Digital geographic data
• are numerical representations that describe real-world features and phenomena
• must be in digitial form and organized as a geographic database for use in a GIS
• are dynamic, in contrast to the static data displayed on a conventional map (i.e., paper)
Geographic matrix*
• geographic data described according to location (columns) and attributes (rows)
• it facilitates areal differentiation, the study of differences among various locations
see figure 3.1
*(Berry, 1964)
Real world data exist as:
Objects - buildings, highways, cities
Phenomena - terrain, temperature, ethnicity
An object:
• Has identifiable boundaries or spatial extent
• Is relevant to some intended application
• Is describable by one of more attributes (characteristics)
• Exact objects - are generally man-made features with
precise boundaries
• Inexact objects - are generally natural features with
transitional, or “fuzzy” boundaries
Spatial phenomena
are real-world features that vary continuously over space with no obvious or specific extent and are represented as surfaces
the surfaces in a field-based model can be conceptualized as being composed of:
• Grid cells or pixels– regular tessellations
• Polygons (i.e., triangles)– irregular tessellations
Representation of spatial relationships ?
• Geometric - when adjacent features share common boundary
• Proximal - when one feature is “close” to another one
see Figures 3.5 and 3.6
Logical organization
focuses upon data classification and geocoding
Physical organization
focused upon the way in which the data are stored in the computer’s memory
Levels of data measurement
• Nominal grouped by category• Ordinal rank-order• Interval numerical values• Ratio numerical values with a
true origin (absolute zero)
Data classification schemes
Descriptive names – identifying classes and subclasses– may be based upon form or function
(“high-rise” vs commercial”)
Definitions – descriptions of classes and subclasses
Data classification schemes
• example see Figure 3.8
• Criteria see page 70
(Rhind and Hudson, 1980)
Geographic data precision
• Computer numbers are discrete, whereas real world values are continuous
• When the original data contain more precise measurements than those supported by the computer, rounding occurs and precision is reduced
• GIS coordinates are normally stored as floating-point numbers (real numbers) in double-precision mode to minimize the impact of rounding during data processing.
Database organization
attribute (stored field) = one data item
record (tuple) = group of related items
data file = collection related records
ASCII files (alphanumeric)Binary files (0 and 1)
Raster geographic data representation
• Is best employed to represent geographic phenomena that are continuous over a large area
• use tessellations to model a surface
tessellations
are geometric arrangements (triangular, square, or hexagonal) of figures that completely cover a flat surface
note the need for map projection!
reasons for the popularity of raster data format:
• compatibility with different types of hardware devices for data capture and output
• compatibility with bit-mapped images
• compatibility with grid-oriented coordinate systems (i.e., plane rectangular )
Nature and characterisitics of Raster data
• Geographic data is subdivided into grid cells
• Linear dimension of each pixel defines the spatial resolution
• Grid size should be one-half the minimum mapping unit (smallest object to be represented)
• One value (character, integer, or floating-point number) assigned to each grid cell
• These values can be used for computations (like interpolation of contours) or as codes linked to a look-up table or color palette
Map layers
• In a raster database, each individual attribute (characteristic) is stored in a separate file
• thus data processing requires the use of multiple map layers
downside
• Identities of individual spatial objects are lost in a raster data model
upside
• Since the data is stored in a linear array and the dimensions of database (rows and columns) is know, there is no need to store the coordinates of the cells in the data file
WARNING!!!
You must know the raster data format and data compression algroithm used to construct the files that you are using for a particular project.
Principles of raster data compression
• Raster data files tend to be quite large, requiring large amounts of storage space and making data transmission problematic