M. B. Schimalski

Assessing Machine Learning and Deep Learning Approaches for Wood Volume Prediction in Forest Plantations Using Hyperspectral Imagery: Limitations and Challenges

This study evaluates four machine learning algorithms, Random Forest Regressor, Support Vector Regressor (SVR), Multilayer Perceptron, and a 1-D Convolutional Neural Network, for estimating Pinus taeda L. wood volume using EnMAP hyperspectral data. Spectral preprocessing included PCA dimensionality reduction, with perm...