Improved Semisupervised UNet Deep Learning Model for Forest Height Mapping With Satellite SAR and Optical Data-Reference-Cited by-同舟云学术

Improved Semisupervised UNet Deep Learning Model for Forest Height Mapping With Satellite SAR and Optical Data

Published:2022 Issue: Volume:15 Page:5776-5787
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

Ge Shaojia¹^ORCID,Gu Hong¹,Su Weimin¹,Praks Jaan²^ORCID,Antropov Oleg³^ORCID

Affiliation:

1. School of Electronic and Optical Engineering, Department of Electronic Engineering, Nanjing University of Science and Technology, Nanjing, China

2. Department of Electronics and Nanoengineering, Aalto University, Espoo, Finland

3. VTT Technical Research Centre of Finland, Espoo, Finland

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Business Finland and Forest Carbon Monitoring

European Space Agency

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atmospheric Science,Computers in Earth Sciences

Link

Reference53 articles.

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