Preliminary Results in Innovative Solutions for Soil Carbon Estimation: Integrating Remote Sensing, Machine Learning, and Proximal Sensing Spectroscopy

Autor: Tong Li, Anquan Xia, Timothy I. McLaren, Rajiv Pandey, Zhihong Xu, Hongdou Liu, Sean Manning, Oli Madgett, Sam Duncan, Peter Rasmussen, Florian Ruhnke, Onur Yüzügüllü, Noura Fajraoui, Deeksha Beniwal, Scott Chapman, Georgios Tsiminis, Chaya Smith, Ram C. Dalal, Yash P. Dang

Publikováno v: Remote Sensing, Vol 15, Iss 23, p 5571 (2023)

This paper explores the application and advantages of remote sensing, machine learning, and mid-infrared spectroscopy (MIR) as a popular proximal sensing spectroscopy tool in the estimation of soil organic carbon (SOC). It underscores the practical i

Externí odkaz: https://doaj.org/article/9961b1d8a48c4b2680f3a6b91a333502

Preliminary Results in Innovative Solutions for Soil Carbon Estimation: Integrating Remote Sensing, Machine Learning, and Proximal Sensing Spectroscopy.

Autor: Li, Tong^1,2 (AUTHOR) zhihong.xu@griffith.edu.au, Xia, Anquan³ (AUTHOR), McLaren, Timothy I.¹ (AUTHOR), Pandey, Rajiv⁴ (AUTHOR), Xu, Zhihong² (AUTHOR), Liu, Hongdou² (AUTHOR), Manning, Sean⁵ (AUTHOR), Madgett, Oli⁶ (AUTHOR) oli@getfarmlab.com, Duncan, Sam⁶ (AUTHOR) sam@farmlab.com.au, Rasmussen, Peter⁶ (AUTHOR), Ruhnke, Florian⁶ (AUTHOR), Yüzügüllü, Onur⁷ (AUTHOR), Fajraoui, Noura⁷ (AUTHOR), Beniwal, Deeksha⁵ (AUTHOR), Chapman, Scott¹ (AUTHOR), Tsiminis, Georgios⁵ (AUTHOR), Smith, Chaya⁵ (AUTHOR), Dalal, Ram C.¹ (AUTHOR), Dang, Yash P.¹ (AUTHOR) y.dang@uq.edu.au

Publikováno v: Remote Sensing. Dec2023, Vol. 15 Issue 23, p5571. 17p.