Geoscience Data Analysis and Modeling

Course instructor: Harmon D. Maher Jr.

GE0L 2300 - T, Th 1:00-2:15 PM, DSC 290

Course intent: The objective of this course is to provide students with basic data analysis, quantitative and computer skills increasingly necessary to succeed in geoscience careers, and in many other career paths. Similar courses at other institutes are commonly taught as an upper division course, but it also makes sense to acquire these skills early and build on them in subsequent geology courses, which is the approach taken here. Some of the software you will be introduced to includes Adobe Illustrator and Photoshop, ArcGIS, Excel, Surfer, and Visual Basic for Applications. In addition, the course should familiarize the student with department and university analytic resources, and with a variety data sources available on the web. As an important byproduct students will also learn a fair bit of geoscience, as the focus is on working on geoscience problems.

Specific topics covered include: describing and comparing sample populations, simple data manipulations, data visualization, creating and working with databases, surface contouring and modeling, fractal geometries and distributions, exponential behavior, basic GIS principles, analysis of remotely sensed data, graphic data representation, and simple computer modeling of geologic processes. If these topics are unfamiliar to you, that is to be expected. In all cases examples and exercises will involve geoscience data, but geoscience provides a large umbrella. For many exercises you can chose to work with data that matches your more specific interests.

Science has changed immensely in the last two decades. Before data and information was primarily in hard copy, assembling it took significant effort, and it was helpful to have as much in your head as possible. Now, so much is easily found and available with the web and the great variety of search engines and large public data bases that the focus has shifted to the sifting through and analysis of all that information; in other words the challenge is often in how to create knowledge out of all that data. It is developing these analytic skills that this course focuses on.

Student audience: The intended student audience consists of geology, geography and environmental science majors who are in the first or second year of their program. They should have successfully completed at least one introductory course in geoscience. Students minoring in these areas may also want to take this course, as may education majors obtaining endorsements in earth or natural science.

Prerequisite: The prerequisite is one course in earth science of some sort. This could be one of the following: GEOL1010, GEOL 1100, GEOL1170, GEOG1030, GEOG1060, or GEOG1070. Other courses that give the student a background in physical earth science would be acceptable on a case by case basis. Please do not hesitate to talk to the instructor if you have a question in this regard.

Texts: There is not an appropriate text to assign for this course, and instead the material available at this website will be your text. Readings from a variety of sources will also be assigned. Two good reference books that are suggested for the course and for future geoscience work are:

Grading: There will be a total of 150 points possible, 10 for each of the 14 weeks of exercise, and 10 points for the final (which will be a multiple choice exam). The grade bins are as follows:

Late assignments will be taken, but with a 1 point penalty if less than a week late and a 2 point penalty if more. All late assignments need to be in by Friday, noon, of deadweek (the week before finals).

While you are encouraged to help each other, the final product must clearly reflect your own work and understanding. The penalty for cheating will be failure for the course, and the stigma associated with cheating. It just isn't worth it, and it isn't necessary, especially in this course. If you have a question about what might constitute cheating please ask me.

Clearly the majority of your effort should go into the weekly assignments. When group work is involved, based on peer evaluation, and with instructor input, students will be awarded points for the degree they constructively contributed to the group's effort.

The course content at this website will be continually updated throughout the semester as part of a continuous improvement process.

Back your work up on a regular basis, and keep copies of all your work! The computer lab may be reimaged at any time, and anything saved on these machines will be lost.

Course content

Week 1: Introduction to course:

Week 2: Identifying , describing and comparing populations:

Week 3: Classical linear and curvilinear regression:

Week 4: Analysis of fractal geometries in the geosciences:

Week 5: Surface analysis and modeling:

Week 6: Computer aided map construction:

Week 7: Analysis of imagery:

Week 8: Geoscience databases:

Week 9: Complex systems, multiple data sets and Geographic Information Science:

Week 10: Modeling with exponential and power law functions (see Vacher 2000):

Week 11 & 12 : Computer modeling of earth processes - Visual Basic for Applications in Excel, and Stella.

Week 13: Temporal spectral analysis:

Week 14: Classification of data using fuzzy logic:

Week 15: Wrap up.

Computer lab facilities available and associated policies

We are very fortunate to have a relatively newly outfitted computer lab in (DSC room 290), which is where we will spend much of our time. However, it is beneficial to learn to use and migrate between different platforms, different operating systems, and different software versions, which is more and more the practice in the real world. One frustration in courses like this is when the computer or program doesn't work right or just as expected, or you have hit a roadblock. The key is to get help!

Remember to log out when you are finished. Use the machines in DSC 290 only for course work. Do not have drinks or food within spill reach of the computers.

Also, I am always interested in feedback on the course. Please let me know whatever is unclear to you (i.e. you are highly encouraged to ask questions). Thank you.

Survey of student backgrounds.

Last updated 8/17/2010. Copyright by Harmon D. Maher Jr.. This material may be used for non-profit educational purposes if proper attribution is given. Otherwise please contact Harmon D. Maher Jr.