1. Data Models (Raster) Reading Assignment: Bolstad, Chapter 2

2. Rasters (Digital Photos)

3. Zoomed In

4. Pixelation

5. Raster = Matrix of Pixels

6. Rasters... Similar to a digital photograph Natural for scanned or remotely sensed data. Can Represent: –continuous surfaces (e.g., topography) –Or categorical (land cover types) Can take much more space Rasters provide uniform (same cell size) coverage for an area

7. Raster Data Model Uses grid cells of a given dimension to represent the value or attribute of a real world entity or phenomenon.

8. In a raster layer, the cells are arranged in rows and columns. All cells in a raster layer are the same size. Cell Size = Spatial Resolution: the dimension of the area covered on the ground and represented by a single cell (e.g., 10m).

9. The value may be a measurement or a code. Cell values are numeric: can be either positive or negative, integer, or floating point.

10. NameArcGIS Attributes ArcGIS GRIDS*Geodatabase Bit1 bit Chew2 bit Nibble4 bit Unsigned byteUnsigned 8 bit Signed byteSigned 8 bit Unsigned shortUnsigned 16 bit Signed shortShort IntegerSigned 16 bitShort Integer Unsigned IntegerUnsigned 32 bit Signed IntegerSigned 32bitLong integer LongLong Integer Float Floating-point 32 bitSingle-precision floating point Double Double-precision floating-point StringText Date * ArcGIS documentation indicates the GRID values are always stored as 32-bit values See: http://www.esri.com/news/arcuser/1002/files/table_2.pdf,http://www.esri.com/news/arcuser/1002/files/table_2.pdf http://webhelp.esri.com/arcgisdesktop/9.3/index.cfm?TopicName=Bit_depth_capacity_for_raster_dataset_cellshttp://webhelp.esri.com/arcgisdesktop/9.3/index.cfm?TopicName=Bit_depth_capacity_for_raster_dataset_cells, http://webhelp.esri.com/arcgisdesktop/9.3/index.cfm?topicname=Technical_specifications_for_raster_dataset_formats ArcGIS Data Types

11. NameNumber of Bits Number of Bytes Minimum ValueMaximum Value Number of Values Sig. Digits Bit11/8012 (2 1 )<1 Chew2¼034 (2 2 )<1 Nibble4½01516 (2 4 ) Unsigned Byte810255256 (2 8 )>2 Signed Byte (aka chars) 81-128127256 (2 8 )>2 Unsigned Short162-327683276765536 (2 16 or 64k)>4 Signed Short16206553565536 (2 16 or 64k)>4 Unsigned Integer (Int) 32404,294,967,2954,294,967,296 (2 32 or 4 Gig) >9 Signed Integer324-2,147,483,6482,147,483,6474,294,967,295>9 Long (always signed) 648A big negative number A big positive number 2 64 >19 Float (always signed) 324~10 -40 ~10 40 2 32 ~7 Double (always signed) 648~10 -300 ~10 300 2 64 ~15 See: http://en.wikipedia.org/wiki/Integer_overflow, http://steve.hollasch.net/cgindex/coding/ieeefloat.htmlhttp://en.wikipedia.org/wiki/Integer_overflow Computer-Based Numeric Data Types

12. Statewide GIS layer (GRID format) of the “working landscape” (areas managed for ag/timber/forage, urban and residential areas, public and private ownership, and reserves )

13. Images: True Color Composite (multi-band raster data set; 3 raster layers; 1 each for RGB) Spectral Reflectance

14. Raster Coordinate Data Coordinates of a corner location are stored (origin). –This and cell dimension are used to calculate location of other cells. Column X cell = X lower-left + column * cell size X cell4 = 100,000 + (4 * 10) = 100,040 01 245 3 ?

15. Raster File Formats –All standard image formats (JPG, TIFF, GIF) –Imagine –Mr. Sid –ESRI GRID

16. Conversion between data models VectorRaster

18. Conversion between data models

20. Choosing an appropriate cell size is not always simple. You must balance your application's need for spatial resolution with practical requirements for quick display, processing time, and storage.

21. Problems associated with conversion: –Loss of Detail –Loss of Accuracy –Stair Stepping (raster to vector) –Changes to the original data

22. Choosing between data models Often depends on –Type of entity or phenomena represented. – (discrete or continuous) – Available storage. – Expected types of analysis. – Expertise of human operators. – Level of accuracy desired. “Raster is faster but vector is corrector”

23. Choosing between data models Raster is useful when: –Working with continuous data types –Good for large area analyses –Good for surface analysis –Mathematical modeling –Spatial detail isn’t important Vector is useful when: –Working with discrete data types –Good for small study areas –Spatial detail is important (When “close enough” isn’t really good enough). –When topology is needed for the analysis