NRM 341 Course Information

- Spring 2001 -
 
 



 
 
 
 
 
 
 
 
 
 
 

Instructor:
Andrew Balser
336 O'Neill Bldg.
Dept. of Forest Sciences, SALRM
University of Alaska Fairbanks


Teaching Assistant:
Aaron Woods

 


Course Objectives:

1)   To build upon GIS concepts covered in NRM 338 (or similar course) in order to develop a broader understanding of the types of questions and objectives that GIS can address.
                            "What is it good for and why do I care?"

2)   To provide hands-on experience in conceiving, structuring and performing such analyses with various types of GIS data.
                            "O.K., so show me some examples of how to get it done."

Hardware/Software:

We'll be using ARC/INFO and ArcView on WindowsN/T.  While experience with ARC/INFO and ArcView is not required (though helpful), general computer literacy is required.

What the course will and won't do . . .

The fall term GIS class, NRM338, teaches students how to create base information within a GIS.  This means taking information from a variety of sources - field sampling, paper maps, GPS coordinates etc etc and putting them into a computer-based GIS.  NRM338 teaches concepts of how information about the world is translated into a GIS format, and provides hands on experience doing it.  The spring term class, NRM341, teaches students how to do things with that information once it is already in a GIS format.  While NRM341 will review concepts of data structure covered in NRM338, it will not re-teach the process of creating base data.  NRM341 will cover concepts, strategies and methods of taking base information from a variety of sources and combining and analyzing them to ask questions about the landscape and provide meaningful answers.  Since we will be working with base data that already exists, it will not be directly necessary for students of NRM341 to have taken NRM338.

Basically, learning GIS is a matter of learning the fundamental concepts up front and becoming familiar with how the data and software work.  Once that's done, you are prepared to get good at it by trial and error and experimentation over time.  It is typical for a GIS "guru" to have learned the basics by taking classes, and then learning the rest on the job.  With every new project you learn new things.  These classes are designed to get you to the point where you have learned the basics, and are ready to jump into the process of trial-and-error learning on your own.


Lectures:  Tuesday/Thursday, 9:45-11:15 Natural Sciences 165

Lab:   Tuesday 2-5PM  OR  Wednesday 6-9PM ONeill 330

Office Hours:     Anytime I'm in my office, or by e-mail appointment . . .


Grading:

Based on total points from the following:

4 quizzes 100 points

4 reading assignments 80 points

13 lab assignments 260 points

2 on-line exams 200 points
 

Total possible points 640. The final grades will be curved based on total points earned
in the course. To emphasize understanding, and not memorization, all exams will be
open book.



 
 

Spring 2001 Schedule:

Lab Reference Document
Sample Documentation File


Date
Lecture
Lab
Week  1  January 18 Introduction none
Week  2  January 23 - 25 Case Studies - GIS in Research Lab 1 - Looking at Data & 
Making Maps
Week  3

    January 30 - February 1

Data Structure / Polygon Analysis

reading assigment 1, due 2/1/01
quiz 1, 2/1/01

Lab 2 - ARC/INFO Intro &
   Polygon Analysis

docfile

Week  4  February 6 - 8 Grids / Map Projections
GridAnalaysis
Lab 3 - Grid Analysis 'Dammit'

docfile

Week  5  February 13 - 15 Continuous Surface Model/
Types of Analyses

reading assignment 2, due
2/20/01

Lab 4 - Continuous Surface
             Model - 
Critical Habitat Watershed

docfile

Week  6  February 20 - 22 Analysis in ArcView/
Structuring an Analysis
 
 

quiz 2, 2/22/01

Lab 5 - Continuous Surface
             Model - 
Critical Habitat Watershed
(ArcView method)

docfile

Week  7 

    February 27 - March 1

Structuring an Analysis cont./
Intro to making an Effective Map/
Exam Review
Lab 6 - Three New Tricks &
Practice Exam 1
Week  8  March 6 - 8 EXAM 1 EXAM 1
Week  9  March 13 - 15 Spring Break Spring Break
Week 10 March 20 - 22 AMLs

quiz 3, 3/22/01

Lab 7 - AML & 
Changing Map Projections

lab7amls.zip

Week 11 March 27 - 29 Intro. to Remote Sensing I Lab 8 - Supervised Classification
Week 12 April 3 - 5 Intro. to Remote Sensing II

Guest Lecture: Scott Rupp
"GIS for Modelling"

reading assignment 3, due
4/10/01

Lab 9 - Supervised Classifications: Evaluation & Analysis 
Week 14 April 10 - 12 Regions

Guest Lecture: Will Putman
"GIS at Tanana Chiefs Conf."

Lab 10 - Regions: Forest Analyis Using Regions and Supervised Classifications
Week 15 April 17 - 19 Points - Telemetric Data

Guest Lecture: Brad Griffith
"GIS for Wildlife Research"

reading assignment 4, due
4/24/01

Lab 11 - Analysis with telemetric point data
Week 16 April 24 - 26 Dynamic Segmentation/Network

quiz 4, 4/26/01

Lab 12 - Dynamic Segmentation
Week 17 May 1 - 3 Review/Summary/Discussion Lab 13 - Practice Exam 2
Week 18 May 7 - 10 EXAM 2 EXAM 2