Closed github-actions[bot] closed 9 months ago
Final project completed, see submission as public repository here: https://github.com/advythr/grassland-phenology-project.
The README for the repository includes the modified rubric I made.
I encountered a bug I could not solve while completing this project, and created a bug report here: https://github.com/earthlab-education/ea-bug-queue/issues/6. The bug is noted in the Jupyter notebook and should be reproducible upon running the notebook.
Our changing climate is changing where key grassland species can live, and grassland management and restoration practices will need to take this into account.
In this project, you will create a habitat suitability model for Sorghastrum nutans, a grass native to North America. In the past 50 years, its range has moved northward. The model will be based on combining multiple data layers related to soil, topography, and climate. You will also demonstrate the coding skills covered in this class by creating a modular, reproducible workflow for the model.
You will create a reproducible scientific workflow
Your workflow should:
xarray-spatial
library, which is available in the latest earth-analytics-python environment (but will need to be installed/updated if you are working on your own machine). Note that calculated slope may not be correct if you are using a CRS with units of degrees; you should re-project into a projected coordinate system with units of meters, such as the appropriate UTM Zone.ds.rio.reproject_match()
method fromrioxarray
.If you are unsure about which model to use, we recommend using a fuzzy logic model
To train a fuzzy logic habitat suitability model:
You will be evaluated on your code AND how you present your results
I will use the following rubric:
Keep your eyes out for videos!
I won’t release a full demo of this, but you will have videos on writing pseudocode, accessing data sources, and any tricky problems that come up.