Introduction to Raster GIS data

1. Raster data
Dr. Hans van der Kwast
OpenCourseWare
ocw.unesco-ihe.org

2. Learning objectives
After this course you are able to:
• Understand what raster data is and how it can be used in
GIS

3. GIS Basics
2 common data models to
represent reality in a GIS:
• Vector
• Raster

4. Raster data
• Matrix of pixels or cells
• Rows
• Columns
• Resolution
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5. Raster data
• Resolution
• Data types:
• Integer – for discrete or
boolean (0,1) data
• Float – for continuous data
• NODATA, mv, nan
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pixel
height
width
55.5

6. Raster resolution
High resolution Low resolution

7. Raster resolution
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8. What is Remote Sensing?RS in een notendop – Opbouw van RS afbeeldingen - Gebruik van False Coilour - Opdracht
MODIS

9. What is Remote Sensing?RS in een notendop – Opbouw van RS afbeeldingen - Gebruik van False Coilour - Opdracht
ASTER

10. RS in een notendop – Opbouw van RS afbeeldingen - Gebruik van False Coilour - OpdrachtWhat is Remote Sensing?
IKONOS

11. What is Remote Sensing?RS in een notendop – Opbouw van RS afbeeldingen - Gebruik van False Coilour - Opdracht
IKONOS

12. Aerial Photograph

13. Why raster data?
• Rasters can represent
continuous information
better than vectors, e.g.:
• Gradients in vegetation
cover
• Elevation
Can you name a few more?
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14. Raster types
• Discrete rasters: integer values representing classes
• E.g. Land-use map, soil map
• Continuous rasters: real values representing features
without sharp borders
• E.g. DEM, temperature map, soil moisture map, runoff map
• Boolean rasters: 1 or 0, representing true or false
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15. Single band rasters
Monochromatic image Gray scale image Color image
Colormap file

16. Consist of several single band rasters.
Each band relates to a range
in the electromagnetic
spectrum collected by a sensor.
Electromagnetic spectrum
Bands are commonly displayed as red
green and blue composits (RGB).
Multi-band rasters

17. Continuous raster data - examples
• Remote sensing data
• Digital Elevation Models
(DEMs)
• Interpolated point data
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18. Discrete raster data - examples
• Land-use map
• Source: CORINE 2000
• Soil map
• Source JRC
• Boolean maps
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19. Vector versus Raster
• Raster data is computationally less expensive to render than vector graphics
• Transparency and aliasing problems when overlaying raster data
• Vector data allows for visually smooth and easy implementation of overlay operations
• Vector data can be easier to register, scale, and re-project
• Vector data is more compatible with relational database environments, where they can
be part of a relational table as a normal column and processed using a multitude of
operators.
• Vector file sizes are usually smaller than raster data, which can be tens, hundreds or
more times larger than vector data
• Vector data is simpler to update and maintain, whereas a raster image will have to be
completely reproduced.
• Vector data allows much more analysis capability, especially for "networks" such as
roads, power, rail, telecommunications, etc.
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