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International Journal of Remote Sensing Volume 42, 2021 - Issue 10
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Research Article

Exploring the potential of canopy reflectance spectra for estimating organic carbon content of aboveground vegetation in coastal wetlands

Hang Chenga School of Resource and Environmental Sciences, Wuhan University, Wuhan, ChinaORCID Iconhttps://orcid.org/0000-0001-7898-7472View further author information
ORCID Icon,
Jing Wangb College of Water Sciences, Beijing Normal University, Beijing, China;a School of Resource and Environmental Sciences, Wuhan University, Wuhan, ChinaCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0001-6563-4555View further author information
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Yingkun Duc Academy of Agricultural Planning and Engineering, Ministry of Agriculture and Rural Affairs of the People’s Republic of China, Beijing, ChinaORCID Iconhttps://orcid.org/0000-0002-1771-2966View further author information
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Tianlin Zhaid College of Resources and Environmental Sciences, Henan Agricultural University, Zhengzhou, ChinaView further author information
,
Ying Fanga School of Resource and Environmental Sciences, Wuhan University, Wuhan, ChinaView further author information
&
Zehui Lia School of Resource and Environmental Sciences, Wuhan University, Wuhan, ChinaView further author information
Pages 3850-3872 | Received 14 Sep 2020, Accepted 04 Jan 2021, Published online: 14 Feb 2021

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Read on this site (3)

Xin Tong, Limin Duan, Tingxi Liu, Zhenlei Yang, Yixuan Wang & Vijay P. Singh. (2023) Estimation of grassland aboveground biomass combining optimal derivative and raw reflectance vegetation indices at peak productive growth stage. Geocarto International 38:1.
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Shuguang Liu, Zhenqi Hu, Zhenke Zhang, Chu Zhang & Li Lu. (2023) Estimating canopy parameters of winter wheat at different stages using hyperspectral data combined with soil variables. International Journal of Remote Sensing 44:15, pages 4684-4703.
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Jia Jin, Quan Wang & Guangman Song. (2023) Exploring low order fractional derivative spectra indices for estimating leaf fuel moisture content across a variety of plant species. International Journal of Remote Sensing 44:7, pages 2342-2358.
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Articles from other publishers (7)

Jiajia Xu, Genshen Fu, Lipeng Yan, Lei Yu, Fan Kuang, Qingfeng Huang & Xuehai Tang. (2024) Estimation of the Relative Chlorophyll Content of Carya illinoensis Leaves Using Fractional Order Derivative of Leaf and Canopy Scale Hyperspectral Data. Journal of Soil Science and Plant Nutrition 24:1, pages 1407-1423.
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Ronald B. Lockwood, Charles Bachmann, Michael Chrisp, Corrie Smeaton, Nima Pahlaven, Eric Hochberg, Marcos J. Montes, Bo-Cai Gao, Robert Frouin, Anthony Vodacek, Cedric Fichot, Tom W. Bell, Roy A. Armstrong, Chunyan Li, Laura Kennedy, Steven Gillmer, Linda Fuhrman, Derrick Brouhard, Jade Wang & Kurtis Thome. (2023) Aquatic ecosystems science using an imaging spectrometer. Aquatic ecosystems science using an imaging spectrometer.
Shuguang Liu, Zhenqi Hu, Jiazheng Han, Yuanyuan Li & Tao Zhou. (2022) Predicting grain yield and protein content of winter wheat at different growth stages by hyperspectral data integrated with growth monitor index. Computers and Electronics in Agriculture 200, pages 107235.
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Xueqin Jiang, Shanjun Luo, Qin Ye, Xican Li & Weihua Jiao. (2022) Hyperspectral Estimates of Soil Moisture Content Incorporating Harmonic Indicators and Machine Learning. Agriculture 12:8, pages 1188.
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Jia Jin & Quan Wang. (2022) Hyperspectral indices developed from the low order fractional derivative spectra can capture leaf dry matter content across a variety of species better. Agricultural and Forest Meteorology 322, pages 109007.
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Shu Ji, Chen Gu, Xiaobo Xi, Zhenghua Zhang, Qingqing Hong, Zhongyang Huo, Haitao Zhao, Ruihong Zhang, Bin Li & Changwei Tan. (2022) Quantitative Monitoring of Leaf Area Index in Rice Based on Hyperspectral Feature Bands and Ridge Regression Algorithm. Remote Sensing 14:12, pages 2777.
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Xueqin Jiang, Shanjun Luo, Shenghui Fang, Bowen Cai, Qiang Xiong, Yanyan Wang, Xia Huang & Xiaojuan Liu. (2021) Remotely sensed estimation of total iron content in soil with harmonic analysis and BP neural network. Plant Methods 17:1.
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