Species information in multi-temporal Sentinel-2 data improves forest canopy height estimation

• Species information largely explains CHM improvements from multi-temporal data. • Multi-temporal data improves CHM across broadleaf, needleleaf, and mixed forests. • Value of species maps for CHM peaks in species-mixed pixels, drops in pure stands. • CHM accuracy depends on number and timing of Sentinel-2 images. The integration of Sentinel-2 (S2) multispectral data and LiDAR measurements using convolutional neural networks (CNNs) has been extensively explored for large-scale canopy height mapping. Recent studies reported multi-temporal S2 imagery improves canopy height mapping, but the ecological mechanism underlying this improvement remains poorly understood. Here, we hypothesize that this improvement in canopy height estimation is primarily because multi-temporal data contain information relevant to tree species composition. Each tree species likely exhibits a unique reflectance–hei…