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Project description
NDVI TRENDS
A module for studying NDVI Trends (from S2/LSAT) with a particular emphasis on determining or deriving relvant features for cover-cropping.
- Generate and Save NDVI Series for small Regions a. grab NDVI Series on the fly for any geom b. for a large set of geoms efficiently grab and save all
- Smooth NDVI Series a. linear interpolation b. remove drops c. sg smoothing d. window smoothing e. 1 at a time or save a stack
- Days over (normalized) NDVI Threshold
- Cover Crop Detection
- green-up dates
- features (AUC, mean/median differences for set time periods, other metrics)
PROPOSED MODULES
smoothing: handles smoothing data
data: get/save data (in real time, 1 at a time, map over a bunch)
gee: helpers for google earth engine
nb: helpers for visual outputs for notebooks
calc: smooths data, extracts features of interest, computes GREEN-DAYS
cli: automates batch jobs
REQUIREMENTS
Packages are managed through a conda yaml file. To create/update the ndvi_trends
environment:
# create
conda env create -f conda-env.yaml
# update
### NOTE: prune not working https://github.com/conda/conda/issues/7279
conda env update -f conda-env.yaml --prune
### use mamba as workaround:
mamba env update -f conda-env.yaml --prune
Additionally this repo is using config_args and mproc still in developmemt. Clone the repos and then (with ndvi_trends conda env activated) run pip install --e .
Note: the minimal conda-env does not specify the required package versions. requirements.txt can be used to recreate the exact env.
QUICK START
Usage example
DOCUMENTATION
API Docs
STYLE-GUIDE
Following PEP8. See setup.cfg for exceptions. Keeping honest with pycodestyle .
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