# Final Project- Earth Analytics Course - GEOG 4563 / 5563

## About the Final Project

The final project in this course includes:

1. A 10 minute group presentation (10%): The structure of the presentation is discussed below.
2. An individual report (20%): Written in R markdown and submitted in either .html or .pdf format.

## Earth Analytics Course Final Project

### 1. Select a Science Question, Phenomenon or Event

Select a topic that you wish to address and better understand. Your topic can be related to something covered in class or something completely different! You must be able to ask and answer an explicit science question using data that you collect, download and find (not data that you have been given to use in this course).

### 2. Research Your Topic

Find papers and other documentation on your selected topic. Research your topic and craft a background section of your presentation that is founded in science. You will also use this to write your literature review for your final paper.

### 3. Find Data

Find at least 2 distinct datasets that are from different sources. A source is defined as a collection method, type or sensor so for example the Landsat sensor is a type of data. NDVI and NBR derived from Landsat are still data from one source. You could however use Landsat and MODIS as two separate sources given the data come from two different sensors. You should use the data to answer the question that you select for your project.

### What to Submit & When

The final group presentations will occur during the last two weeks of class. IMPORTANT: Submit your final presentation to D2L by 9am this day. I will download all presentations to my computer. DO NOT EMAIL ME CHANGES TO YOUR PRESENTATION after 9AM!

The final individual report is due the following week during finals: Submit your html / pdf file and your .Rmd file to D2L by Monday 18 December 2017 @ 9AM.

• NOTE 1: I expect groups to be the same as the groups for the mid-term. However it is OK if you changed your topic, data sources, questions, etc. given feedback on the mid-term presentation.
• NOTE 2: You can decide whether you want to submit your report in .html vs .pdf format. If you want to include an interactive graphic you will need to use .html format!

## Final Group Presentation

For your final, as a group, you will present the following:

• The study area that you selected for your project. Be sure to include a map and context map that clearly shows where the study area is. Create your map using R.
• The science topic that you selected for your project.
• Why the topic, event or phenomenon is important (why should the class care). This should include some background that you develop via a literature review. Have other people studied it? What did they find?
• Plots showing at least 2 different types of data from different sources that allow you to answer questions about the topic.
• Explanation of where you got the data (the source).
• Explanation of how you processed the data in R.
• Results that you found by looking at the data.
• Challenges that you faced in working with the data.
• Any relevant conclusions.

This is a science presentation so be sure to clearly articulate the significance of your project.

#### Important:

• You have exactly 10 minutes to present your project to the class.
• Each member in each group needs to present!
• You can use any presentation tool that you wish for your presentation (powerpoint, rpres, pdf, etc.), as long as the entire class can see the final presentation and you can submit it to D2L for grading.
• Groups should be 2-3 people. It is OK if you decide you really want to work on your own but I prefer (and you will have a better project) if you work with others.
• You can reach out to the the experts who have presented in this course for guidance if you want!
• Matthew Rossi (floods - Earth Lab)
• Megan Cattau (fire - Earth Lab)
• Lise (social media - Earth Lab)

## Individual Final Report

To complement your final presentation, create a report using R markdown. This report should be structured as a scientific paper or white paper. For your report, select a component of the project that you are most interested in. Perform a literature review on that topic. In your report be sure to cite in your text at least 2 peer reviewed journal articles about that topic and then 2 other sources (peer reviewed or not peer reviewed) including blogs, newspaper articles, etc. Also be sure to include data driven plots and maps as appropriate. Your report should include:

1. An Introduction that includes a map of the study area created in R.
2. Literature review that references to at least 2 scientific (peer reviewed) papers and 2 other sources on the topic.
3. A Methods overview that describes
• The data that you used
• The source of the data
• How the data were processed in R.
4. Results - at least 4 maps and/or plots that answer the question that you decided to address or the phenomenon that you decided to explore using data.
5. Summary text - what did you learn about your topic? What did the data tell you?
6. References - list all references that you used to write your report (in text citations) at the end. Don’t forget to reference your data.

The report should be written independently, however it is ok if you decide to share code with your group members given you may all tackle different parts of the data when you work on your project. It is also ok if you share interesting articles and other sources of information about the topic.

The writing of each report needs to be your own.

The report should also include the code that you used to create maps and process any data used. You can hide this code using code chunk arguments but be sure to clearly document your process as you have been learning in class all semester! We will grade your final pdf / html document and the code.

#### Report Notes

• Be sure all plots and maps have clearly labeled x and y axes (as appropriate) and legends.
• All plots / maps should also include a caption that describes what the data show. You can add the caption using fig.cap = OR if you prefer, add the caption in the markdown text of your document.
• Spell and grammar check your paper BEFORE YOU SUBMIT. This is worth 20% of your grade. Take time to make sure it’s well written!
• Hide your code in the .Rmd document UNLESS you feel like your methods are important to call out (for example you may decide to show some of your methods in the methods section of the report).
• Turn off warnings and other messages so they do not appear in your final rendered report.
• Do not include any code in your submission that is not crucial to creating the output plots and analysis.
• Makre sure that the .Rmd (or .ipynb) file runs (we can hit knit in Rstudio and everything will work).
• Start early - make sure your reports renders to pdf or html WELL BEFORE the assignment is due!
• Proof your output .html file BEFORE your submit it.

## Graduate Students - Additional Report Elements

In addition to the requirement above, graduate students should include:

1. A more robust literature review on the selected topic. This literature review should include 4 or more peer reviewed references and should be 1.5 to 2 pages in length (~700 words).
2. An abstract that provides the big picture of the topic that you selected. This abstract should follow the format of an abstract that your would write for a journal submission in your field.

## Submission

• GROUP PRESENTATION: The final group presentations will occur on the final day of class. Submit your final presentation to the group D2L Drop Box by 9AM on the class day that you present. )

• FINAL INDEPENDENT REPORT: The final individual report is due on Monday of finals week. Submit your html / pdf file and your .Rmd file to D2L by Monday 18 Dec 2017 @ 9AM.

• DATA: Please submit your data to D2L as a group to D2L by Monday 18 Dec 2017 @ 9AM. If you are using a specific dataset that you are not able to share, OR a data set that is particularly large, please shoot us a note and we will figure out an alternative! If the data are large, submitting an intermediate output that is smaller and will allow us to run your analysis is an option.

## Presentation Rubric

#### Science (50%)

Full CreditNo Credit
The science question / topic is thoughtfully presented
The importance of the project topic to those in the room (the specific audience) is clearly articulated. Why should we (the earth analytics class) care?
Results of data analysis are clearly articulated. (If the student presents the week prior their results may not be complete, thus expected results are articulated instead
The methods that clarify how the data were processed are clearly articulated as they relate to the science question / topic.
Conclusions associated with data analysis are clearly articulated and thoughtful. Conclusions consider the data analysis as presented. (If the student presents a week prior, conclusions may not be complete, but expected findings can be discussed.)

#### Data (25%)

Full CreditNo Credit
2 specific data sources are identified in the presentation
Each data source identified is described: how it’s collected & where you downloaded it from or accessed it
How the data were used to address the topic is clearly articulated
Sources of uncertainty associated with the data and/or analysis are clearly articulated in the presentation
The x, y axes, legends, associated units and other elements of each plot are clearly explained and labeled.
An R generated study area map is included in the presentation to clearly articulate the study area.

#### Presentation (20%)

Full CreditNo Credit
Presentation is clear, concise and thoughtfully pulled together
Presenters are well prepared
All students introduce themselves and their background (not just their names, but their major OR area of study)
The project topic is clearly and concisely introduced
Everyone in the group presents
The presentation spans no more than 10 minutes (group will be stopped at 10 minutes).

#### Slide Presentation (5%)

Full CreditNo Credit
Presentation “slides” are simple and easy to read
Presentation graphics are relevant to the topic being presented
Data slides (containing maps or plots) area easy to read
Colors used in the slides are readable
Slides can be read from the back of the room

## Final Report Rubric

### Report Structure & Text Writeup: 10%

Full CreditNo Credit
.pdf or .html file and .rmd file is submitted and named appropriately
Summary text is provided for plots and plots are discussed in the text
Grammar & spelling are accurate throughout the report
Report contains atleast 2 (4 for grad students) scientific peer reviewed citations inserted using proper citation format (you chose the style) and 4 total citations
References are included as both in text citations and as a list at the end of the report and include data sources.

### Report Code Structure & Format: 10%

Full CreditNo Credit
Code is written using “clean” code practices following the Hadley Wickham style guide
Comments are used to document code
There is no extraneous code in the report. All code included in the report is required to create the report output.
Code chunks are hidden / visible as makes sense to support the report
All required R packages are listed at the top of the document in a code chunk
All code chunks run in the order they are presented in the .Rmd or .ipynb file

### Report Plots & Data Content: 20%

Full CreditNo Credit
Report includes a study area map created in R
Report contains at least 4 maps and/or plots that support discussion of the science question or phenomenon selected to study
All plots are labeled appropriately including units. Its contents are discussed in the paper as they related to the selected study topic

### Report Science Content: 60%

Full CreditNo Credit
The project background is presented clearly and thoughtfully and includes the study area
Project background clearly discusses why the topic is important to study
Project background introduces the topic in the context of the literature (both scientific and non scientific as relevant)
Methods: data sources and how the data were acquired are clearly identified and discussed
Methods: processing and analysis methods are clearly articulated in the report and also align with comments and processing steps seen in the code implementation
Results: results include at least 4 plots and/or maps that support the report findings
Results discuss findings making reference to the plots as makes sense
Conclusions associated with data analysis are clearly articulated and thoughtful. They consider the data analysis as presented.