A method and system for soil organic carbon and spectral coupling generation model

CN122113626APending Publication Date: 2026-05-29CHINA AGRI UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
CHINA AGRI UNIV
Filing Date
2026-02-24
Publication Date
2026-05-29

AI Technical Summary

Technical Problem

Existing soil organic carbon monitoring models lack applicability in the field and cross-regional transmission. Physical model parameters are difficult to measure, and data-driven methods lack physical constraints, making it impossible to achieve bidirectional dynamic verification of SOC and spectra.

Method used

A coupled generation model of soil organic carbon and spectral parameters is constructed. A two-stage hybrid optimization algorithm and a random forest algorithm are used, combined with global soil vector theory and brightness-shape transformation to separate the spectral brightness and shape effects, so as to realize the bidirectional mapping between SOC content and spectral morphology parameters. Hyperparameters are determined by Bayesian optimization, and spectral parameters are optimized by an improved genetic algorithm and a trust region reflection algorithm.

Benefits of technology

It achieves a bidirectional reversible mapping between SOC content and soil spectrum, with no significant spectral deviation when applied across regions. The model logic is anchored to the physical mechanism, improving parameter solution efficiency and monitoring accuracy, and is suitable for large-scale soil carbon monitoring.

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Abstract

The application discloses a kind of soil organic carbon and spectral coupling generation model method and system, belong to soil remote sensing monitoring technical field.The method includes five core steps of data preprocessing, dry soil spectrum fitting, SOC mapping model construction, morphological parameter generation, spectral reconstruction and bidirectional verification.Brightness-shape-humidity (BSM) theoretical framework separates spectral brightness and shape effect, fuses random forest algorithm and double-stage hybrid optimization model, and constructs the bidirectional reversible mapping system between spectral morphological parameter and SOC content.The application breaks through the limitation of traditional technology one-way inversion, can be based on soil spectrum high-precision inversion SOC content, and can also generate high-fidelity soil spectrum according to target SOC content, has physical explainability and data-driven flexibility, solves the technical problems of cross-regional spectral deviation and lack of explainability, and provides reliable tool for soil carbon cycle remote sensing monitoring.
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