000 scale - UTM Zone 17, NAD 27)

CS 128/ES 228 - Lecture 5a1 Working with Rasters.

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