PREREQUISITE: This course is an advanced course using ArcGIS from ESRI. GIS510 OR GY307 OR equivalent prior experience with ArcGIS is absolutely required.
GIS 570 23114 Section 001 WWW Blackboard http://jsu.blackboard.com 3 semester hours
Professor: Dr. Miriam Helen Hill
Office: 205 Martin Hall
Office Hours: Tuesdays 10 a.m.--3 p.m. OR by appointment and through Blackboard IM, Blackboard Virtual Office Hours, or AOL IM
E-mail addresses: firstname.lastname@example.org that will go to email@example.com
Telephone: 256-782-8063 (please, contact me by e-mail)
Course Description: Modeling and Customization (3). Enhancement of the ArcGIS interface through simplification and automation using Python scripting and ModelBuilder. GIS 570 on different topics can be taken twice for credit.
Purpose of the Course: This course is to designed to build skills in using the ArcGIS interface and extensions. Python and programming logic are applied to ArcGIS scripting and modeling using the ModelBuilder extension. This class has a strong laboratory component using ArcGIS from ESRI.
Student Learning Outcomes:
The student will be able to:
David W. Allen, Getting to Know ArcGIS ModelBuilder Redlands, CA: ESRI, Press, 2011, 978-1-58948-255- 5
Tony Gaddis, Starting out with Python 2nd, Addison Wesley, 2012, 978-0-13-257637-6
Software required ArcGIS 10.x (available from professor), MS Office 2007 or 2010 or more recent, USB 2 G jump drive, headset or microphone and speakers
Class Homepage: The class homepage is at http://www.jsu.edu/depart/geography/mhill/GIStopics/index.html and is linked to Dr. Hill's webpage at http://www.jsu.edu/depart/geography/mhill/index.html. This site is mirrored at http://www.aegis.jsu.edu/mhill/index.html. The syllabus is, also, linked to the class homepage.
Mandatory Assignment: Completion of a two part post test is required. Failure to complete this will result in a 10% grade reduction.
Grading: The class will be graded on a scale of 1000 points. The twelve laboratory activities will be worth 20 points each for a total of 240 points. The fourteen review exercises will be worth 20 points each for a total of 280 points. The midterm will be worth 200 points. The final will be worth 300 points. Additional bonus points may be awarded for exceptional work and extra credit activities. Final scores: above 900 points A; 800-900 B; 700-800 C; and below 700 F. All work MUST be submitted before the DUE date. No late work will be accepted. All work must be submitted through Blackboard. Invalid data submissions will receive no credit. Failure to complete the two part posttest will result in a letter grade reduction.
Reading Assignments: Use the attached schedule to read the chapters in the texts and complete the work BEFORE the due dates as indicated. Complete the assignments in Blackboard.
Laboratory Assignments: Twelve laboratory assignments are provided in Blackboard. Carefully follow the instructions and submit the work in Blackboard BEFORE the deadlines. Late work will NOT be accepted. Pay close attention to deadlines and work ahead of the schedule.
Review Questions: Each chapter in the Python text has a set of review questions at the end that must be submitted in Blackboard BEFORE the deadline. Late assignments will count as 0.
Midterm and Final: The midterm and final examinations will have multiple parts and include a variety of question types. All course materials may be content material.
ESRI Virtual Campus Work: Some activities will use materials from the ESRI Virtual Campus. Course access codes will be provided to enable enrollment in the course without payment to ESRI. Although passing the courses without completing the work is possible, as a graduate student, you are expected to complete the exercises to gain the experience and to add the results to your portfolio. Submission of your ESRI transcript statement will be required to document course completion.
Class Membership: Class members are expected to answer and ask questions, be involved in activities, and to facilitate an educational academic atmosphere. Proper attitude and behavior are expected. At all times presence should facilitate a smooth flow of intellectual ideas, knowledge, and intelligent discussion. Failure to contribute or promote this important goal demonstrates poor professional development.
Graduate Comprehensive Examination: For those graduate students who will be taking comprehensive examinations in order to complete their degree programs, sample comprehensive examination questions are posted in Blackboard. You are advised to archive all course materials, including these questions in order to enable yourself to prepare as your "comps" approach. The Blackboard course may no longer be available. The time to begin your preparation is as you start each course.
Portfolio: Your work from this course should be retained in your professional portfolio.
Note: All materials presented in this class are done so with educational goals in mind and are not intended to cause distress of any nature. Please be aware that controversial materials, theories, exhibits, etc. will be presented in this class. If you are unwilling or unable to view these presentations in the educational light in which they are presented, then you need to reconsider your enrollment in this class.
Answers and grading will usually be succinct and to the point. No value judgment of you, your personality, character, or your intelligence is intended. Feedback is provided so that you can learn from your mistakes and improve the work that you are doing. The focus will center on what you can improve, and it is up to you not to lose sight of the accomplishments and progress that you are making. Do not get discouraged, but you must strive continually to improve your work. GIS is complex and multifaceted, and your work will contain far more things done correctly than the few things highlighted for improvement.
Citation of Sources: All sources must be properly credited. Work containing copyright violation or plagiarism will be rejected. Use Turabian format AS DEFINED by Microsoft Word 2007 (2010) for the documentation format. Entering the requested information correctly into the software with the Turabian setting will automatically generate the correctly formated information.
Academic Dishonesty: Academic dishonesty is defined to include any form of cheating or plagiarism. A discussion of the topic is set forth in the student handbook. Working and studying with classmates are beneficial and to be encouraged. Copying work is not to be confused with comparing work and discussing similarities and differences. You are responsible for both understanding answers submitted and the completion of the materials. The material in this course is important not just for your grade but also for your future profession. All of the work is open book. SafeAssign will be used to check for plagiarism. Thoroughly document your work!
Notice: This syllabus is in no way binding. All information is subject to change. Any changes made by the instructor will be announced to the class through emails or posting to the Announcements area of Blackboard.
Questions or problems: Please contact the professor. Asking questions is an extremely important part of the learning process. Be specific. Incomplete information and vague questions only expand the time it will take for you to get an adequate response. Expect that I will ask you questions to ascertain what you understand so I can begin the answer from that point.
Making Contact: When e-mailing the professor, provide detailed information. Identify yourself, the course, the level, and the specific assignment. This will facilitate a more rapid and accurate response. We will use Blackboard IM to facilitate communication. If GEM (JSU e-mail system) is not your primary e-mail, place a forward on that account, and test it to be sure that it is functional. Blackboard uses GEM for e-mail contacts.
Disabilities: According to Public Law 504 and the Americans with Disabilities Act, Jacksonville State University will provide reasonable access and appropriate accommodations for otherwise qualified disabled students. If you need such access or accommodations, please consult with Disability Support Services and your professor immediately. Where extended testing sessions are allocated, Blackboard continues to function after the original time settings are reached, and the scores and actual times used are reported. By clicking on the ! or grade, both student and faculty can view these reports and verify completion within the appropriate time limits.
Class Schedule: Use the outline provided to complete the assigned readings and assignments BEFORE the designated dates.
GIS 570 Advanced Topics in Spatial Analysis: Modeling and Customization* S16
|January 6-12||1||computers and programming functions||Gaddis 1-3|
|13-19||2||Decisions and Looping||Gaddis 4-5|
|20-26||3||Value Functions, Modules, Files, and Exceptions||Gaddis 6-7|
|27-February 2||4||Lists, Tuples, Strings, Dictionaries, and Sets||Gaddis 8-10|
|3-9||5||Classes and Inheritance||Gaddis 11-12|
|10-16||6||Recursion and GUI Programming||Gaddis 13-14|
|24-March 1||8||Scripting and ArcGIS|
|2-8||9||Model Basics||Allen 1-2|
|9-15||10||Programming with Model Tools||Allen 3-4|
|16-29||11||Multiple Inputs and Iterations||Allen 5-6|
|30-April 5||12||Model Documentation||Allen 7|
|6-12||13||Geoprocessing and Automation|
*Any major changes to this schedule will be announced. All grades are final at 11:55 p.m., Tuesday, April 19, 2016.