The document discusses raster data models in GIS. Raster data models represent geographic space as a grid of cells or pixels, with each cell storing numeric values representing attributes like elevation. Key points: - Raster models use a grid-based structure of rows and columns to store imagery and represent continuous surfaces. - Each cell holds a value like elevation and has a defined spatial resolution (size). - Raster data is used for things like satellite imagery, elevation maps, and representing variables that vary continuously over space.

1. Raster Data Model

2. GIS data models
Model
Abstraction of realworld/process/phenomenon
GIS data model
Set of constructs/rules for
describing or representing
the real world within a
computer
Two data models
Vector
Raster

3. Data Models
Raster
A cellular based data structure composed of rows
and columns for storing images. Homogenous
units are called cells or pixels.
• Mainly Used for representing continuous surface e.g.
reflectivity of EMR, elevation, rainfall, soil/landuse etc.,
Vector
A coordinate based data structure commonly used
to represent geographic features. Homogenous
units are points, lines, and polygons.
• Mostly used for representing discrete geographical
features such as building, wells, roads etc.,

4. A grid defines geographic space as a matrix of
identically-sized square cells. Each cell holds a
numeric value that measures a geographic attribute
(like elevation) for that unit of space.
Source: http://www.ce.utexas.edu/prof/maidment/class.html

5. Grid data structure
Grid size is defined by extent, spacing
and no data value information
Number of rows, number of column
Cell sizes (X and Y)
Top, left , bottom and right coordinates
Source: http://www.ce.utexas.edu/prof/maidment/class.html

6. Definition of a Grid
Cell size
Number
of
rows
NODATA cell
(X,Y)
Number of Columns
Source: http://www.ce.utexas.edu/prof/maidment/class.html

8. Somewhere on earth

9. Raster grid is placed

10. Reality >>> Raster value
The average EMR is measured within
each grid
Depending on the average intensity of
the EMR a numeric value is assigned
for each grid

11. Spatial resolution
finer
Coarser

12. Spatial Resolution Examples
15 meters
60 meters
30 meters
Source: G. Bryan Bailey, U.S.Geological Survey, EROS Data Center, gbbailey@usgs.gov

13. NODATA Cells

14. Types of Raster
Based on the data type
Integer
• Binary or Boolean (0 or 1)
• Grayscale (Signed/Un-signed, 8 bit, 16bit,
32bit)
Real (floating decimal point)
• Grayscale (32 bit, 64 bit)
Based on the number of bands
Single band
Multi-band  Remotely sensed data

15. red
green
blue
UV
0.4 0.5 0.6 0.7
Near-infrared

18. Raster Calculator
Cell by cell
evaluation of
mathematical
functions

19. Example
7
5
6
6
2
3
4
3
=
5
2
2
3
Precipitation
Losses
(Evaporation,
Infiltration)
=
Runoff

20. Raster Data Formats
TIFF – GeoTIFF
Tagged Image File Format
GIF
Graphic Interchange Format
BMP
BitMap format
JPEG
Joint Photographic Experts Group

21. Other Formats
ArcInfo GRID
ERDAS Imagine
ASCII
Binary format
Band sequential
Band Interleaved by Line
Band Interleaved by Pixel

23. Raster Vs Vector

25. Advantages
Disadvantages

27. Data
Raster
Grid cell or pixel

28. Data

29. Data
Vector

30. Data
Vector
Raster

31. Data Conversion
Integrate other GIS data with Remote
Sensing
Rasterization
Vector to Raster
Can only approximate original location
• Pixel resolution
Vectorization
Raster to Vector

32. Raster Generalization: case 1
Largest share rule
Central point rule

33. Raster Generalization: Case 2
Largest share rule
Central point rule

34. Vectorization
Raster to vector
More complex
• Points
• Lines
• Polygons
Edge enhancement
Classification
Vectorizing
Topology need to be built