Methodology for Regional Soil Organic Matter Prediction with Spectroscopy: Optimal Sample Grouping, Input Variables, and Prediction Model

Methodology for Regional Soil Organic Matter Prediction with Spectroscopy: Optimal Sample Grouping, Input Variables, and Prediction Model

Soil organic matter (SOM) is an essential component of soil and is crucial for increasing agricultural production and soil fertility. The combination of hyperspectral remote sensing and deep learning can be used to predict the SOM content efficiently, rapidly, and cost-effectively on various scales....

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Bibliographic Details
Main Authors: Xinle Zhang, Chang Dong, Huanjun Liu, Xiangtian Meng, Chong Luo, Yongqi Han, Hongfu Ai
Format: Article
Language:English
Published: MDPI AG 2024-01-01
Series:Remote Sensing
Subjects:
soil organic matter
hyperspectral
deep learning
grouping approach
Online Access:https://www.mdpi.com/2072-4292/16/3/565

Internet

https://www.mdpi.com/2072-4292/16/3/565

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