GEOL 50863

Course Name : Spatial Analysis

Pre-requisites : GEOL 50721 & GEOL 50762,   MATH   10043 or equivalent

Credits : 3 credit hours, 15 week course.

Class meets : Wednesdays 2-3:50 pm

Instructor : Ranjan S. Muttiah

Office : Room 221, phone: 257-6272

Office Hours :   Tues & Thurs. 2-3:30 pm

Sources for my notes and lectures:

Geostatistics for Natural Resources Evaluation by Pierre Goovaerts, Oxford University Press, 1997.

Principles of GIS by Peter Burroughs and Rachael McDonnell.

Statistics for spatial data by Noel Cressie

Isobel Clarke’s internet website (http://http://uk.geocities.com/drisobelclark/PG1979/index.htm)

Spatial autocorrelation: A Primer by Daniel Griffith

Spatial Regression analysis on the PC by Daniel Griffith

An Introduction to Applied Geostatistics, Edward Isaaks & R. M. Srivastava

Description :

This course covers the fundamentals of spatial analysis on point measurements, namely: spatial regression and spatial interpolation.   Since measurement of environmental variables in space are generally correlated, lagged spatial regression can be employed to predict relationships between variables measured on aerial units, using the auto-correlation parameter to capture spatial dependency.   Spatial interpolation provides another means of determining spatial variability of point measurements. We will primarily cover ordinary kriging, and ordinary co-kriging.   We will end with point pattern methods which are used to check for randomness of patterns in space of point measurements.

Goals & Objectives:  

To teach the students useful skills for their spatial data applications, and provide advanced training in marketable GIS skills.

Schedule:

January – May, 2005

January

Week-1: Why spatial Analysis ? Classical statistics vs. spatial statistics

Week-2: Testing of hypothesis in classical statistics

February :

Week-3:   Central Limit Theorem and its role in spatial regression

Week-4:   Tests of randomness on aerial units

              Project proposals due (graduate students only)

Week-5: Auto-correlation parameter

Week-6: Spatially lagged regression. Exam-1                                  

March

Week-7:   Spatially lagged regression, continued.

Week-8:   Introduction to interpolation methods

Week-9:   Ordinary kriging

Week-10: Ordinary kriging, continued – Exam 2

April:

Week-11: Interpretation of semi-variograms

Week-12: Co-kriging

Week-13: Co-kriging

Week-14: Point pattern processes

May:

Week-15: Point pattern processes

Important Dates:

January 18 (Tuesday), Classes begin

January 24 (Monday), Last day to withdraw with 100% tuition refund

March 9 (Wednesday), Mid-semester reports to registra

March 11 (Friday), Spring Break

March 24 (Thursday), Good Friday holiday

May 4 (Wednesday), Last day of classes

May 13 (Friday), Final Exam from 3-5:30pm

Policies :

It is the policy of TCU to have zero tolerance on cheating and plagiarism.      Attendance at all classes is required.   Quoting from the TCU student handbook:

“ Academic Misconduct (Sec. 3.4 from the Student Handbook) – Any act that violates the academic integrity of the institution is considered academic misconduct. The procedures used to resolve suspected acts of academic misconduct are available in the offices of Academic Deans and the Office of Campus Life.   Specific examples include, but are not limited to:

• Cheating: Copying from another student’s test paper, laboratory report, other report, or computer files and listings; Using, during any academic exercise, material and/or devices not authorized by the person in charge of the test; Collaborating with or seeking aid from another student during a test or laboratory without permission; Knowingly using, buying, selling, stealing, transporting, or soliciting in its entirety or in part, the contents of a test or other assignment unauthorized for release; Substituting for another student or permitting another student to substitute for oneself;
• Plagiarism: The appropriation, theft, purchase or obtaining by any means another’s work, and the unacknowledged submission or incorporation of that work as one’s own offered for credit. Appropriation includes the quoting or paraphrasing of another’s work without giving credit therefore.
• Collusion: The unauthorized collaboration with another in preparing work offered for credit.”

I encourage your active participation in class; you should feel free to ask me questions in class.    In turn, I ask that you do all your assignments, and give 110% of your effort.   You are encouraged to discuss the homework problems together.   The homework assignments however should be completed individually, and assignments should contain evidence that the student has carefully thought through the problem i.e., show evidence of independent thinking.    Home works turned in late will be assigned minus 10 points for each late day.    If you don’t understand anything that I will discuss in class, don’t hesitate to ask.   If you need additional help, schedule a visit to my office. Provide feedback to me at end or beginning of classes.   This will help you during the semester during which you are taking this course.   Evaluations at the end of the course help those who will take it later.

Grading :

Grading will be based on the following:

        Home work assignments counting for 15% of the grade

        2 exams counting at 20% each

        1 Final exam counting 25%

        Graduate student project counting for 20%

Undergraduate grades will be based on 25% for exams in lieu of student project

The following definitions will be used for grades: 90-100% will earn you an A, B will be 80- 90%, C will be 70-80%, D will be 60-70%, and 0- 60% will be assigned F.

Graduate Student Requirement : Graduate students will be required to prepare a project, write a report, and present findings to the class.   Projects will be expected to cover data dependency on location, write required computer code in ArcGIS/or other programming environments, and draw statistically defensible inferences from their data.   Undergraduate students will not be required to prepare a project.

Everything listed above is the anticipated class program.   I reserve the right to change it as necessary.

Disabilities Statement :

Texas Christian University complies with the Americans with Disabilities Act and Section 504 of the Rehabilitation Act of 1973 regarding students with disabilities.   If you require accommodations for a disability, please contact the Coordinator for Students with Disabilities in the Center for Academic Services, located in Sadler Hall 11.   Further information can be obtained from the Center for Academic Services, TCU Box 297710, Fort Worth, TX 76129, or at 817-257-7486.  

Adequate time must be allowed to arrange accommodations and accommodations are not retroactive; therefore, students should contact the Coordinator as soon as possible in the academic term for which they are seeking accommodations.   Each eligible student is responsible for presenting relevant, verifiable, professional documentation and/or assessment reports to the Coordinator.   Guidelines for documentation may be found at http://www.acs.tcu.edu/DISABILITY.HTM.

Students with emergency medical information or needing special arrangements in case a building must be evacuated should discuss this information with their instructor/professor as soon as possible.

TCU Mission Statement

To educate individuals to think and act as ethical leaders and responsible citizens in the global community