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. Once a week lab exercise, and a term long class project are important portions of the class which will really help you practice what you learned from the class.
Prerequisites: EES5033/GEO5033, or permission of instructor
Instructor:
Office Hours:Dr. Hongjie Xie , Email: hongjie.xie@utsa.edu, Tel: 210-458-5445
Department of Geological Sciences at UTSA, http://www.utsa.edu/LRSGTeaching Assistant: Eric Kouba (nty143@my.utsa.edu).
Dr. Xie: Wednesday and Thursday 3:30-5:30 pm or by appointment at room of SB 4.02.07AMr. Kouba: Friday 1-4 pm Wednesday 2-5 pm, or by appointment at SB 2.01.02 or 4.02.07, through email at nty143@my.utsa.edu
Lecture and Lab:
Lecture and Lab: Thursday 5:30-8:00 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.Grade Policy:
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.
- Quizzes will be given occasionally (no prior notice) and will be extra credits (maximum 5 pts) towards to your final grade.
- Extra credits for assigned ESE seminars: 1 pt per seminar, no more than 5 pts in total towards to your final grade.
- Final grade will be 96-100 (A+), 90-95 (A-), 86-89 (B+), 80-85 (B-), 76-79 (C+), 70-75 (C-), 66-69 (D+), 60-65 (D-), and less than 60 (F). (see a link for a comparison between plus/minus and traditional polices (link).
- March 26 is the last day to drop an individual course or withdraw from all classes and receive an automatic grade of "W".
Lab exercise:
Lab exercise will be assigned on Thursday and due right before the Thursday 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).
Term project:
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 23. You will be asked to report the progress (10%) on March 22 (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), including title, name, affiliation, abstract, introduction, study area, data and method, results and discussions, conclusions, acknowledgements, reference. Instructor will also give some topics for your reference. More details will be given in the Term Project Assignment on Feb 2. 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. You can find more university-wide information below:
Roadrunner Creed: www.utsa.edu/about/creed and Honor Code: www.utsa.edu/about/creed/honorcode.html
Tentative Schedule:
(Lecture)
Lab
(L1)Introduction, review of basic GIS (ppt) 1: geodatabase, a ESRI online class paper 1
(L2)Spatial analysis: vector data analysis (ppt) 2
(L3)
Spatial statistics (ppt)
project assignment
3 reading (1) (2)
(L4)
Network analyst (ppt) 4
(L5)Spatial analysis: raster data analysis(1) (ppt)
5 reading (e-book of spatial analyst) Feb23
(L6)
Spatial analysis: raster data analysis(2)
proposal due
6 paper 2
(L7)
Spatial interpolation and Geostatistical analysis (1) (ppt)
7: Intro to ArcGIS Geo. Analyst (Tutorial ex1,2) paper 3.
reading (e-book of geostatistical analyst)
Mar8 (L8) Spatial interpolation and Geostatistical analysis (2)
8: Intro to ArcGIS Geo. Analyst (Tutorial ex3,4,5) read kriging 1, and papers 2, 3, 4 Mar15 Spring break, no class
Mar22(L9) Geoprocessing: ModelBuilder (ppt)
project progress report
9: Building models (ESRI class) reading (materials from the FreeCrs)
(L10)
Geoprocessing: PythonBasics (ppt)
10: ESRI class reading (e-book of Python Tutorial)
(L11)
Geoprocessing: Python2 (pdf) (old ppt) 11: code. old lab 11
3D analysis (ppt)
12: ESRI class. old lab 12 reading (e-book of 3D analyst), (more) Apr19 Special talk Apr26 Student presentations (term paper due May 2), final review Student Study Day May10 Final exam (5:30-7:30pm)