Summary Introduction Geo-
Information Science
Geo-Information Science
Lecture One: Introduction geo-information science
Geo information: Information connected to a location on earth.
Geo-information Science: the discipline dedicated to capture, storage, analysis, presentation,
exchange and use of geographical/geospatial data.
Geo-data is at the basis of mapping and measurement, monitoring, modelling and management.
Lecture Two: From real world into geo-data 1
Describing reality: Thematic description (what), Geometrical description (where), Temporal
description (when), who.
Earth
Database and Spatial perception
application by files Depends on the person and the goal:
and programs -
-
Knowledge
Research goal
- Purpose
- Users
- …
Things that are important with
respect to definition, level of detail
and scales
Data structure Spatial
geometric/thematic representation by
by a data model an information
model
Discrete phenomena:
- Thematic
- Categorical
- Discontinuous
- Objects. Boundary determines value.
Continuous phenomena: function of the location. Fields. Location determines value.
Representing continuous fields:
- Regular spaced sample points
- Irregular set of sample points
, - Regular shaped cells
- Triangular networks (TIN)
- Isolines
Tangible phenomena: can be seen in the real world.
Virtual phenomena: cannot be seen in the real world.
Vector: Objects in the vector data model:
- Point
o 0 dimensions
o Only location
- Line (polyline)
o 1 dimension
o Location, length, shape
- Area (polygon)
o 2 dimensions
o Location, length, area, shape
Raster: Objects in the raster data model:
- Cell
- Raster
- Point: singe cell
- Line: sequence of neighbouring cells
- Area: collection of contiguous cells
- Clusters of contiguous raster cells with the same value are called a region. All regions
with the same value make up a zone.
Lecture Three: From real world into geo-data 2
Geometry:
- Location and orientation
o Coordinate system
o Coordinates
o Units
- Shape and size (dimension)
- Topology
o About the spatial relationship/ configuration between objects and/ or between
primitives of the geometry representation.
o Relative location of spatial objects.
o Invariant for coordinate transformation
Attributes properties:
A table consists Attributes which have a measurement scale (nominal, ordinal, interval, ratio), an
attribute domain a data type and relations with other attributes.
Relational data model: A collection of tables, which can be related to each other by key attributes
whose values can uniquely identify a record in a table.
, ‘Integer’ raster:
- Nominal, ordinal
- Value attribute table (VAT)
‘Floating point’ raster:
- Interval, ratio
- No value attribute table
Lecture Four: Geodata acquisition
What data is needed?
- Data framework
o Administrative units
o Land cover/use
o Field survey
How to get these data? HHI
- Harvesting data by the web
o Spatial data infrastructure
o Metadata
o Portals/ registry/ clearinghouses
o Spatial Data Infrastructure (SDI)
A coordinated series of agreements on standards. Policies and technologies
to support the efficient use of geo-data. It is about facilitation and
coordination of the finding, exchange and sharing of geo-data.
- Handling (desktop creating data strategies)
o Using data which is not immediately useful
o Digitizing/scanning of hardcover maps
o Digital editing to create geo-data
o Remote sensed Data Classification
o Derive orthogonal data by Photogrammetry: to retrieve orthogonal geodata by
using overlapping (stereo-pairs) photo’/ images/ footage.
- In situ (field measuring strategies)
Clinton’s Geo-data initiative: “Coordinating Geographic Data Acquisition and Access: The National
Spatial Data Infrastructure”. Standardized documentation of data.
INSPIRE Directive (2007-2019): EU spatial data infrastructure.
Webservices: 3-tier architecture:
1. Presentation tier: Access of webservices
2. Application tier: Interoperability of webservices
3. Data tier: Servers with Data and Metadata
WCS: Web Coverage Service (raster): web-based retrieval of raster data.
Information Science
Geo-Information Science
Lecture One: Introduction geo-information science
Geo information: Information connected to a location on earth.
Geo-information Science: the discipline dedicated to capture, storage, analysis, presentation,
exchange and use of geographical/geospatial data.
Geo-data is at the basis of mapping and measurement, monitoring, modelling and management.
Lecture Two: From real world into geo-data 1
Describing reality: Thematic description (what), Geometrical description (where), Temporal
description (when), who.
Earth
Database and Spatial perception
application by files Depends on the person and the goal:
and programs -
-
Knowledge
Research goal
- Purpose
- Users
- …
Things that are important with
respect to definition, level of detail
and scales
Data structure Spatial
geometric/thematic representation by
by a data model an information
model
Discrete phenomena:
- Thematic
- Categorical
- Discontinuous
- Objects. Boundary determines value.
Continuous phenomena: function of the location. Fields. Location determines value.
Representing continuous fields:
- Regular spaced sample points
- Irregular set of sample points
, - Regular shaped cells
- Triangular networks (TIN)
- Isolines
Tangible phenomena: can be seen in the real world.
Virtual phenomena: cannot be seen in the real world.
Vector: Objects in the vector data model:
- Point
o 0 dimensions
o Only location
- Line (polyline)
o 1 dimension
o Location, length, shape
- Area (polygon)
o 2 dimensions
o Location, length, area, shape
Raster: Objects in the raster data model:
- Cell
- Raster
- Point: singe cell
- Line: sequence of neighbouring cells
- Area: collection of contiguous cells
- Clusters of contiguous raster cells with the same value are called a region. All regions
with the same value make up a zone.
Lecture Three: From real world into geo-data 2
Geometry:
- Location and orientation
o Coordinate system
o Coordinates
o Units
- Shape and size (dimension)
- Topology
o About the spatial relationship/ configuration between objects and/ or between
primitives of the geometry representation.
o Relative location of spatial objects.
o Invariant for coordinate transformation
Attributes properties:
A table consists Attributes which have a measurement scale (nominal, ordinal, interval, ratio), an
attribute domain a data type and relations with other attributes.
Relational data model: A collection of tables, which can be related to each other by key attributes
whose values can uniquely identify a record in a table.
, ‘Integer’ raster:
- Nominal, ordinal
- Value attribute table (VAT)
‘Floating point’ raster:
- Interval, ratio
- No value attribute table
Lecture Four: Geodata acquisition
What data is needed?
- Data framework
o Administrative units
o Land cover/use
o Field survey
How to get these data? HHI
- Harvesting data by the web
o Spatial data infrastructure
o Metadata
o Portals/ registry/ clearinghouses
o Spatial Data Infrastructure (SDI)
A coordinated series of agreements on standards. Policies and technologies
to support the efficient use of geo-data. It is about facilitation and
coordination of the finding, exchange and sharing of geo-data.
- Handling (desktop creating data strategies)
o Using data which is not immediately useful
o Digitizing/scanning of hardcover maps
o Digital editing to create geo-data
o Remote sensed Data Classification
o Derive orthogonal data by Photogrammetry: to retrieve orthogonal geodata by
using overlapping (stereo-pairs) photo’/ images/ footage.
- In situ (field measuring strategies)
Clinton’s Geo-data initiative: “Coordinating Geographic Data Acquisition and Access: The National
Spatial Data Infrastructure”. Standardized documentation of data.
INSPIRE Directive (2007-2019): EU spatial data infrastructure.
Webservices: 3-tier architecture:
1. Presentation tier: Access of webservices
2. Application tier: Interoperability of webservices
3. Data tier: Servers with Data and Metadata
WCS: Web Coverage Service (raster): web-based retrieval of raster data.
