Task: Use a provided Sentinel-2 data cube with only raw bands, then post-process a new layer of NDVI to achieve a map and time series visualization
- Materials:
- netCDF of data cube
- Geojson of sub-AOI
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A Jupyter notebook from start to finish, opening, exploring, visualizing, and modifying the geospatial data, specifically including the following:
a. Calculation of the Normalized Difference Vegetation Index (NDVI) over the entire AOI for each date given in the data cube and added as a separate data layer in the same provided data cube
b. A visual RGB image of one date
c. Distribution (histogram) of NDVI pixels
d. Time series of NDVI averaged over the AOI
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A brief description of your interpretation of the spatial distribution and evolution of the NDVI/vegetation
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A visualization of NDVI (colormap here) clipped to the provided sub-AOI
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Development is to be done using Python. Any frameworks/libraries are accepted.
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Any additional data exploration (i.e. not explicitly required for the deliverables) can be kept in the notebook if displayed in a clean and organized manner