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A Framework for Measuring Tree Rings Based on Panchromatic Images and Deep Learning.
Wang, Sheng; Zhao, Chaoyue; Su, Yun; Cao, Kangjian; Mou, Chao; Xu, Fu.
Afiliación
  • Wang S; School of Information Science and Technology, Beijing Forestry University, Beijing, China.
  • Zhao C; Engineering Research Center for Forestry-Oriented Intelligent Information Processing, National Forestry and Grassland Administration, Beijing, China.
  • Su Y; State Key Laboratory of Efficient Production of Forest Resources, Beijing, China.
  • Cao K; School of Information Science and Technology, Beijing Forestry University, Beijing, China.
  • Mou C; Engineering Research Center for Forestry-Oriented Intelligent Information Processing, National Forestry and Grassland Administration, Beijing, China.
  • Xu F; State Key Laboratory of Efficient Production of Forest Resources, Beijing, China.
Plant Cell Environ ; 2024 Sep 10.
Article en En | MEDLINE | ID: mdl-39253958
ABSTRACT
Tree-ring data are pivotal for decoding the age and growth patterns of trees, reflecting the impact of environmental factors over time. Addressing the significant shortcomings of traditional, labour-intensive and resource-demanding methods, we propose an innovative automated technique that utilizes panchromatic images and deep learning for measuring tree rings. The method utilizes convolutional neural networks to enhance image quality, precisely delineate tree rings through segmentation and perform ring counting and width calculation in the post-processing stage. We compiled an extensive data set from diverse sources, including Beijing Forestry University and the Summer Palace, to train our algorithm. The performance of our method was validated empirically, demonstrating its potential to transform tree-ring analysis and provide deeper insights into ecological and climatological research.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Plant Cell Environ Asunto de la revista: BOTANICA Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Plant Cell Environ Asunto de la revista: BOTANICA Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos