Geography 4203 GIS 2: Modeling Applications

Transcription

1 Geography 4203 GIS 2: Modeling Applications Lectures: M/W/F 11-11:50pm, Gugg 6 (KESDA) Labs: M 1-3:50 or F 8-10:50am, Gugg 6 (KESDA) Instructor: Galen Maclaurin TA: Jessie Hong galen.maclaurin@colorado.edu jung.hong@colorado.edu Office hours: T 11-12:30, W 1-2:30 or by appointment Gugg. 301b M/W/F 12-1 in KESDA or by appointment OVERVIEW: This course follows GIS 1 (Geog 4103) and builds on the skills and understanding gained in such an introductory GIS course. We will focus mostly on modeling in raster-based GIS, while using some vector data as well. The course covers the fundamental concepts of raster analysis techniques and their applications in terrain modeling and methods of spatial estimation. In doing so, the course looks at Map Algebra, iteration in GIS and spatial autocorrelation. Finally, we will discuss the phases of a GIS project design and management. We will touch on the advanced topics of spatio-temporal, uncertainty modeling and the link to automation and programming in GIS. During the last weeks of the term, students will work in small groups on a modeling project. Group leaders will propose a project in the middle of the term, and then design and implement it with their groups. PREREQUISITES: Geog 4103 or equivalent course work. It is assumed that you have working experience with ArcGIS v.9 and Windows, and have some basic experience in modeling applications. Experience from an introductory GIS class (similar to Geog 4103) should be fine. CLASS MEETINGS: Lectures will cover a series of topics given in the schedule and will be linked to the seven lab assignments. Some of the class meetings will be used for readings discussions. Towards the end of the semester, class meetings will address issues with ongoing project work and provide extra work time for groups. READINGS: Bolstad, P GIS Fundamentals. Minnesota: Eider Press. 3nd Edition. DeMers, M. N GIS Modeling in Raster. New York: Wiley. (optional) Below is a list of the additional required readings that will be used in this course. Five class meetings will be devoted to readings discussions led by students (see below). The readings for these discussions will be available in electronic form on the class homepage. Students will submit reading summaries prior to the discussions. READINGS DISCUSSIONS AND SUMMARIES: Each readings discussion will be led by a group of 4-5 students. There will be five readings discussions each with a set of two readings. Students will submit summaries for four of the five sets of readings. The set of summaries you skip is your choice. Each set will have a half page summary with 2 questions for each reading (i.e. two half page summaries and 4 questions). Students need to send me an with the top three discussions they would prefer to lead. I will assign discussion leaders in the order I receive your s (first comes, first serves time stamp of the counts!). GROUP PROJECTS: During the final weeks of the term, students will work in small groups on a chosen modeling problem. Each project will have three presentations (a proposal by the project leader, a progress report and a final presentation both given by the whole group). To become a project leader, you must have a topic/problem to propose by Sept. 27 th. The final project proposal will be due on Oct. 15 th ; at which point you must have your data in hand and in a workable format. For the project to proceed, at least one other student must choose to work with you. Project leaders will manage the project design and

2 implementation for the group with our help and guidance and will write a short report on GIS project management at the end of the semester. GRADING: Lab Exercises (7 exercises) 120 pts Readings Summaries 40 pts Class Participation 15 pts Group Project (team) 25 pts Group Project (individual) 30 pts Leading a readings discussion 20 pts Total 250 pts Project leaders will earn extra credit (up to 20 pts). ATTENDANCE: Students must attend all labs. Four points will be taken off your final grade for each missed lab. Attendance in lecture is also mandatory; students will be allowed four unexcused absences during the semester. After that, four points will be taken off your final grade for each additional absence. Exceptions require permission from the instructor prior to the absence. LATE POLICY: Lab assignments must be ed to the instructor and TA before the lab session of the next exercise. For late lab assignments, 10% will be taken off the assignment grade for each weekday they are late. This policy will also apply to the group project report. Reading summaries must be ed to the instructor by 5pm the day before the corresponding reading discussion. No late reading summaries will be accepted. SCHEDULE OF READINGS DISCUSSIONS: September 1 st Readings discussion 1: Fields and Objects Couclelis (1992) Goodchild (1989) September 17 th Readings discussion 2: Terrain Models Burrough, P.A. and McDonnell, R.A. (1998) pg Weibel and Heller (1991) September 29 th Readings discussion 3: Spatial Interpolation Mitas and Mitasova (1999) Oliver (2001) October 20 th Readings discussion 4: Spatial data quality and uncertainty Fisher (1999) Goodchild (1991) October 29 th Readings discussion 5: Spatio-temporal O Sullivan (2005) Kwan (2004)

3 TENTATIVE SCHEDULE: We will adjust the schedule as needed during the semester. Wk Date Lecture Readings Lab Exercise 1 8/23 Course introduction Bolstad 2,9; (DeMers 1,2) No lab 8/25 GIS modeling (Some) perspectives Bolstad 13; (DeMers 5) 8/27 Review on raster data, objects and fields Bolstad 2; (DeMers 3) Lab 1: Line-of-sight 2 8/30 Mathematics of raster maps & Map Algebra Bolstad 10; Tomlin 1991; (DeMers 3) 9/1 Readings discussion 1: Objects and Fields Couclelis 1992; Goodchild /3 Monday lab make-up Lab 2: 3 9/6 Labor day no class, no lab 9/8 Terrain modeling Slope and aspect Bolstad 11; (DeMers 5,7) 9/10 Terrain modeling Slope and aspect Burrough & McDonnell 1998 (pg ) 4 9/13 Hydrological functions Bolstad 11 9/15 Hydrological functions 9/17 Readings discussion 2: Terrain modeling Burrough & McDonnell 1998 (pg. Proximity Lab 3: Hydrologic ); Weibel & Heller 1991 Lab 3: continued 5 9/20 Spatial Estimation Point interpolation Bolstad 12, Burrough & McDonnell 1998 (pg ) 9/22 Spatial Estimation Point interpolation Bolstad 12, Burrough & McDonnell 1998 (pg ) 9/24 Spatial Estimation Spatial prediction Bolstad 12 Lab 4: 6 9/27 Spatial Estimation Spatial prediction Bolstad 12 Interpolation Project leader problem statements due 9/29 Readings discussion 3: Spatial Interpolation Mitas & Mitasova 1999; Oliver /1 Spatial Estimation Spatial prediction Bolstad 12 Lab 4: 7 10/4 Areal interpolation Wright 1936 continued 10/6 Dasymetric mapping Eicher & Brewer /8 Map algebra revisited Lab 5: 8 10/11 Map algebra: branching Dasymetric Modeling 10/13 Spatial data quality and uncertainty Bolstad 14 10/15 Spatial data quality and uncertainty Bolstad /18 Final project proposals due Dynamic modeling and Spatio-temporal Itami 1994 Lab 5: continued 10/20 Readings discussion 4: Spatial data quality Fisher 1999, Goodchild 1991 and uncertainty 10 10/22 10/25 Dynamic modeling and Spatio-temporal Python scripting Lab 6: Modeling time and change 10/27 Python scripting 10/29 Readings discussion 5: Spatio-temporal O Sullivan 2005; Kwan 2004 Lab 7: Python scripting 11 11/1 Python scripting 11/3 Project group selection 11/5 Project help and work time Group projects

4 12 11/8 Project help and work time Group projects 11/10 Project help and work time 11/12 Project help and work time Group projects 13 11/15 Project help and work time Group projects 11/17 Group presentations: status update 11/19 Group presentations: status update Group projects 14 11/22 11/24 11/26 Thanksgiving Break No lab 15 11/29 Project help and work time Group projects 12/1 Project help and work time 12/3 Project help and work time Group projects 16 12/6 Final presentations Final reports 12/8 Final presentations due 12/10 at 12/10 Final presentations 5pm ADDITIONAL READINGS: Available as PDFs on the course webpage. Burrough, P.A. and McDonnell, R.A Principles of Geographical Information Systems. London: Oxford. (Digital Elevation Models: pg ; Interpolation: pg and ) Couclelis, H People manipulate objects (but cultivate fields): beyond the raster-vector debate in GIS. In Theories and methods of spatio-temporal reasoning in geographic space. eds. A. U. Frank, I. Campari, and U. Formentini, Berlin: Springer Verlag. Eicher, C.L. and Brewer, C.A Dasymetric Mapping and Areal Interpolation: Implementation and Evaluation. Cartography and Geographic Information Science 28(2): Fisher P Models of uncertainty in spatial data. In: Longley, P. Goodchild, M.F., Maguire, D. and Rhind, D. (eds.) Geographical Information Systems. 2nd Edition. Vol. 1: Principles and Technical Issues: Goodchild, M.F Modeling Error in Objects and Fields. In Gopal, S. and Goodchild, M.F. (eds.) Accuracy of Spatial Databases. London: Taylor & Francis. Goodchild M F 1991 Issues of quality and uncertainty. In Muller J C (ed) Advances in Cartography. London, Elsevier: , Robinson. Itami, R.M Simulating Spatial Dynamics: Cellular Automata Theory. Landscape and Urban Planning 30: Kwan, M.P GIS Methods in Time-Geographic Research: Geocomputation and Geovisualization of Human Activity Patterns. Geografiska Annaler 86B(4): Lo, C.P. and Yeung, A. K. W GIS Implementation and Project Management. Chapter 11 in: Concepts and Techniques of GIS. New Jersey: Prentice-Hall: Mennis, J. and Hultgren, T Intelligent Dasymetric Mapping. Cartography and GIScience 33(3): Mitas, L. and Mitasova, H Spatial Interpolation. In: Longley, P. Goodchild, M.F., Maguire, D. and Rhind, D. (eds.) Geographical Information Systems. 2nd Edition. Vol. 1: Principles and Technical Issues: Oliver, M.A Determining the Spatial Scale of Variation in Environmental Properties Using the Variogram. Chapter 11 in: : Tate, N.J. and Atkinson, P.M. (eds.) Modelling Scale in Geographical Information Science. New York: John Wiley:

5 O Sullivan, D Geographical Information Science: Time Changes Everything. Progress in Human Geography 29(6): Tomlin, C.D Cartographic Modeling. In Maguire, D., Goodchild, M.F., and Rhind, D. (Eds.) Geographic Information Systems: Principles and Applications. London: Longman: Weibel, R. and Heller, M Digital Terrain Modeling. In Maguire, D., Goodchild, M.F., and Rhind, D. (Eds.) Geographic Information Systems: Principles and Applications. London: Longman: Wright, J.K A Method of Mapping Densities of Population with Cape Cod as an Example. Geographical Review 26(1): Department of Geography Code of Conduct: In the Department of Geography, instructors strive to create an atmosphere of mutual trust and respect in which learning, debate, and intellectual growth can thrive. Creating this atmosphere requires that instructors and students work to achieve a classroom in which learning is not disrupted. At the most basic level, this means that everyone attend class, be prepared with readings and assignments completed, and that students pay attention. This means no conversations with friends, reading the newspaper, coming late, or leaving early. Such behavior is disruptive to the instructor and to your fellow classmates. These basics of classroom etiquette are an important means of building and showing mutual respect. Inevitably, however, disagreements will arise. Sometimes these disagreements will be about content, sometimes about grades or course procedures, and sometimes they will be about the treatment of participants in the class. In order to facilitate the resolution of these disagreements, the following guidelines should be followed by everyone: All interactions must be guided by mutual respect and trust. If you are bothered by some aspect of the class, identify what it is that is bothering you and center the discussion on that issue. Address issues that concern you early. Problems are easier to resolve before they fester. Consider whether it is best to address your concerns in class or in a separate appointment with the instructor. Remember, behavior that disrupts your fellow classmates is not acceptable. Abusive speech or behavior will not be tolerated in any interaction between students or between student and instructor. If an instructor feels that your speech or behavior is abusive, you will be asked to leave the room. If you believe an instructor has become abusive, you may leave the room and talk with the department chairperson. Debate and discussion can continue when all parties proceed with mutual respect. If mutual respect cannot be restored, either you or the instructor may take the issue to the department chairperson or the Campus Ombuds Office. Policy on Plagiarism Plagiarism is the act of using someone else's words, pictures, ideas, or procedures without proper acknowledgement, or to present them as if they originated with you. In science and especially in academics, plagiarism is unacceptable. In an exam, for example, copying from someone else's test booklet and handing it in as if it were your own work is plagiarism. In some instances it is difficult to document whether plagiarism has occurred. In other situations, particularly learning situations, it is possible that students who do not know the protocols of academic expression can inadvertently plagiarize. In some cultures, direct use of another person's words bring great honor to the quoted person.

6 In this university, plagiarism constitutes a form of cheating, and will not be tolerated. If you are unsure whether to cite someone else's work as you work through an assignment, come talk with me about it. The Honor Code THE PLEDGE "On my honor, as a CU Boulder student, I have neither given nor received unauthorized assistance on this work." Students may be asked to include this pledge on their written assignments and tests. The full Honor Code is available for your review on line, at