1. This Class
This is a graduate level spatial modeling class in natural resources
This will be one of the most challenging classes you’ll probably take
You’ll leave with a background in modeling and critical thinking that few GIS professionals ever achieve
The material in the class has been combined from previous courses at Colorado State and OSU

2. Introductions

3. Class Info We’ll use Canvas for assignments and grades.
A link to the web site for materials is on the home page in Canvas

4. What is a model? An abstraction of reality
We cannot describe all the details
They are never perfect
Help us to answer questions for problems we cannot test directly
spectorlab.cshl.edu

5. Why do we model?

6. Modeling is Huge!
Modeling is a huge, rapidly growing, and exciting field
My background is in habitat suitability modeling with large datasets, primarily for plants
There will be new topics we’ll work with to learn together
Welcome to research!

7. How the class works There are three components:
Analysis and Modeling in R
Presentations and discussions
Your project
By the end of class you will be able to:
Build your own models in R
Articulate the theory, capabilities, and weaknesses of modeling
Select appropriate modeling approaches
Continue to learn about modeling in your field

8. What do you need from me? Break into groups of 2-3
Select the top 3 things you need me to do to help you be successful
Select someone to add them to the list on the board

9. From Spring 2017:
Make sure all information or material for projects and assignments are in one location
Adequate, in person and availability to troubleshoot modeling issues
Continue to be receptive to input
Communicate
Availability
Resources
Take your time with programming explanations
Keep environment open for questions
Focus on specific tools rather than big range of toolkit -> doing a few things very well
Office hours availability
Two way communication understanding our knowledge gaps
More exposure to R and various statistical analyses
How to acquire high quality data (for free) like high resolution satellite imagery
Application skills: how to pick a modeling approach for research questions
How to incorporate uncertainty

10. Class Structure
I’ve structured the class to prepare you for the “real” world
Out there, there are few classes, tests, and quizzes
Mostly there are:
Communication ( & group)
Coordination
Budgets, reports
Some data collection, evaluation, and modeling…

11. To Be Successful Show up for class and lab (on time) Do the readings
Spend time getting to know R (play time!)
Use your resources to get help! Me
Other students
Books, articles
And the web

12. How to read the book I recommend:
Read it once fairly quickly
Go back and read key parts and think about them
Try the code examples
Ask questions about key parts that are unclear
Play with the concepts in R until comfortable with them
PS: this has taken me years

13. Projects
You are responsible to present and turn in a completed project at the end of the semester
I will not be asking for incremental deliverables (i.e. you need to manage your project schedule)

14. Start Now! Define your project Start your introduction Find the data!
Can be part of your research but must have new content over existing deliverables
Start your introduction
Start looking for papers
Create summaries (annotated bibliography)
Add to citation manager (EndNote)