We've learned a great deal this semester, I think you'll agree, so it would be nice to put some of this to work on a real project. That's the purpose of the final project portion of this class. So where do we start?

1. The first step would be to pick a study area with data we can use. You should know by now some of the data you might have available. You may find this exercise link useful. You will find resources on the web, but it can be challenging to find good data. You might network with other students in the class, some of whom either work or have contacts at resource agencies in the Bay Area. As I find resources, I will include them on our web site, under "Projects and Data".
2. Then we'll need to decide what kind of analysis to do. This may come from talking with other people working in the study area we choose – e.g. a watershed group, a resource agency, a local environmental organization – or from your own ideas. The reason we started with data is that we won't have time to generate new data for this project – you only have 3-4 weeks.
3. You should pass your idea by me before you get too far into it, to make sure it's going to work and it's acceptable for the assignment.
4. Now you do the project. Watch out for common pitfalls. One requirement for the assignment is including either a model or a script.  This will (a) help you avoid mistakes; (b) let you test it out with different data; (c) provide a record of your work (you'll be surprised at how much of what you've done you'll forget after a project is done); (d) provide you with a model that you can share with others; and (e) make it much easier for me to evaluate what you did. Don't create any datasets beforehand that are not included in the model or script. If you have a problematic dataset that needs preparation beforehand, make sure to carefully document it in your report, test it thoroughly -- I'll need to understand it to evaluate your project.\
5. Document all data sources. You should include in your report a list of all data sources, with all of the essential metadata, especially:
   a. Data source, agency or person who created the data.
   b. Spatial reference: projection & coordinate system, including horizontal and vertical units.
   c. Process used to create the data, including anything you had to do to prepare it for use. Ideally, you should have included preprocessing in your model.
   d. Extent
   e. Cell size
   f. Attributes you are using.
6. Create a map or two displaying the results. 
7. Write it up as a 4-7 page paper describing your project. Include the purpose of the project, the process you used, and an analysis of the results. Make sure to cite your sources, including web sources.  Include a readableprintout of any models or scripts.  On a floppy disk, turn in any (1) .aml text file, (2) ModelBuilder .xmd file, or (3) ArcView project file containing the scripts.  Clearly document your project, since I may have to find your sources to evaluate your project.