Available Code on Github

Python script for downloading and processing GOES-R data

Code created by Danielle Losos using Google Colab and Jupyter Notebooks to process a sample of GOES-R surface products, including a calculation of the Normalized Difference Vegetation Index (NDVI) and the Near Infrared Reflectance of Vegetation (NIRv) from surface reflectances, as well as an estimate of Photosynthetically Active Radiation (PAR) from the Downward Shortwave Radiation (DSR). The data repositories required for processing can be found through the Ameriflux network and the gcp-public-data-goes-16 bucket available on Google Cloud, shown below.

Ameriflux

Search active Ameriflux sites and data availability

Google Cloud Storage

Public GOES-16 data products

Arraylake for ALIVE zarr arrays

A lesson on how to work with zarr libraries created using Arraylake by earthmover, using a zarr library that contains GPP estimates from the Advanced Baseline Imager Live Imaging of Vegetated Ecosystems (ALIVE) workflow. Full tutorial created by Danielle Losos is available here.

GOES_ABI_LandSurfaceProduct_Downloads

ABI_LandSurfaceProducts_Download samples several GOES-R surface data products including surface reflectances (BRF), land surface temperature (LST), and downward shortwave radiation (DSR) at eddy covariance tower locations, effectively converting stacks of images into time-series stored as csv files. This code loops through each product at each tower location at every timestamp for a given year.

GOES_Download

GOES_Download is an introduction to downloading large batches of GOES-R data product files using either command line or python.