Download - Working with Rasters
![Page 1: Working with Rasters](https://reader036.vdocuments.net/reader036/viewer/2022062323/56816689550346895dda455c/html5/thumbnails/1.jpg)
CS 128/ES 228 - Lecture 5a 1
Working with Rasters
![Page 2: Working with Rasters](https://reader036.vdocuments.net/reader036/viewer/2022062323/56816689550346895dda455c/html5/thumbnails/2.jpg)
CS 128/ES 228 - Lecture 5a 2
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
![Page 3: Working with Rasters](https://reader036.vdocuments.net/reader036/viewer/2022062323/56816689550346895dda455c/html5/thumbnails/3.jpg)
CS 128/ES 228 - Lecture 5a 3
Issue #1 - resolutionLarger cells: less precise
spatial fix
line + boundary thickening
features too close overlap - less detail possible
Fig. 3.10, 3rd ed.
![Page 4: Working with Rasters](https://reader036.vdocuments.net/reader036/viewer/2022062323/56816689550346895dda455c/html5/thumbnails/4.jpg)
CS 128/ES 228 - Lecture 5a 4
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
![Page 5: Working with Rasters](https://reader036.vdocuments.net/reader036/viewer/2022062323/56816689550346895dda455c/html5/thumbnails/5.jpg)
CS 128/ES 228 - Lecture 5a 5
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
![Page 6: Working with Rasters](https://reader036.vdocuments.net/reader036/viewer/2022062323/56816689550346895dda455c/html5/thumbnails/6.jpg)
CS 128/ES 228 - Lecture 5a 6
Image depth minimum = 1 bit
B/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
![Page 7: Working with Rasters](https://reader036.vdocuments.net/reader036/viewer/2022062323/56816689550346895dda455c/html5/thumbnails/7.jpg)
CS 128/ES 228 - Lecture 5a 7
Determining cell values
![Page 8: Working with Rasters](https://reader036.vdocuments.net/reader036/viewer/2022062323/56816689550346895dda455c/html5/thumbnails/8.jpg)
CS 128/ES 228 - Lecture 5a 8
Filtering raster data Neighborhood
averaging
Smoothes “holes” and transitions
Other techniques available
Chang 2002, p. 203
![Page 9: Working with Rasters](https://reader036.vdocuments.net/reader036/viewer/2022062323/56816689550346895dda455c/html5/thumbnails/9.jpg)
CS 128/ES 228 - Lecture 5a 9
Issue #3 - layers in raster format Each layer must
be referenced in common coordinates
Thematic data can be combined and revised (reclassified)
![Page 10: Working with Rasters](https://reader036.vdocuments.net/reader036/viewer/2022062323/56816689550346895dda455c/html5/thumbnails/10.jpg)
CS 128/ES 228 - Lecture 5a 10
Analysis by raster overlay
Fig. 6.17, 3rd ed.
![Page 11: Working with Rasters](https://reader036.vdocuments.net/reader036/viewer/2022062323/56816689550346895dda455c/html5/thumbnails/11.jpg)
CS 128/ES 228 - Lecture 5a 11
Lack of spatial registration
![Page 12: Working with Rasters](https://reader036.vdocuments.net/reader036/viewer/2022062323/56816689550346895dda455c/html5/thumbnails/12.jpg)
CS 128/ES 228 - Lecture 5a 12
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”
![Page 13: Working with Rasters](https://reader036.vdocuments.net/reader036/viewer/2022062323/56816689550346895dda455c/html5/thumbnails/13.jpg)
CS 128/ES 228 - Lecture 5a 13
Issue #4 – mosaicking rasters
http://www.microimages.com/featupd/v57/mosaic/
![Page 14: Working with Rasters](https://reader036.vdocuments.net/reader036/viewer/2022062323/56816689550346895dda455c/html5/thumbnails/14.jpg)
CS 128/ES 228 - Lecture 5a 14
Mosaicking: mismatched tilesEx. 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
![Page 15: Working with Rasters](https://reader036.vdocuments.net/reader036/viewer/2022062323/56816689550346895dda455c/html5/thumbnails/15.jpg)
CS 128/ES 228 - Lecture 5a 15
Mosaicking: adjusting color valuesHistogram matching:
Computer compiles histogram of color (or gray) values in 1 tile
2nd tile’s colors adjusted to match
![Page 16: Working with Rasters](https://reader036.vdocuments.net/reader036/viewer/2022062323/56816689550346895dda455c/html5/thumbnails/16.jpg)
CS 128/ES 228 - Lecture 5a 16
Raster data editing
![Page 17: Working with Rasters](https://reader036.vdocuments.net/reader036/viewer/2022062323/56816689550346895dda455c/html5/thumbnails/17.jpg)
CS 128/ES 228 - Lecture 5a 17
Clip to rectangle ...
![Page 18: Working with Rasters](https://reader036.vdocuments.net/reader036/viewer/2022062323/56816689550346895dda455c/html5/thumbnails/18.jpg)
CS 128/ES 228 - Lecture 5a 18
… vs. clip to shapefile
![Page 19: Working with Rasters](https://reader036.vdocuments.net/reader036/viewer/2022062323/56816689550346895dda455c/html5/thumbnails/19.jpg)
CS 128/ES 228 - Lecture 5a 19
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)