A convolution neural network for forest leaf chlorophyll and carotenoid estimation using hyperspectral reflectance-Reference-Cited by-同舟云学术

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A convolution neural network for forest leaf chlorophyll and carotenoid estimation using hyperspectral reflectance

Published:2022-04 Issue: Volume:108 Page:102719
ISSN:1569-8432
Container-title:International Journal of Applied Earth Observation and Geoinformation
language:en
Short-container-title:International Journal of Applied Earth Observation and Geoinformation

Author:

Shi Shuo,Xu Lu,Gong Wei,Chen Bowen,Chen Biwu,Qu Fangfang,Tang Xingtao,Sun Jia,Yang Jian

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

National Basic Research Program of China

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Computers in Earth Sciences,Earth-Surface Processes,Global and Planetary Change

Reference35 articles.

1. Mapping Forest Ecosystem Services: A Review;Ajrhough;Int. Arch. Photogrammetry, Remote Sensing and Spatial Information Sciences,2019

2. Chlorophyll Concentration Retrieval by Training Convolutional Neural Network for Stochastic Model of Leaf Optical Properties (SLOP) Inversion;Annala;Remote Sensing,2020

3. Spatially constrained inversion of radiative transfer models for improved LAI mapping from future Sentinel- imagery;Atzberger;Remote Sens. Environ.,2012

4. Deep Convolutional neural network (CNN) in tea leaf chlorophyll estimation: a new direction of modern tea farming in Assam, India;Barman;J. Appl. Natural Sci.,2021

5. Integrating Multi-Source Data for Rice Yield Prediction across China using Machine Learning and Deep Learning Approaches;Cao;Agric. For. Meteorol.,2021

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