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DRPS : Course Catalogue : School of Geosciences : Postgraduate Courses (School of GeoSciences)

Postgraduate Course: Object Orientated Software Engineering: Spatial Algorithms (PGGE11106)

Course Outline
SchoolSchool of Geosciences CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityAvailable to all students
SCQF Credits10 ECTS Credits5
SummaryThe course assumes a prior working knowledge of the Python programming language and of Object-Oriented design principles. It uses these to develop understanding of computational algorithms used to manipulate and analyse spatial data. A range of examples is used to identify and utilise generic algorithmic principles across a variety of different spatial data types and problems. Concepts of algorithm efficiency are addressed but emphasis is also placed on clarity of design and implementation. There is a strong practical emphasis to learning on the course and it is delivered through a sequence of five, four-hour workshops that allow you to iteratively learn about aspects of algorithm design and then to implement these in practice for yourself. PGGE 11042 Object-Oriented Software Engineering Principles or other equivalent experience is a pre-requisite for this course.
Course description Week by week breakdown of the course:
Week 1:
Handling Spatial Data: Simple geometric calculations, distance and bearing, range searching and data sorting.

Week 2
Divide and Conquer methods: Binary searching, Recursion, Line generalisation.

Week 3
Grid Data and Arrays. Handling, traversing and searching raster data. Point and focal functions.

Week 4
Problem solving by task partitioning. Nearest Neighbour analysis and cartogram generation examples.

Week 5
More advanced raster and vector processing. Developing flow routing algorithms. Processing raw vector data.

Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Information for Visiting Students
High Demand Course? Yes
Course Delivery Information
Academic year 2016/17, Available to all students (SV1) Quota:  None
Course Start Block 2 (Sem 1)
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 100 ( Lecture Hours 18, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 80 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) 100% coursework: practical assessment 20%; project (80%)
Feedback Not entered
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. identify how different spatial data models can be implemented in object-oriented designs.
  2. have an understanding the principles of algorithm development and of generic concepts employed in algorithm design and be familiar with a range of algorithms used to manipulate and analyse spatial data.
  3. be able to develop Python classes suited to the representation and analysis of spatial data.
  4. be able to undertake spatial data Input/Output in standard formats and to interface Python with other proprietary software.
  5. be able to complete programming and software documentation within specified parameters and to a professional standard.
Reading List
Martelli A, (2009), Python in a Nutshell, O┐Reiley
Lutz M, Learning Python(2009), O┐Reiley
Sedgewick R, and Wayne K (2011):,Algorithms 4th edition
Westra, E 2015 Python GeoSpatial Analysis essentials. Packt publishing
Additional Information
Course URL
Graduate Attributes and Skills Not entered
KeywordsPGGE11106 Algorithms,Java,object oriented design
Course organiserDr Nick Hulton
Tel: (0131 6)50 2531
Course secretaryMrs Karolina Galera
Tel: (0131 6)50 2572
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