A Radiative Transfer-Driven Deep Learning Framework for Accurate Estimation of Rice Growth Parameters Using Multisource UAV Data (opens in new tab)

Leaf area index (LAI) and leaf chlorophyll content (LCC) are key indicators for monitoring rice growth dynamics. While unmanned aerial vehicle (UAV)-based hyperspectral data is widely used, its high redundancy poses challenges for efficient information extraction. To address this, we propose a two-step generic framework. First, synthetic spectra generated by a field-constrained PROSAIL model are used to train a 1-D convolutional neural network (1D-CNN) with a self-attention mechanism that der...