Raster Vs Vector Data

Raster Vs Vector Data 

VECTOR:

Basic Elements:

1. Location (x,y) or (x,y,z)

3. Explicit, i.e. pegged to a coordinate system

4. Different coordinate system (and precision) require different values:

   •   e.g. UTM as integer (but large)

   •   Lat, long as two floating point numbers +/-

5.  Points are used to build more complex features

• Advantages of Vector Data Structures:
  • Good representation of phenomenonology
  • Compact
  • Topology can be completely described
  • Accurate graphics
  • Retrieval, updating and generalization of graphics and attributes possible

  Disadvantages of Vector Data Structures:
  • Complex Data Structures
  • Combination of several vector polygon maps through overlay creates difficulties
  • Simulation is difficult because each unit has a different topological form
  • Display and plotting can be expensive, particularly for high quality color
  • The technology is expensive, particularly for the more sophisticated software and hardware
  • Spatial analysis and filtering within polygons are impossible 

  

  VECTOR FORMATS

  1. Shapefile
       Contains:
              o Point, or multi-point
              o Line, or polyline
              o Polygon  

  2. Coverage
         Contains:
             o Point, or node                                      
             o Arc, or line
             o Polygon
             o Label

  EXAMPLES

  Administrative borders

Linear features
Roads
Rivers
Discrete habitat boundaries

RASTER

Basic Elements

1. Extent

   •     Rows

   •    Columns 

     
     

2.  Origin 

3. Orientation

4. Resolution: pixel = grain = grid cell 

5. Advantages of Raster Data Structures:

   • Simple data structures
   • Overlay and combination of maps and remote sensed images easy
   • Some spatial analysis methods simple to perform
   • Simulation easy, because cells have the same size and shape
   • Technology is cheap 

6. Disadvantages of Raster Data Structures:

   • The use of large cells to reduce data volumes means that phenomenonologically recognizable structures can be lost and there can be a serious loss of information
   • Crude raster maps are considerably less beautiful than line maps
   • Network linkages are difficult to establish
   • Projection transformations are time consuming unless special algorithms or hardware is used.

 EXAMPLES

•   Temperature (air, water)
•  Air pressure
•  Ecotones
•  Soil ph
•  Precipitation
•  Salinity
•  Elevation & its derivatives
•  Flow
•  Direction, distance
•  Reflectance (photography/imagery)