Spring 2024 UMass
Department of Geosciences
GEO-SCI
468/668: GIS and Spatial Analysis 3 cr
Schedule
TuTh 10-11:15
In person Classroom Lectures in 129 Morrill III and Labs in 212 Morrill
III
Instructor Prof. Qian Yu, qyu@umass.edu, Office hour Tues 1-2 Th 11:30-12:30 or by appointment
TA Hutch Tyree, qtyree@umass.edu, Office hour Mon 2:30-3:30 Wed 12:30-1:30 or by appointment
Objectives
This is an upper-level GIS course for students
to obtain intermediate to advanced GIS skills to solve science and application
problems. Extended from Introductory
GIS, the course focuses on vector- and raster- based GIS techniques and spatial
analysis. In addition, we will introduce spatial statistics and geostatistical
principles and tools. Upon the completion of this course, students are expected
to be able to:
•
Conduct geospatial analysis (vector and raster)
•
Design and create models
•
Understand and use common spatial statistics tools
•
Interpret and evaluate the outcomes of GIS
analysis in wider research contexts
•
Improve writing and presenting skills for
describing technical specifications
Prerequisite
•
Introductory GIS (NRC585 or GEOG585),
•
Familiar with computer,
MS Word.
•
High school Algebra II and Geometry, including
Trigonometry.
Required textbooks
1. GIS Fundamentals: A First Text on Geographic Information Systems, 7th
edition, Paul Bolstad, Eider Press, White Bear Lake, MN.
https://www.gisfundamentals.org/ ($44 Print, $24/$18 digital lifetime/rental)
2. The lab book includes the selected chapters from Mastering ArcGIS Pro
(2nd edition). Order either print copy or digital copy from McGraw
Hill Create following the URL posted in Canvas. We will need the book in the 2nd
week, so please order ASAP.
Suggested order information is posted on CanvasàSyllabus
Reference textbook
3.
Mastering ArcGIS Pro, 2nd
edition, Maribeth Price, McGraw Hill Higher Education.
4.
Concepts and Techniques of Geographic
Information Systems, 2/E, Chor Pang Lo, Albert K.W. Yeung (2007)
5.
Introduction to Geographic
Information Systems, K. Chang, McGraw Hill
6. Interactive Spatial Data Analysis, T.C. Bailey and A.C. Gatrell,
Prentice Hall, 1995.
7. David O'Sullivan, David J. Unwin, Geographic
Information Analysis, Wiley, Inc, Hoboken, New Jersey, ISBN:
978-0-470-28857-3, 2nd ed, Hardcover, 432 pages, March 2010.
Course Structure and
Expectations
· Course Structure The courses are
composed of topics. Each topic will be introduced by lecture, in-class
exercise, and lab assignments. Students will be asked to bring their own laptop
or tablet to class to work on pop quizzes.
· Lab We will use ArcGIS Pro for labs. Besides class
time, students are also expected to use extra time to complete weekly
assignments and submit on time.
· Final Project All students are
required to complete a final project in small groups. You are encouraged to
define the objective of your project, collect all necessary data, and perform
spatial analysis. A final report is due on the last day of final
exam.
·
Estimate of student
workload and time commitment The
weekly lectures and in-class exercise will require 2.5 hours. The weekly
readings will require at least 1.5 hours. The weekly effort on the homework/lab
assignments is at least 2 hours. The weekly workload for the final project will
vary throughout the semester from 0 hours at the beginning of the semester to 4
hours per week near the end.
How to run ArcGIS Pro
using your own computer
·
A MS Windows computer is required
to install ArcGIS Pro with internet connection. A handout about license
requesting and installing ArcGIS Pro is posted on Canvas. If you need help on
installing ArcGIS software to your computer, please directly contact IT. https://www.umass.edu/it/support
· Alternative to the above, you can connect through UMass
Azure Virtual Desktop and use ArcGIS pro installed on the server. It is not as stable as local installation. For students who
need to request remote desktop access (i.e., Azure Virtual Desktop), please read here and submit a
request.
https://www.umass.edu/it/support/computer-classrooms/access-software-windows-virtual-desktop
In person attendance is strongly encouraged for this class.
The class is designed with group work and interactions. Remote 668 students who plan to take the
course online should contact the instructor in the first week of the semester
and arrange a zoom meeting. 468 students must take the course in person.
The lectures and lecture recording will be accessible via zoom with links
provided on Canvas. All students are welcome to use the recordings. TA will
monitor the zoom Chat during lectures. During the lab time, the instructor and
TA will help in person students and might not be able to provide timely help to
remote students. Remote students are encouraged to get help during the office
hours.
Grading scheme
|
|
468 |
668* |
|
468 |
668* |
|
Labs |
45% |
45% |
Quiz |
10% |
10% |
|
Mid-term
project |
10% |
/ |
Final
project |
30% |
30% |
|
Journal paper presentation |
/ |
10% |
Class
participation |
5% |
5% |
* In some labs, extra parts will be assigned to
668 students. 668 students are expected to give a journal paper presentation
and finish a more complete final project.
Policies
1.
Attendance Policy For most students
taking the class in person, attendance to both lecture and lab session is
required in the normal circumstances and forms a portion of your grade.
Students who are absent due to excusable extenuating circumstances remain
responsible for watching the class recordings, obtaining any materials (i.e.
notes) from other students, meeting all class requirements, and making up
missed work in a timely fashion. Failure to meet course requirements will
require documentation for alternate arrangements to be made.
2.
All the assignments are required to be
submitted to Canvas. Most assignments are integrated in Canvas and auto-graded
answer keys will be released after late due deadline.
If document upload is needed, acceptable document format is either WORD or PDF,
not Google Doc link. Canvas allows the instructor and TA to grant extension to
individuals for special circumstances. Please email
the instructor and TA for excusable extension. Any submission made by
email attachment or link to your shared document will
not be considered for grading and meeting deadline. If you use Google Doc for editing,
you must download a copy in .docx or .pdf and upload it to Canvas.
3. Assignment late submission policy
Both due date and late due date are noted in each assignment. The
late due date is normally 7 days after the due date. All
exercises must be turned in by the hours the exercises are due. Each
student has one chance of late submission with no point deduction during the
semester. Other late submissions before late
due date without advance permission by the instructor will cause a grade
deduction. No lab assignment will be
accepted after one week following the due date unless special arrangement is made with the instructor before the
deadline.
|
Late submission |
24-72 hours (1-3 days) |
72-168 hours (4-7
days) |
>7 days |
|
Point deduction |
1/4 |
1/2 |
Not accepted |
4.
Missing mid-term project, final project
presentation, final project report, or >=3 assignments will result in an F
for the course, no matter what your final grade is.
Academic Honesty Statement: Since the integrity
of the academic enterprise of any institution of higher education requires
honesty in scholarship and research, academic honesty is required of all
students at the University of Massachusetts Amherst. Academic dishonesty is
prohibited in all programs of the University. Academic dishonesty includes but
is not limited to: cheating, fabrication, plagiarism,
and facilitating dishonesty. Appropriate sanctions may be imposed on any
student who has committed an act of academic dishonesty. Instructors should
take reasonable steps to address academic misconduct. Any person who has reason to believe that a
student has committed academic dishonesty should bring such information to the
attention of the appropriate course instructor as soon as possible. Instances
of academic dishonesty not related to a specific course should be brought to
the attention of the appropriate department Head or Chair. Since students are
expected to be familiar with this policy and the commonly accepted standards of
academic integrity, ignorance of such standards is not normally sufficient
evidence of lack of intent.
(http://www.umass.edu/dean_students/codeofconduct/acadhonesty/).
Disability
Accommodation Statement: The University of
Massachusetts Amherst is committed to providing an equal educational
opportunity for all students. If you have a documented physical, psychological,
or learning disability on file with Disability Services (DS), you may be
eligible for reasonable academic accommodations to help you succeed in this
course. For disability accommodation, please register with Disability Services
as early as possible. Meanwhile please notify me within the first two weeks of
the semester so that we may make appropriate arrangements. DS accommodation request must be filed each semester. Do
not expect the request will be automatically carried over.
Class
schedule and reading are posted on http://www.geo.umass.edu/courses/geo468/. This link is also provided in Canvas.
Schedule will be updated with classes progressing. Lecture notes and assignments in PDF are posted on Canvas. Check your
UMass email daily for class notices and announcements.
|
General |
Vector |
Raster |
Spatial statistics |
|
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Week |
Class |
Arrangement |
Topic |
Assignment/Reading |
Location |
|
||
|
1. Jan 29 |
Th |
Lec 0 |
Syllabus and Introduction |
|
Morrill
129 |
|
||
|
2. Feb 5 |
Tu |
Lec 1.1 |
Coordinate system and Projection revisit
(Datum, Projection) |
Bolstad ch3 p89-111 Optional ch112-115 |
Morrill 129 |
|
||
|
Th |
Lec 1.2 Lab
1 |
Coordinate
system and Projection revisit (UTM, State Plane, GIS operation) Projection
(Define, convert projection, raster georeferencing) |
Bolstad ch3 p116-132 |
Morrill 212 |
|
|||
|
3. Feb 12 |
Tu |
Lab 1 |
Continue |
Lab book Ch1 p111-127 |
Morrill 212 |
|
||
|
Th |
Lec 2 |
Geodatabase
and Vector data model revisit Quiz 1 Projection |
Bolstad ch2 scan p25-38, p61-63 read p39-50 more carefully |
Morrill 129 |
|
|||
|
4. Feb 19 |
Tu |
Lab 2 |
Working
with Geodatabase I.
Geodatabase schemas II.
Editing with Topology III.Working with Geodatabase
(Domain and Subtype) |
|
Morrill 212 |
|
||
|
Th |
|
Monday schedule |
|
|
|
|||
|
5. Feb 26 |
Tu |
Lec 3 with
in-class exercise |
Vector Spatial Analysis revisit (Spatial Query, Spatial Join, Overlay, Dissolve) |
Bolstad ch9 (You can skip this reading if you are familiar
with this content from Intro GIS) |
Morrill 212 |
|
||
|
Th |
Lab 3 |
Map Overlay and Geoprocessing |
Price p309-322 |
Morrill 212 |
|
|||
|
6. Mar 4 |
Tu |
Lec and Lab 4 |
Census
data and Geocoding |
Bolstad p318-321, p416-417 |
Morrill 212 |
|
||
|
Th |
Lec 5.1 |
Raster
Data Model Quiz 2 Vector data
model and basic analysis |
Bolstad ch 2
p51-60, 70-72, Bolstad ch10 p435-460 |
Morrill 129 |
|
|||
|
7. Mar 11 |
Tu |
Lec 5.2 |
Raster
Spatial Analysis (local, focal, zonal, block) |
Morrill 129 |
|
|||
|
Th |
Lab
5.1 |
Raster
Spatial Analysis (local functions) |
|
Morrill 212 |
|
|||
|
8. Mar 18 |
TuTh |
|
Spring break |
|
|
|
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|
9. Mar 25 |
Tu |
Lec 5.3 Lec 6.1 |
Raster
Spatial Analysis (focal, zonal, block) Terrain
Analysis: TIN, topography surface |
Bolstad ch2 p61-66, ch11 p473-481, p494-497 Bolstad ch12, p509-523 |
Morrill 129 |
|
||
|
Th |
Lab 5.2 |
Raster
Spatial Analysis |
Price p339-352 |
Morrill 212 |
|
|||
|
10. Apr 1 |
Tu |
Lec 6.2 |
Terrain
Analysis: Viewsheds, hillshade, watershed analysis Quiz 3 Raster spatial analysis |
Bolstad ch11, p482-491 |
Morrill 129 |
|
||
|
Th |
Lab 6 |
Watershed
delineation |
Morrill 212 |
|
||||
|
11. Apr 8 |
Tu |
|
Mid-project
|
|
Morrill 212 |
|
||
|
Th |
|
Graduate student journal paper
presentation |
|
Morrill 129 |
|
|||
|
12. Apr 15 |
Tu |
Lec 7 |
Other raster analysis: sampling,
interpolation, density analysis, cost analysis |
Bolstad ch10, p460-464 |
Morrill 129 |
|
||
|
Th |
Lab 7 |
Cost
Analysis |
|
Morrill 212 |
|
|||
|
13. Apr 22 |
Tu |
Lec 8 |
Spatial
Statistics I.
Point
Pattern Analysis: Measure and Test II. Spatial continuous
data and area objects: spatial autocorrelations test Quiz 4 Terrain Analysis |
Bailey & Gatrell ch3,
5&7 |
Morrill 129 |
|
||
|
Th |
Lab 8 |
Spatial statistics |
|
Morrill 212 |
|
|||
|
14. Apr 29 |
Tu |
Working on final project Final project proposal due April
26 Monday |
|
Morrill 212 |
|
|||
|
Th |
Working on final project |
|
Morrill 212 |
|
||||
|
15. May 7 |
Tu |
Working on final project |
|
Morrill 212 |
|
|||
|
|
Th |
Final Project presentation |
|
Morrill 129 |
|
|||
|
|
|
Final
project report due on May 17 Friday |
|
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