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 ### Introduction
 
-For your final project, you will be presenting the results from a
-spatial data analysis in a reproducible format. This analysis will build on skills you have already executed in in-class activities and assignments, as well as the project tasks. 
+For your final project, you will create and publish a Google Earth Engine App that applies at least one remote sensing method that we've learned in this class to a dataset (related to natural hazards) of your group's choice. The methodologies that you could implement in this project include:
 
-Your spatial data analysis will explore a variable from the Census Bureau (I suggest using the American Community Survey) at a selected enumeration
-unit (block group, tract, county, etc.) for a selected geographical area. You will execute Exploratory Spatial Data Analysis on the selected variable, and develop a research question around the variable that will likely require you to obtain additional data (either another variable from the Census Bureau or an additional spatial dataset). 
+- reducing/aggregating to regions
+- utilizing band math or calculating an index
+- creating and analyzing a time series
+- change detection
+- A method of your choice (in collaboration with the instructor)
 
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-### Required Components
--   Create spatial data from non-spatial data (e.g. join)
--   Produce descriptive statistics for your variable of interest
--   Produce at least one non-map graphic (for instance, a histogram or scatterplot)
--   Execute spatial clustering analysis (this should be Moran’s I and LISA)
--   Create at least two different interactive maps (this will likely be your LISA analysis and your variable of interest)
--   Develop one research question, with appropriate table(s),
-    graphic(s), or statistical test results to analyze it
 
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-### Reproducible
-
-You must organize your analysis such that it is fully reproducible. The most important thing that needs to be done to ensure reproducibility is using relative file paths. 
-
+### Your script should: 
+-   Select a dataset from the Earth Engine Data Catalog
+-   Apply at least one type of filter to the dataset (spatial, temporal)
+-   Execute at least one analytical technique on the filtered data
+-   Create at least one meaningful output (chart, map, table, etc.)
 
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-
-### Organization
-
-This is a general breakdown of how your final project may be organized. 
-
-#### *Introduction*
-
-Should be a broad introduction to your topic and your research question. This should be approximately 3-4 paragraphs. You must include at least two outside data sources (at least one must be a peer-reviewed article). Your introduction should introduce the importance of your variable of interest and your geographical area, provide insight into current research on your geographical area/ variable of interest, introduce your research question and hypothesis and why you believe that hypothesis might be true (which will likely cite other literature)
-
-#### *Data Preparation*
-
-Describe data preparation and processing steps required to acquire and prepare your data for analysis. Please **do not** include the code you used to extract the data in your final project report .Rmd document!! This
-should be in a separate .Rmd file (see Project Task \#1 and 2) that
-should be submitted with your final project files.
-
-#### *Data Description and Summary*
-Include descriptive statistics, graph(s), and a plain text description of what you
-learned about your data.
-
-#### *Geographic Distribution and Spatial Clustering*
-Includes map(s), results of clustering analysis, and a plain text
-description of what you learned about your data.
-
-#### *Research Question and Analysis*
-
-Include your research question. Include a plain text description of
-your method to answer the question. Include your answer to the research
-question (your interpretation of the statistical test or graphic). You
-may want to break this section up into subsections!
-
-Note that your research analysis does not need to be entirely comprehensive (meaning you probably will not be able to fully answer your research question given the methods we have learned in this class). Instead, focus on developing a good spatially-oriented research question and applying an appropriate methodology from the ones that we have learned.
-
-#### *Conclusion*
-
-Include a summary of the entire project
-
+### Your application should: 
+-   Be correctly published as a Google Earth Engine App
+-   Allow users to meaningfully engage with your data and analysis
+-   Include at least one option for user selection/ input (button, slider, etc.)
 
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-### Text Length
-
-The narrative text portion (introduction, data description, research question, etc.) of your final project should be a minimum of 750 words. 
+### Your final project report should: 
+-   Introduce your dataset and why it is helpful for analyzing your selected hazard
+-   Discuss your selected hazard, focusing on the human and environmental impacts
+-   Summarize the role of remote sensing in studying the hazard you've selected 
+-   Discuss the benefits of using Google Earth Engine for your analytical strategy
+-   Analyze your script-created output
+-   Conclude by offering suggestions for future research
 
+Your final project report should be approximately 750-1000 words and must include at least 4 peer-reviewed references cited in APA format. 
 
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-### Formatting
+### CrediT Author Statement
+A successful group project requires meaningful participation from all group members. This does not mean that each group member must contribute equally to all project tasks. Collaboration allows people to focus their efforts on parts of the project that they feel they have the most expertise and/or interest in. 
 
-There is a lot of flexibility regarding formatting your final project. Your final document must be readable and visually pleasing. For instance, you should use clear headers, you should not have code warnings and messages in the output, you may want to hide some of your code chunks in the output, you might want to look into R Markdown themes and the `kable` R package for tables. Your maps should be clear, your figures should have readable, well-described axis labels and titles, your tables should be well-formatted, etc. 
+However, it is essential that groups track the contributions of group members and ensure that group members are expending equal(ish) effort towards the completion of the project. 
 
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+[CRediT (Contributor Roles Taxonomy)](https://www.elsevier.com/researcher/author/policies-and-guidelines/credit-author-statement) was developed for academic manuscripts to accurately track individual contributions to collaborative projects. For your final project, you will craft a CrediT statement that describes the contributions of each group member. Note that not every role will be filled for this project (for instance, funding acquisition). 
+
+Alongside the CrediT statement, each group member will complete a self-evaluation of contribution to the project. 
 
-### Deliverables
 
-You should submit a zipped version of your final project folder. This zipped file should include
-- Your "Code" folder with the .Rmd and .html of your data preparation (Project Task 1+2) document and your final project .Rmd and .html
-- Your "Data" folder with your processed dataset (output of Project Task 2)
 
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