A Framework for Measuring Tree Rings Based on Panchromatic Images and Deep Learning

Researchers have developed an automated framework for measuring tree rings using panchromatic images and deep learning, significantly advancing the efficiency of ecological and climatological studies. This innovative method leverages convolutional neural networks to enhance image quality, segment tree rings with precision, and perform ring counting and width calculation in a post-processing stage. The approach was validated using an extensive dataset from diverse sources, including Beijing Forestry University and the UNESCO World Heritage Site, the Summer Palace. By automating traditionally labor-intensive processes, this study offers a transformative tool for decoding tree-ring data, providing deeper insights into environmental impacts on tree growth patterns over time.

Wang, S., Zhao, C., Su, Y., Cao, K., Mou, C., & Xu, F. (2024). A Framework for Measuring Tree Rings Based on Panchromatic Images and Deep Learning. Plant, Cell & Environment, 48(1), 189–198. Portico. https://doi.org/10.1111/pce.15091