Data presented in the paper: A Novel Instrument for Bed Dynamics Observation Supports: Machine Learning Applications in Mangrove Biogeomorphic Processes

  • Zhan Hu (Creator)
  • J. Zhou (Creator)
  • ChunQing Wang (Creator)
  • H. Wang (Creator)
  • Z. He (Creator)
  • Y. Peng (Creator)
  • P. Zheng (Creator)
  • F Cozzoli (Creator)
  • T.J. Bouma (Creator)

Dataset

Description

Short-term bed level dynamics on the intertidal flats plays a critical role in long-term coastal wetland dynamics. High-frequency observation techniques are crucial for better understanding of intertidal biogeomorphic evolutions. Here, we intrĀ (truncated)
Date made available2020
PublisherTU Delft - 4TU Centre for research data
Date of data production2018 - 2019
Geographical coverageNational mangrove park in Hailing island, Yangjiang city, Guangdong province, China

Cite this

Hu, Z. (Creator), Zhou, J. (Creator), Wang, C. (Creator), Wang, H. (Creator), He, Z. (Creator), Peng, Y. (Creator), Zheng, P. (Creator), Cozzoli, F. (Creator), Bouma, T. J. (. (Creator) (2020). Data presented in the paper: A Novel Instrument for Bed Dynamics Observation Supports: Machine Learning Applications in Mangrove Biogeomorphic Processes. TU Delft - 4TU Centre for research data. 10.4121/UUID:3D971EC0-7A0D-46FA-BE02-A2B3D4B9BADD