Transcript GIS DATA STRUCTURES

PROCESS IN DATA SYSTEMS
USER
NEEDS
PLANNING
DATA
INPUT
ACTIVITIES
DATA
STORAGE
DATA
OUTPUT
DATA
ANALYSIS
DATA STRUCTURES
Non spatial
 Finance
 Library
 Communication
 Transportation
Spatial
 earth
 coordinates
DATA STRUCTURES
NON SPATIAL
 Management
Information System
 Decision Support System
 Office Otomation
System
 Artificial Inteligent
System
SPATIAL
 Environmental Info
Systems
 Infrastructural Info
Systems
 Cadastral Info Systems
 Social-economic Info
Systems
GIS DATA STRUCTURES



traditional computer file structures that allow for the
storing, ordering and searching of pieces of data
higher level of organisation in the computer called data
base structures allow more complex methods of
managing data
GIS: graphic data structure, multiple graphic data layers
and their databases
SPATIAL DATA




POINTS
LINES
AREAS
can be represented by their respective symbols
SURFACES
most often represented either by point elevations or
other computer structures,
POINT FEATURES



Trees, houses, road intersections, and many more.
Each feature is said to be discrete in that it can occupy
only a given point in space at any time.
These objects are assumed to have no spatial
dimension. Each can be referenced by its locational
coordinates
LINEAR (LINE) FEATURES



They are conceptualized as occupying only a
single dimension in our coordinate space.
Roads, rivers, regional boundaries, fences,
hedgerows, or any kind of object that is
fundamentally long and very skinny.
Other lines such as political boundaries, have no
width dimension to be concerned about. In fact
they are not physical entities at all, but rather, a
construct of political convention and
agreement.
LINEAR (LINE) FEATURES



They allow us to measure their spatial extent by simply
finding out how long they are.
Two points, a beginning and an ending point.
The more complex the line, the more points we will
need to indicate exactly where it is located.
AREAS


Objects observed closely enough to be clearly seen to
occupy both length and width are called areas.
Two-dimensional objects include the area occupied by a
yard, the areal extent of a city, and an area as large as a
continent.
SURFACES



Adding the dimension of height to our area features
allows us to observe and record the existence of
surfaces.
Surfaces occur all around us as natural features. Hills,
valleys, ridges, cliffs.
Continuous data
SPATIAL MEASUREMENT LEVELS



Objects themselves are called entities (coordinates)
Spatial features or entities also have additional
information besides spatial information
The additional non-spatial information that helps us
describe the objects we observe in space comprises the
feature’s attributes
GEOGRAPHIC DATA MEASUREMENTS


Range from simply naming objects, to give ourselves
something to call them, to precise measurements that
allow us to directly compare the qualities of different
objects.
Nominal Scale: Named data, no comparison
GEOGRAPHIC DATA MEASUREMENTS



Ordinal Scale: From best to worst. The spectrum is
based entirely on what we intended to use the
information for.
Interval scale: Numbers are assigned to the items
measured.
Ratio scale: Most useful, level of data measurement.
Allows us to make a direct comparison between two
spatial variables.
SPATIAL LOCATION AND REFERENCES


Absolute location: It will give us definitive, measurable,
fixed point in space.But we must have a reference
system against which to evaluate such a location.
Spherical grid system, places two sets of imaginary lines
around the earth
SPATIAL LOCATION AND REFERENCES
Parallels
The angular distance-latitude
 Meridians
The angular distance-longitude

GRAPHIC DATA
RASTER
 raster
 grid cells
 resolution
 dots or pixel
 coverage
 grid,
 compact storing of raster
data
VECTOR
 X and Y coordinates
 representative of
dimensionality
 simple network
 topology
 Polygon
 direct translation of the
graphic
 topologically coded network
and polygon
NON GRAPHIC DATA

SIMPLE LIST

Simplest file structure is called simple list.
Our names, addresses like creating a separate index card
for each name (unordered)
Searching is very inefficient (Suppose your database
contains 200000 records)


ORDERED SEQUENTIAL FILES


The sequence of alphabetical characters.
Names and addresses in ordered files.
INDEXED FILES



It can be developed as direct files or inverted files
Key attribute say a number sequence or alphabetic
sequence. Search was based on the key attributes
‘yellow pages’
Attributes are the primary search criteria and the
entities rely on them for selection. We call this an
indexed inverted file structure
DATABASE




A collection of multiple files is called database. The
complexity of working with database system requires a
more elaborate structure for management called data
base management system.
Hierarchical data structures
network system
relational database structure
HIERARCHICAL DATA STRUCTURE



Parent-to child branching
classifying plants and animals
A major advantages of this system is that it is easy to
search because the structure is so well defined and easy
to expand
NETWORK SYSTEMS


This structure allows users to move from data item to
data item through a series of pointers
network systems are generally considered to be an
improvement over hierarchical structures for GIS work
because they are less rigid and can handle many to
many reletionships
RELATIONAL DATABASE
MANAGEMENT SYSTEM





The data are stored as ordered records or rows of
attribute values called tuples
Tubles are grouped with data rows in aform collectively
called relations
primary key
relational join
graphic representation of entities and attributes