raster data model

raster data model

• 1.
  Raster Data Model
• 2.
  GIS data models Model Abstractionof 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 cellularbased 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 definesgeographic 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 Gridsize 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 aGrid 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 isplaced
• 10.
  Reality >>> Rastervalue 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 15meters 60 meters 30 meters Source: G. Bryan Bailey, U.S.Geological Survey, EROS Data Center, [email protected]
• 13.
  NODATA Cells
• 14.
  Types of Raster Basedon 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 0.60.7 Near-infrared
• 18.
  Raster Calculator Cell bycell 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 ERDASImagine 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 orpixel
• 28.
  Data
• 29.
  Data Vector
• 30.
  Data Vector Raster
• 31.
  Data Conversion Integrate otherGIS data with Remote Sensing Rasterization Vector to Raster Can only approximate original location • Pixel resolution Vectorization Raster to Vector
• 32.
  Raster Generalization: case1 Largest share rule Central point rule
• 33.
  Raster Generalization: Case2 Largest share rule Central point rule
• 34.
  Vectorization Raster to vector Morecomplex • Points • Lines • Polygons Edge enhancement Classification Vectorizing Topology need to be built