UEP Advanced Geographical Information Systems (GIS)

Transcription

1 UEP Advanced Geographical Information Systems (GIS) Fall 2016 Location: GIS Lab, Tisch Library Time: Wednesday 1:30-4:00PM Instructor: Sumeeta Srinivasan, Lab Hours: Wed 10-12PM and as arranged with individual students Teaching Assistant: Sharon Ron, Prerequisites: A previous course in GIS or equivalent experience with ArcGIS or any other GIS software is required. Students will be also expected to have competence in microcomputer use and familiarity with Microsoft Windows environment 1.0 Course Objectives: The major goals are: To learn more about the theoretical basis of GIS databases and analysis To further explore topics in applied spatial analytical research and methodology The learning objectives of this course are to: Use appropriate spatial analysis methods in different contexts Create and model databases for spatial analysis projects Appraise spatial analysis in journal articles Interpret and evaluate spatial statistics in journal articles Implement an independent project that incorporates spatial analysis 2.0 Course Description: This course is intended to be students from any discipline with an interest in spatial data analysis. It explores advanced topics in Geographic Information Systems (GIS) and their applications in a specific context of interest to the students either in group or individual projects. Every week, there will be a lecture and discussion as well as laboratory exercise when students will be expected to work with a variety of spatial analysis methods including spatial statistics, geostatistics and network analysis. The lab exercise will segue into weekly assignment. The lab component will focus on the use of ArcGIS (Version 10.3) and Geoda among other software in a Windows environment. Automation using Python and Model builder will also be explored. The instructor will also provide support to students who would like to use R. 1/5

2 3.0 Grading: The final course grade will be based on: Assignment 1 2% Assignments 2-10 (best 7 scores) 35% Final project (10% paper + 20% poster + 3% abstract) 33% Presentation 15% Participation 15% 4.0 Final Project The purpose of the final project is to provide additional experience in collecting, processing and analyzing spatial data. The project can be relevant to your research interests or to your thesis/ dissertation or for a joint project or final paper in another course. Students must start thinking about project ideas early in the semester. The project should use spatial analysis software to examine the spatial implications of a research problem. By November 30 th, the student is expected to have scheduled and met the instructor for at least one discussion about their project. The final project will require a paper describing the data and a poster. The final project report is due Dec 19 th. Group projects are encouraged but the products of group work will be expected to scale-up corresponding to the number of members in the group. 5.0 Textbook Lloyd, Christopher, D. 2010, Spatial Data Analysis, Oxford University Press. The textbook is available from various booksellers both on and off-line. The book is also available as an ebook from the Tisch Library at Tufts University. 6.0 Student Responsibilities for Meeting Course Objectives 1. Obtain and read the required textbook and supplemental material. Students will be evaluated on knowledge and skills obtained from lecture, discussion, the required textbook and supplemental reading materials. 2. Be prepared for class discussions and participation. Volunteer to both discuss information and answer questions. Outcomes of this practice will be used by the instructor as a means to subjectively evaluate students at the end of the semester. 3. Follow the student honor code and ethical standards. The academic code of conduct can be accessed over the web at: 2/5

3 4. Out-of-class assignment must be professionally prepared. This means the course project and exercises will have to be legible and free of spelling errors, and poor grammar. References must be cited properly. No late assignments will be accepted under any circumstances. 5. If you need to communicate with the instructor, you may do so via , or by making a personal appointment. It may take at least one workday for the instructor to return a telephone or message. Please plan accordingly. If you need more then 5-10 minutes of the instructor s time, it may be best to schedule an appointment. 6. Please do attend office hours not only when you have questions or concerns about the material in class but also when you just need someone to brainstorm or have a conversation. 7. Be prepared to spend many hours in the lab learning to work with the software and data. 3/5

4 7.0 Course Outline and Readings Week 1 Sep 7 Lecture Course Introduction Readings: Llloyd, Ch 1-2 Laboratory Assignment Lab 0: Preliminary project abstract Week 2 Sep 14 Geodatabases Skim: support.esri.com/index.cfm?fa=downloads.datamodels.matrix Lab 1: Geodatabases Assignment 1 is due by 1PM Week 3 Sep 21 Automating Analysis: Rasters, Vectors (again) Readings: (Lesson ) Lab 2: Model Builder and Python in ArcGIS Assignment 2 is due by 1PM Week 4 Sep 28 Suitability analysis Readings: Llloyd, Ch 5 Lab 3: Model Builder for suitability analysis Assignment 3 is due by 1PM Week 5 Oct 5 Raster analysis Readings: Llloyd, Ch 10 Lab 4: DEM, cost path in ArcGIS Assignment 4 is due by 1PM Week 6 Oct 12 Network analysis Readings: Llloyd, Ch 6 Skim: www-sre.wuwien.ac.at/ersa/ersaconfs/ersa03/cdrom/papers/433.pdf Lab 5: Network Analysis in ArcGIS Assignment 5 is due by 1PM Week 7 Oct 19 Spatial Statistics Readings: Llloyd, Ch 4.8, Lab 6: Spatial statistics in Geoda Assignment 6 is due by 1PM 4/5

5 Week 8 Oct 26 Lecture Spatial Regressions Readings: Llloyd, Ch 8 Laboratory Assignment Lab 7: Spatial Regression in Geoda Assignment 7 is due by 1PM Week 9 Nov 2 Geostatistics Readings: Llloyd, Ch 9 Lab 8: Geostatistical Analysis in ArcGIS Assignment 8 is due by 1PM Week 10 Nov 9 Spatio-temporal data Readings: Delmelle et al, Methods for Space Time Analysis, 2013 Lab 9: Space Time GIS in CAST, ArcGIS and Geoda Assignment 9 is due by 1PM Week 11 Nov 16 GIS Project Discussion Assignment 10 is due by 1PM Week 11 Nov 30 GIS Project Project Abstracts are due Week 13 Dec 7 Project Presentations Week 14 Dec 14 Project help Week 15 Dec 19 Final Poster and Paper due 5/5