Search results for "Vegetation traits"

showing 1 items of 1 documents

Quantifying Fundamental Vegetation Traits over Europe Using the Sentinel-3 OLCI Catalogue in Google Earth Engine

2022

Thanks to the emergence of cloud-computing platforms and the ability of machine learning methods to solve prediction problems efficiently, this work presents a workflow to automate spatiotemporal mapping of essential vegetation traits from Sentinel-3 (S3) imagery. The traits included leaf chlorophyll content (LCC), leaf area index (LAI), fraction of absorbed photosynthetically active radiation (FAPAR), and fractional vegetation cover (FVC), being fundamental for assessing photosynthetic activity on Earth. The workflow involved Gaussian process regression (GPR) algorithms trained on top-of-atmosphere (TOA) radiance simulations generated by the coupled canopy radiative transfer model (RTM) SC…

Vegetation traitsTime seriesvegetation traits; Sentinel-3; TOA radiance; OLCI; Gaussian process regression; machine learning; hybrid method; time series; Google Earth EngineTOA radianceMachine learningHybrid methodGeneral Earth and Planetary SciencesMatemática AplicadaSentinel-3OLCIGoogle Earth EngineGaussian process regressionRemote Sensing
researchProduct