GEO-SCI591D Spatial Data Analysis

3 cr, Spring 2008

Syllabus in Print version  (PDF)

Course Location:   Morrill III 126,  Lab in Morrill IV South 271

Lecture Time:         Tu 2:30PM - 5:15PM

Instructor:                 Dr. Qian Yu

Office:              Morrill IV South 267

Tel:                    413-545-2095

EMAIL:            qyu@geo.umass.edu

Office Hours:                 M 2:30-3:30pm   W 1:30-2:30pm or by appointment

Purpose: The course covers a broad range of spatial data analysis methods from basic statistics to advanced computational techniques. The topics include point pattern analysis, spatial prediction based on deterministic methods and Geostatistical theory, spatial autocorrelation and regression, and raster analysis. The labs are based on ArcGIS and statistical software.

The goal of this course is to introduce students various quantitative methods, particularly multivariate regression and spatial analysis, used in geographical data and applications; to teach students to understand these concepts and to be able to apply them in geographical problems.

Format: 60% lectures and class discussions, 40% class exercises including computer lab and project.  Take home exercises and lab practice will be assigned to students to get familiar with the concepts discussed in class.

Prerequisite 

- Basic statistical knowledge

- Introductory level GIS and know how to use ArcGIS

Required textbook:

 

David O'Sullivan, David J. Unwin, Geographic Information Analysis, John Wiley& Sons, Inc, Hoboken, New Jersey, ISBN: 978-0-471-21176-1, Hardcover, 448 pages, November 2002

Lab software: ArcGIS and R.

References:

Christopher D. Lloyd, Local Models for Spatial Analysis, CRC Press, 2007.

Bailey TC, Gatrell AC,  Interactive spatial data analysis. Harlow, Essex, England: Longman, 1995.

Isaaks EH, Srivastava RM, An Introduction to Applied Geostatisitics, Oxford University Press, 1989.

Course Evaluation: Assignment 35%, Class Participation 10%, Project (including presentation and report) 55%

Class schedule and reading

Available at http://www.geo.umass.edu/courses/geo591d/. It will be updated with classes progressing.

Notes and assignments in PDF will be published on the SPARK.

Notices and announcement will be published on SPARK Bulletins for update, schedule change and clarification questions

Class arrangement (Tentative)

 

	Topic	Reading
Jan 29 Lecture 1.	Concepts in spatial data and models	O'Sullivan's ch1-2
Feb 5 Lecture 2.	Point Pattern Analysis: point pattern measure and test	O'Sullivan's ch3-4
Feb 12 Lecture 3.	Point Pattern Analysis: cont, Lab 1 Point Pattern Analysis	O'Sullivan's ch 5 Gatrell, 1996
Feb 19	Monday schedule
Feb 26 Lecture 4.	Analysis of Spatial continuous data: Exploring spatial continuous data	Bailey's p155-181
Mar 4 Lecture 5.	No class
Mar 11 Lecture 6.	Analysis of Spatial continuous data: Modeling spatial continuous data, variogram and simple kriging	Bailey's p181-201
Mar 25 Lecture 7.	Analysis of Spatial continuous data: Modeling spatial continuous data, extensions of simple kriging, geospatial analyst in ArcGIS	Handout
Apr 1 Lecture 8.	Area objects and spatial autocorrelation, GLS and spatial autoregressive models Moran’s I, Geary’s C	Handout
Apr 8 Lecture 9.	Area objects and spatial autocorrelation, GLS and spatial autoregressive models Moran’s I, Geary’s C	Handout
Apr 15 Lecture 10.	No lecture, Work on assignment 3 and  final project
Apr 22 Lecture 11.	Spatial regression analysis in R
Apr 29 Lecture 12.	Linear object analysis
May 6 Lecture 13.	Projects
May 13 Lecture 14.	Projects