探究高光谱重建技术对水稻生理参数定量反演的影响：使用MST++模型的案例研究

doi:10.1016/j.jia.2024.03.082

摘要/Abstract

摘要： 定量反演是遥感科学中的一个重要研究内容。基于可见光的高光谱重建技术的发展，为农业中的低成本、高精度遥感反演打开了新的前景。本研究旨在评估高光谱重建技术在农业遥感应用中的有效性。使用MST++高光谱重建模型重建了高光谱图像，并就它们与生理参数的相关性、单一特征建模的准确性以及组合特征建模的准确性，与原始可见光图像进行了比较。结果显示，与可见光图像相比，重建数据与生理参数的相关性更强，无论是单一特征还是组合特征反演模式，准确性都有所提高。然而，与多光谱传感器相比，高光谱重建在反演模型准确性上提供的改进有限。结果表明，对于不易直接观察的生理参数，通过高光谱重建技术对可见光数据进行深入特征挖掘，可以提高反演模型的准确性。适当的特征选择和简单模型更适合传统农艺小区实验的遥感反演任务。为了加强高光谱重建技术在农业遥感中的应用，需要进一步发展包括更广泛的波长范围和更多样的农业场景。

Abstract: Quantitative inversion is a significant topic in remote sensing science. The development of visible light-based hyperspectral reconstruction techniques has opened up novel prospects for low-cost, high-precision remote sensing inversion in agriculture. The aim of this study was to assesses the effectiveness of hyperspectral reconstruction technology in agricultural remote sensing applications. Hyperspectral images were reconstructed using the MST++ hyperspectral reconstruction model and compared with the original visible light images in terms of their correlation with physiological parameters, the accuracy of single-feature modeling, and the accuracy of combined feature modeling. The results showed that compared to the visible light image, the reconstructed data exhibited a stronger correlation with physiological parameters, and the accuracy was improved in both the single-feature and the combined feature inversion mode. However, compared to multispectral sensors, hyperspectral reconstruction provided limited improvement on the inversion model accuracy. It was concluded that for physiological parameters that are not easy to be directly observed, deep mining of features in visible light. data through hyperspectral reconstruction technology can improve the accuracy of the inversion model. Appropriate feature selection and simple models are more suitable for the remote sensing inversion task of traditional agronomic plot experiments. To strengthen the application of hyperspectral reconstruction technology in agricultural remote sensing, further development is necessary with broader wavelength ranges and more diverse agricultural scenes.

Key words: multistage spectral-wise transformer , hyperspectral reconstruction , , rice , , dry matter content , , height

. 探究高光谱重建技术对水稻生理参数定量反演的影响：使用MST++模型的案例研究[J]. Journal of Integrative Agriculture, DOI: 10.1016/j.jia.2024.03.082.

Weiguang Yang, Bin Zhang, Weicheng Xu, Shiyuan Liu, Yubin Lan, Lei Zhang. Investigating the impact of hyperspectral reconstruction techniques on the quantitative inversion of rice physiological parameters: A case study using the MST++ model[J]. Journal of Integrative Agriculture, DOI: 10.1016/j.jia.2024.03.082.

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