Spatial Data ModelsRaster Data ModelRaster Data ModelRaster Data ModelCells - Absolute ValuesPond Branch Catchment – Control Topographic Index ExampleCells - Coded ValuesMODIS LULC In Climate DivisionsCells – Coded ValuesCell Size & ResolutionRules for Assigning Cell ValuesRaster Data Model - ObjectsRaster Data Model - PointsRaster Data Model - LinesRaster Data Model - AreasRaster and Vector Data Model ComparisonRaster Data Model - TopologyGrids and Missing DataRaster Data Model - StorageRaster Data Model – CompactionRaster Data Storage – No CompactionRaster Data Storage – Run Length EncodingRaster Data Storage - QuadtreesVector to Raster TransformationsVector Data Model - AdvantagesVector Data Model - DisadvantagesRaster Data Model - AdvantagesRaster Data Model - DisadvantagesWhich Data Model Should You Use?David Tenenbaum – GEOG 070 – UNC-CH Spring 2005Spatial Data Models• Rasteruses individual cells in a matrix, or grid, format to represent real world entities• Vectoruses coordinates to store the shape of spatial data objectsDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005Raster Data Model• In the raster data model, the primary data object is the cell or pixel• You are familiar with these if you have used a digital camera or viewed a computer monitorDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005Cell (x,y)•The raster data model represents the Earth’s surface as an array of two-dimensional grid cells, with each cell having an associated value:2542293457133539386485321Cell valueCell size = resolutioncolumnsrowsRaster Data ModelDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005Raster Data Model• Each grid cell in a raster data layer is one unit (the minimum amount of information in the raster data model)• Every cell has a value, even if it is a special value to indicate that there is “no data” or that data is “missing” at that location• The values are numbers, either:– absolute values OR– codes representing an attributeDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005Cells - Absolute Values•In this instance, the value of the cell is actually the value of the phenomenon of interest, e.g. elevation data (whether floating point or integer):David Tenenbaum – GEOG 070 – UNC-CH Spring 2005Pond Branch Catchment – ControlTopographic Index ExampleDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005Cells - Coded Values•Here, the values stored in each cell are used as substitutes for some nominal or categorical data, e.g. land cover classes:David Tenenbaum – GEOG 070 – UNC-CH Spring 2005MODIS LULC In Climate DivisionsMaryland CD6North Carolina CD3David Tenenbaum – GEOG 070 – UNC-CH Spring 2005Cells – Coded Values•The coded values can then link to one (or more) attribute tables that associate the cell values with various themes or attributes:David Tenenbaum – GEOG 070 – UNC-CH Spring 2005Cell Size & Resolution•The size of the cells in the raster data model determines the resolution at which features can be represented• The selected resolution can have an effecton how features are represented:10 m Resolution1 m Resolution5 m ResolutionDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005Rules for Assigning Cell Values•Cell values are assigned to cells accorded to some set of rules, and selecting those rules differently can also effect the representation of features:David Tenenbaum – GEOG 070 – UNC-CH Spring 2005The raster data model still represents spatial objects, but does so differently from the vector model:Geographic Primitives•Points–0 dimensional •Lines–1 dimensional•Polygons–2 dimensionalRaster Data Model - ObjectsDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005++++1 point = 1 cellWhat problem do we have here? How can we solve it?Raster Data Model - PointsDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005A line = a series of connected cells that portray length Is there a problem with this representation? Raster Data Model - LinesDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005Area = a group of connected cells that portray a shapeWhat problems could we have with this representation?Raster Data Model - AreasDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005Real World Features Raster Vector• • • “A raster model tells what occurs everywhere, while a vector model tells where every thing occurs”Raster and Vector Data Model ComparisonDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005Spatial Relations are implicit•Origin: upper left corner•Each cell has 8 neighbors•4 in cardinal directions•4 in diagonal directions•Cells are identified by their position in the grid•Location of a cell can be calculated based on its position and the cell sizecolumnsrowsX-axisY-axisorigin(2,2)(0,0)Raster Data Model - TopologyDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005Grids and Missing Data•This TVDI image has “no data” values in the black portions of the gridDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005Raster Data Model - Storage•There is a trade-off between spatial resolutionand data storage when we use the raster data model, e.g.– 60 km satellite image with 10m cell size• 6000 X 6000 = 36,000,000 cells• 1 byte of attribute value (i.e. values 0-255)• ~36 MB of disk storage!– 60 km satellite image with 100m cell size• 600 x 600 = 360,000 cells• 360 KB of data… 1% the size of the other oneDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005Raster Data Model – Compaction• Because the raster data model records a value for each and every cell in a grid, it is very storage intensive, meaning that it can use a lot of memory and disk space to represent a theme • Compaction techniques are used in conjunction with raster data to reduce the amount of required storage space to a more manageable amountDavid Tenenbaum – GEOG 070 – UNC-CH Spring 200510, 10, 10 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 00 0 0 0 1 1 1 1 0 00 0 0 0 1 1 1 1 0 00 0 1 1 1 1 1 1 0 00 0 1 1 1 1 1 1 0 00 0 1 1 1 1 1 1 0 00 0 1 1 1 1 1 1 0 00 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0max. cell valuerowscolumnsProblem: too much redundancy1110010000100000000000000001110011100111000000000000000000000011100111001110000000000111001110011100Raster Data Storage – No CompactionThis approach represents each cell individually in the file:103 valuesDavid Tenenbaum – GEOG 070 – UNC-CH Spring 200510,10,10, 100, 100, 4, 1, 4, 0,20, 4, 1, 4, 0,20, 2, 1, 6, 0,20, 2, 1, 6,