Total Points: 20
Note: exceptional attention to any element of presentation or analysis can yield up to 2 bonus points.
1. Vector Data (4 points)
Criteria
Points
Read spatial vector data with Ibis
1
Manipulation of vector data (e.g. filter)
1
Coercion to geopandas or geojson
1
Visualization in leafmap
1
Criteria
Points
STAC search of raster data
1
Streaming-based computation of NDVI
1
Visualization in leafmap
1
2. Raster-vector operations (3 points)
Criteria
Points
Compute zonal statistics
1
Visualization in plots/charts (seaborn)
1
Visualization in leafmap
1
3. Text-based Explanations and Scientific Context (6 points)
Criteria
Points
Discussion of redlining and systemic racism
4
Clear explanations of analysis process
1
Integration of explanations with code and results
1
5. GitHub and Repository Management (3 points)
Criteria
Points
Proper use of GitHub for version control
1
Passing all built-in CI tests
1
Interactive "static" HTML page
1
Students should demonstrate proficiency in working with both raster and vector data in a spatial context.
Code should be concise, supported by text and follow best practices for readability and efficiency.
Visualizations should effectively communicate key findings from the data analysis.
The GitHub repository should be professional, well-organized, and include all necessary files for reproducing the analysis.