This introductory course is aimed at students who require instruction in the basic theoretic principles of digital photogrammetry and digital surface models.

Themes covered in the course include:

• Principles of digital photogrammetry
• Stereo vision and parallax
• Types of photogrammetry
• Image sourcing and acquisition
• Flight planning
• Sensor orientation and image characteristics
• Interior and exterior orientation
• Ground control and tie-point collection
• Bundle adjustment
• Least-squares adjustment and coordinate transformations
• Image processing (contrast and spectral enhancement, image matching, mosaicing);
• Topographical-map production
• GIS integration
• LIDAR technology (Light Detection and Ranging)

Including two separate four-day or three-week courses (see course structure for more detail):

1. Introduction to Spatial Analysis
2. Advanced Spatial Analysis

These two courses are aimed at students who require basic and/or advanced instruction in the theoretical principles of spatial data analysis.

Themes covered in the course include:

• Query operations and query languages
• Geometric measures
• Spatial analytical operations
• Surface analysis
• Geo-statistics
• Network analysis
• Analysis design
• Fuzzy sets

This is an intermediate course is aimed at students who require practical and theoretical instruction in the principles of spatial data acquisition, data capture and GPS.

THEMES COVERED IN THE COURSE INCLUDE:

• Spatial data types and models· Acquisition and creation of spatial data
• Digitising and scanning
• Field data collection
• Global navigation satellite systems
• Uncertainty and error
• Data quality
• Sources of GIS data and imagery
• National and international data providers and warehouses
• Metadata and standards
• Data sharing

This intermediate course is aimed at students who need instruction in the intermediate principles and techniques fundamental to spatial data management, map projections and coordinate systems.

Themes covered in the course include:

• Map projections and coordinate systems
• Spatial data models (e.g. vector, raster, tin)
• Topology
• Databases, including object-orientated
• Geo-databases
• Data model and format conversions
• Data generalisation and aggregation
• Data quality

Including two separate four-day or three-week courses (see course structure for more detail):

1. Introduction to Spatial Modelling
2. Advanced Spatial Modelling

These two courses are aimed at students who require basic and/or advanced instruction in the theoretical principles of spatial data modelling.

Themes covered in the course include:

• The concepts of models in science with specific reference to spatial models· Classification criteria (and examples) of different types of models
• Principles of model development
• The process of spatial model construction
• Application of spatial models in GIS
• Definition of cartographic modeling methodologies, input and output data, operations and standardisation
• Commonly used symbols, equations and parameters, error propagation and validation in cartographic models;
• Stages in the development of a cartographic model
• Automating GIS processes