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Geocarto International Volume 37, 2022 - Issue 3
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Original Articles

Dynamic modelling of rice leaf area index with quad-source optical imagery and machine learning regression models

Lamin R. Mansaraya Institute of Applied Remote Sensing and Information Technology, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, China;b Magbosi Land, Water and Environment Research Centre, Sierra Leone Agricultural Research Institute (SLARI), Freetown, Sierra LeoneCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0001-9250-3657View further author information
ORCID Icon,
Adam Sheka Kanuc Rokupr Agricultural Research Centre (RARC) Sierra Leone Agricultural Research Institute (SLARI), Freetown, Sierra LeoneView further author information
,
Lingbo Yanga Institute of Applied Remote Sensing and Information Technology, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, ChinaView further author information
&
Jingfeng Huanga Institute of Applied Remote Sensing and Information Technology, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, ChinaView further author information
Pages 828-840 | Received 17 Aug 2019, Accepted 29 Feb 2020, Published online: 03 Apr 2020

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Mahlatse Kganyago, Clement Adjorlolo, Mbulisi Sibanda, Paidamwoyo Mhangara, Giovanni Laneve & Thomas Alexandridis. (2022) Testing Sentinel-2 spectral configurations for estimating relevant crop biophysical and biochemical parameters for precision agriculture using tree-based and kernel-based algorithms. Geocarto International 0:0, pages 1-25.
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Lamin R. Mansaray, Adam Sheka Kanu, Lingbo Yang, Jingfeng Huang & Fumin Wang. (2020) Evaluation of machine learning models for rice dry biomass estimation and mapping using quad-source optical imagery. GIScience & Remote Sensing 57:6, pages 785-796.
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