Algorithms in GIS and Remote Sensing

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Abstract

In this subject students learn the advanced mathematical knowledge and skills required to analyse and develop mathematical algorithms for GIS and Remote Sensing. This includes developing a good understanding of mathematical concepts required for the development of GIS-related algorithms, developing skills in solving linear algebra problems, having an ability to analyse, modify and design various GIS algorithms.Students also learn important mathematical concepts and algorithms commonly used in processing of multispectral remote sensed imagery. This includes understanding the sources and characteristics of remote sensed data and the geometric and radiometric corrections to remote sensed imagery. Students who complete this subject will have advanced knowledge and skills in constructing and implementing spatial algorithms.

Syllabus

Concepts of space as applied to GIS and remote sensing; Matrix operations; Vectors in Euclidean space; Geometric algorithms used in GIS and remote sensing; Radiometric and geometric image enhancement techniques; Line simplification, smoothing and interpolation; andRemote sensing classification techniques.

Assumed knowledge

GIS knowledge equivalent to SPA431 or SPA215 and remote sensing knowledge equivalent to SPA441 or SPA217.

Enrolment restrictions

Incompatible

Learning resources

Additional resources required by students

Students are responsible for all associated travel and resources (if applicable). Programming software (R) and spatial information software (ArcGIS) is used in this subject. R can be downloaded for free, ArcGIS is supplied.