Enhancing satellite-based gross primary production estimation with photosynthetically active radiation and foliage clumping
Abstract
Satellite remote sensing has revolutionized our ability to monitor Earth's ecosystems, including estimating Gross Primary Production (GPP), a crucial metric for understanding carbon fluxes. However, accurately estimating GPP from satellite data remains challenging due to several factors, including uncertainties in key parameters such as Photosynthetically Active Radiation (PAR) and foliage clumping. This article delves into recent advancements in satellite-based GPP estimation, focusing on the integration of PAR and foliage clumping to improve the accuracy of Near-Infrared Vegetation Index (NIRv) estimates of GPP. We explore the significance of PAR and foliage clumping in enhancing GPP estimation accuracy and discuss the implications for ecosystem monitoring and climate change research.