土壤养分浓度高光谱相机向常规光谱仪定标转移研究

摘要：仪器间的定标转移主要针对普通光谱仪之间的定标转移，目前关于土壤养分浓度从高光谱相机到普通光谱仪的定 标转移研究较少。本文采集了青岛市3个地区164个土壤样品，分别获取普通光谱仪和高光谱相机的光谱数据以及总碳、 氮浓度。然后，利用普通光谱仪的光谱数据建立土壤总碳、氮含量模型。采用单一常规定标转移算法、多种定标转移算 法组合以及经过光谱预处理后的定标转移算法等多种方法对高光谱数据进行转移。利用普通光谱仪建立的总碳、总氮浓 度模型对转移后的高光谱数据进行预测。采用绝对系数𝑅2和预测值的均方根误差（（RMSEP）评价定标转移后的预测性能。 𝑡 尝试了多种校准传递方法后，Repfile-PDS和RepfileSNV方法的校准传递预测性能最好。Repfile-PDS方法的校准传递中， 当PDS窗口数为27、标准数据数为40时，TC浓度的R2t和RMSEP分别为0.627和2.351；当PDS窗口数为25、标准 数据数为100时，TN浓度的R2t和RMSEP分别为0.666和0.297；Repfile-SNV方法的校准传递中，当TC和TN标准 数据数为120时，𝑅2最大，分别为0.701和0.722，RMSEP分别为2.880和0.399。通过以上算法对高光谱数据进行定标 𝑡 转移后，再利用普通光谱仪建立的土壤TC、TN浓度模型进行预测，可以得到较好的预测效果。解决土壤养分浓度从高 光谱相机到普通光谱仪的定标转移，为利用高光谱相机采集的大量图像信息数据的快速预测提供了有力的依据，大大减 少了工作量，促进了高光谱相机在定量分析和快速测量技术中的应用。

期刊：Journal of Spectroscopy

DOI：https://DOI.org/10.1155/2020/8137142

设备：GaiaField

Study on the Calibration Transfer of Soil Nutrient Concentration from the Hyperspectral Camera to the Normal Spectrometer

Abstract：The calibration transfer between instruments is mainly aimed at the calibration transfer between normal spectrometers. There are few studies on the calibration transfer of soil nutrient concentration from a hyperspectral camera to a normal spectrometer. In this paper, 164 soil samples from three regions in Qingdao, China, were collected. /e spectral data of normal spectrometer and hyperspectral camera and the concentration of total carbon and nitrogen were obtained. And then, the models of soil total carbon and nitrogen content were established by using the spectral data of a normal spectrometer. hyperspectral data were transferred by a variety of methods, such as single conventional calibration transfer algorithm, combination of multiple calibration transfer algorithms, and calibration transfer algorithm after spectral pretreatment. transferred hyperspectral data were predicted by the total carbon and total nitrogen concentration model established by using a normal spectrometer. /e absolute coefficients 𝑅2 and root 𝑡 mean square error of prediction (RMSEP) were used to evaluate the prediction performance after calibration transfer. After trying many calibration transfer methods, the prediction performance of calibration transfer by the Repfile-PDS and RepfileSNV methods was the best. In the calibration transfer of the Repfile-PDS method, when the number of PDS windows was 27 and the number of standard data was 40, the 𝑅2 and the RMSEP of TC concentration were 0.627 and 2.351. When the number of PDS windows was 𝑡 25 and the number of standard data was 100, the 𝑅2and the RMSEP of TN concentration were 0.666 and 0.297. In the calibration 𝑡 transfer of the Repfile-SNV method, when the number of TC and TN standard data was 120, the 𝑅2was the largest, 0.701 and 𝑡 0.722, respectively, and the RMSEP was 2.880 and 0.399, respectively. After the hyperspectral data were calibration transferred by the above algorithms, they could be predicted by the soil TC and TN concentration model established by using a normal spectrometer, and better prediction results can be obtained.solution of the calibration transfer of soil nutrient concentration from the hyperspectral camera to the normal spectrometer provides a powerful basis for rapid prediction of a large number of image information data collected by using a hyperspectral camera. It greatly reduces the workload and promotes the application of hyperspectral camera in quantitative analysis and rapid measurement technology.