Quantifying mangrove leaf area index from Sentinel-2 imagery using hybrid models and active learning-Reference-Cited by-同舟云学术

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Quantifying mangrove leaf area index from Sentinel-2 imagery using hybrid models and active learning

Published:2022-03-25 Issue:15-16 Volume:43 Page:5636-5657
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Binh Nguyen An¹,Hauser Leon T.²^ORCID,Viet Hoa Pham¹,Thi Phuong Thao Giang¹,An Nguyen Ngoc¹,Nhut Huynh Song¹,Phuong Tran Anh¹,Verrelst Jochem³

Affiliation:

1. Ho Chi Minh City Institute of Resources Geography, Vietnam Academy of Science and Technology, Ho Chi Minh, Vietnam

2. Department of Environmental Biology, Institute of Environmental Sciences, Leiden University, Leiden, The Netherlands

3. Image Processing Laboratory (IPL), Parc Científic, Universitat de València, Paterna, Valéncia, Spain

Funder

the Vietnam Academy of Science and Technology

European Research Council

Ramón y Cajal Contract

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2021.2024912

Reference78 articles.

1. Pantropical modelling of canopy functional traits using Sentinel-2 remote sensing data

2. Biophysical and Biochemical Sources of Variability in Canopy Reflectance

3. Global synthesis of leaf area index observations: implications for ecological and remote sensing studies

4. Estimating Canopy Characteristics from Remote Sensing Observations: Review of Methods and Associated Problems

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