Based on your understanding and knowledge of basic GIS, this class will focus on some advanced GIS concepts, tools and operations including spatial analysis, spatial statistics, geostatistical analysis, 3D analysis, and geoprocessing. The emphasis in this course is on understanding the underlying principles of those tools and how to apply them to solve real world problems. A term long class project is an important portion of the class which will really help you practice what you learned from the class.
Prerequisites: EES5033, or permission of instructor
Office Hours:Dr. Hongjie Xie , Email: firstname.lastname@example.org, Tel: 210-458-5445
Department of Geological Sciences at UTSA, http://www.utsa.edu/LRSG
Monday 3:00-5:00 pm or by appointment at room of SB 2.02.16
Lecture and Lab:
Lecture and Lab: M 5:30-8:50 pm, room SB 2.01.02. Lecture in the first 1.5 - 2 hours, and lab in the rest of the time. You are required to attend all lectures and labs except you have a good excuse (you should let me know prior to the class).
Textbook:No text book required and but many materials from different sources will be assigned for reading.
The final grade for the course will be determined as below:
Lab exercises 40%
Final exam 20%
Term project 40%
- Active class participation and exceptional performance in term project will be rewarded with extra credits. However, if you miss a class without permission (prior to the class), you will loss 2 point (based on 100 points) per missing class.
- Actively participate (for those did not register the seminar class) graduate seminar recommended by the instructor, will be awarded 1 point per seminar no more than 5 points in total.
- Final grade will be 90-100 (A), 80-89 (B), 70-79 (C), 60-69 (D), and less than 60 (F).
- March 25 is the last day to drop an individual course or withdraw from all classes and receive an automatic grade of "W".
Lab exercise will be assigned on Monday and due right before the Monday class in the following week. Late exercise is unacceptable, unless you do have an good excuse. No make-up lab exercise. Email submission is unacceptable unless you have to miss the class (you should let me know in advance). All lab exercises should use MS Word or others, please no handwriting (it is difficult to read). Lab exercise is very important for you to actually understand the image processing techniques, to use image processing software package, and to solve real world problems.
A large portion (40%) of this class is a term project. You will submit a complete proposal (5%) (no less than 2 pages, double space, 12 font) with a title, student name, introduction or question statement, data and methods to be used, and expecting results on Feb 25. You will be asked to report the progress (10%) on March 24 (no less than 6 pages, double space, 12 font). All students will give a 15 minutes class presentation (10%) and a final project paper (15%) (no less than 10 pages, single space, 12 font). Instructor will also give some topics for your reference. More details will be given in the Term Project Assignment on Feb11. You are always very welcome to discuss with me about your project.
Academic dishonesty policy:
All works must be original. Plagiarizing or cheating in any form will be reported and a failing mark will be assigned.
Subject Lab Reading
Introduction, review of basic GIS (ppt) 1: geodatabase, a ESRI online class paper 1 Jan21
MLK Birthday Holiday, no class
Spatial analysis: vector data analysis (ppt) 2 Feb4
Spatial statistics (ppt) 3 reading (1) (2) (3) Feb11
Spatial analysis: raster data analysis(1) (pdf) project assignment
4 reading (e-book of spatial analyst) Feb18
Spatial analysis: raster data analysis(2)
5 paper 2
Geostatistical analysis (1) (ppt)
6: Intro to ArcGIS Geostatistical Analyst (first half)
reading (e-book of geostatistical analyst)
Geostatistical analysis (2)
7: Intro to ArcGIS Geostatistical Analyst (last half) reading kriging 1 Mar10(L8)
Geostatistical analysis (3)
papers 4, 5 Mar17
Spring break, no class
Geoprocessing: modelBuilder (ppt)
project progress report
8 reading (materials from the FreeCrs) Mar31
Geoprocessing: PythonBasics (ppt) 9 reading (e-book of Python Tutorial) Apr7
3D analysis (ppt)
10 reading (e-book of 3D analyst), (more) Apr14(L12)
Other topics paper
Apr21 Final review
Apr28 Student presentations and term paper due May5 Final