SPATIAL ANALYSIS

STA4SA

Not currently offered

Credit points: 15

Subject outline

The subject surveys the theory of random fields, spatial processes, spatial statistics models, and their applications to a wide range of areas, including image analysis and GIS (geographic information system). The subject will cover the methodology and modern developments for spatial-temporal modelling, estimation and prediction, and spectral analysis of spatial processes. All the methods presented will be introduced in the context of specific datasets with GRASS and R software.

School: Engineering and Mathematical Sciences (Pre 2022)

Credit points: 15

Subject Co-ordinator: Andriy Olenko

Available to Study Abroad/Exchange Students: Yes

Subject year level: Year Level 4 - UG/Hons/1st Yr PG

Available as Elective: No

Learning Activities: N/A

Capstone subject: No

Subject particulars

Subject rules

Prerequisites: STA3AS or STA4AS and (STA3SI or STM3SI) or (STA4SI or STM4SI) or enrolment into SMDS

Co-requisites: N/A

Incompatible subjects: N/A

Equivalent subjects: N/A

Quota Management Strategy: N/A

Quota-conditions or rules: N/A

Special conditions: A sufficient background in probability and statistics is required to undertake this subject.

Minimum credit point requirement: N/A

Assumed knowledge: N/A

Learning resources

Applied spatial analysis with R

Resource Type: Book

Resource Requirement: Recommended

Author: Bivand, R.S., Pebesma, E. J., Gomez-Rubio, V.

Year: 2008

Edition/Volume: N/A

Publisher: SPRINGER.

ISBN: N/A

Chapter/article title: N/A

Chapter/issue: N/A

URL: N/A

Other description: N/A

Source location: N/A

Statistics for spatial data

Resource Type: Book

Resource Requirement: Recommended

Author: Cressie, N.A.C

Year: 1993

Edition/Volume: N/A

Publisher: WILEY

ISBN: N/A

Chapter/article title: N/A

Chapter/issue: N/A

URL: N/A

Other description: N/A

Source location: N/A

Analysing spatial point patterns in R.

Resource Type: Book

Resource Requirement: Recommended

Author: Baddeley, A.

Year: 2008

Edition/Volume: N/A

Publisher: WORKSHOP NOTES, VERSION 3.

ISBN: N/A

Chapter/article title: N/A

Chapter/issue: N/A

URL: N/A

Other description: N/A

Source location: N/A

Career Ready

Career-focused: No

Work-based learning: No

Self sourced or Uni sourced: N/A

Entire subject or partial subject: N/A

Total hours/days required: N/A

Location of WBL activity (region): N/A

WBL addtional requirements: N/A

Graduate capabilities & intended learning outcomes

Graduate Capabilities

Intended Learning Outcomes

01. Formulate purposeful questions to explore new statistical ideas and subsequently design valid statistical experiments.
02. Present clear, well structured proofs of important theoretical statistical model results.
03. Creatively find solutions to real world problems consistent with those commonly faced by practicing statisticians.
04. Professionally defend or question the validity of existing statistical analyses and associated evidence-based conclusions that are derived via application of sound spatial statistical methodology.
Subject not currently offered - Subject options not available.