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GIS fundamentals - raster

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Introduction to Raster GIS data

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GIS fundamentals - raster

  1. 1. Raster data Dr. Hans van der Kwast OpenCourseWare ocw.unesco-ihe.org
  2. 2. Learning objectives After this course you are able to: • Understand what raster data is and how it can be used in GIS
  3. 3. GIS Basics 2 common data models to represent reality in a GIS: • Vector • Raster
  4. 4. Raster data • Matrix of pixels or cells • Rows • Columns • Resolution 4
  5. 5. Raster data • Resolution • Data types: • Integer – for discrete or boolean (0,1) data • Float – for continuous data • NODATA, mv, nan 5 pixel height width 55.5
  6. 6. Raster resolution High resolution Low resolution
  7. 7. Raster resolution 7
  8. 8. What is Remote Sensing?RS in een notendop – Opbouw van RS afbeeldingen - Gebruik van False Coilour - Opdracht MODIS
  9. 9. What is Remote Sensing?RS in een notendop – Opbouw van RS afbeeldingen - Gebruik van False Coilour - Opdracht ASTER
  10. 10. RS in een notendop – Opbouw van RS afbeeldingen - Gebruik van False Coilour - OpdrachtWhat is Remote Sensing? IKONOS
  11. 11. What is Remote Sensing?RS in een notendop – Opbouw van RS afbeeldingen - Gebruik van False Coilour - Opdracht IKONOS
  12. 12. Aerial Photograph
  13. 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? 13
  14. 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 14
  15. 15. Single band rasters Monochromatic image Gray scale image Color image Colormap file
  16. 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. 17. Continuous raster data - examples • Remote sensing data • Digital Elevation Models (DEMs) • Interpolated point data 17
  18. 18. Discrete raster data - examples • Land-use map • Source: CORINE 2000 • Soil map • Source JRC • Boolean maps 18
  19. 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. 19

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