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International Journal of Remote Sensing Volume 42, 2021 - Issue 5
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Research Article

New empirical backscattering models for estimating bare soil surface parameters

S. Mohammad Mirmazloumia Geomatics Division, Centre Tecnològic De Telecomunicacions De Catalunya (CTTC/CERCA), Castelldefels, SpainCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0001-5310-5859
ORCID Icon,
Mahmod Reza Sahebib Faculty of Geodesy and Geomatics Engineering & Remote Sensing Institute, K. N. Toosi University of Technology, Tehran, IranORCID Iconhttps://orcid.org/0000-0001-7742-3974
ORCID Icon &
Meisam Amanic Wood Environment & Infrastructure Solutions, Ottawa, ON, CanadaORCID Iconhttps://orcid.org/0000-0002-9495-4010
ORCID Icon
Pages 1928-1947 | Received 29 Apr 2020, Accepted 19 Oct 2020, Published online: 20 Dec 2020

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Farzane Mohseni, Amirhossein Ahrari, Jan-Henrik Haunert & Carsten Montzka. (2023) The synergies of SMAP enhanced and MODIS products in a random forest regression for estimating 1 km soil moisture over Africa using Google Earth Engine. Big Earth Data 0:0, pages 1-25.
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Articles from other publishers (2)

Abhilash Singh, Kumar Gaurav, Atul Kumar Rai & Zafar Beg. (2021) Machine Learning to Estimate Surface Roughness from Satellite Images. Remote Sensing 13:19, pages 3794.
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Dexin Meng, Jianwei Ma, Jingfeng Xin, Yayong Sun, Shifeng Huang & Furong Zhang. (2021) Estimation of soil moisture with SAR data in large area based on support vector regression. Estimation of soil moisture with SAR data in large area based on support vector regression.

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