/Global-EVT-maps

Global temporally reconstructed maps of essential vegetation traits processed from the TOA Sentinel-3 catalogue in Google Earth Engine

Primary LanguagePython

Hello!

We present the workflow for the retrieval of global maps in Google Earth Engine (GEE) of 4 Essential Vegetation Traits (EVTs):

(1) fraction of absorbed photosynthetically active radiation (FAPAR) (2) leaf area index (LAI) (4) fractional vegetation cover (FVC) (3) leaf chlorophyll content (LCC)

Sentinel-3 (S3) top-of-atmosphere (TOA) OLCI data is used with hybrid retrieval models to infer globally four essential vegetation traits (EVTs): The models are based on Gaussian process regression (GPR) algorithms trained on SCOPE-6SV model simulations, and so applicable to process TOA OLCI date.

12124r1

You can use the Colab file (Batch_export_EVT_maps.ipynb) containing a Python script with comments and descriptions to retrieve the maps in your own GEE environment.