Research on the Quantitative Inversion of Soil Iron Oxide Content Using Hyperspectral Remote Sensing and Machine Learning Algorithms in the Lufeng Annular Structural Area of Yunnan, China

Research on the Quantitative Inversion of Soil Iron Oxide Content Using Hyperspectral Remote Sensing and Machine Learning Algorithms in the Lufeng Annular Structural Area of Yunnan, China

This study used hyperspectral remote sensing to rapidly, economically, and non-destructively determine the soil iron oxide content of the Dinosaur Valley annular tectonic region of Lufeng, Yunnan Province. The laboratory determined the iron oxide content and original spectral reflectance (OR) in 138...

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Bibliographic Details
Main Authors: Yingtao Qi, Shu Gan, Xiping Yuan, Lin Hu, Jiankai Hu, Hailong Zhao, Chengzhuo Lu
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Sensors
Subjects:
soil
hyperspectral
iron oxide
characteristic wavelength selection
XGBoost model
Online Access:https://www.mdpi.com/1424-8220/24/21/7039
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