Combined use of laboratory-based and portable infrared and x-ray fluorescence spectroscopy approaches for the spatial-vertical characterization of samples of selected soil groups

基于传感器的土壤监测采用红外光谱法（维斯/近红外光谱法、MIRS法）和能量色散X射线荧光光谱法（XRF法），可以量化土壤特性，这些特性对于以高空间和时间分辨率推导和评估土壤功能至关重要。然而，收集和评估在实验室为基础的和便携式传感器为基础的方法尚未优化，使其难以严格评估的可能性和局限性，这些methods.This建议旨在优化IR和XRF数据收集光谱活性土壤属性使用基于实验室的和便携式的方法为代表的土壤类型复杂的选定的土壤景观。在测量模式（漫反射红外傅里叶变换与MIRS的衰减全反射，粉末与XRF的颗粒）、样品制备（原位、干燥、干燥和筛分、干燥和研磨）、测量条件和所需样品数量方面，对各个方法进行了优化。在所研究的样品剖面中定义了不同土壤性质的特定深度函数，并对维斯/近红外光谱、中红外光谱和X射线荧光光谱定量土壤光谱活性性质的校准算法进行了系统的比较。将采用线性和非线性校准方法以及光谱去卷积作为多个分区中不同样本量的函数。将使用现有数据库进行光谱变量选择和加标。便携式和实验室为基础的光谱方法，以及潜在的可转移性校准的估计模型的土壤剖面表征的准确性将进行系统的研究个别剖面的研究土壤类型复合体。光谱活性和光谱非活性或光谱定义不明确的土壤性质之间的特定场地关系的分析将通过化学计量和回归分析进行，使用光谱活性土壤性质作为预测因子。使用基于实验室的方法和移动的方法的协同IR和XRF数据分析将基于低、中、高水平以及混合数据融合方法，重点是外产物分析、低水平融合以及随后的自动波长范围选择，使用主成分的中级融合和使用贝茨-格兰杰和格兰杰方法的高级融合-该项目提供了优化基于传感器的土壤监测数据收集的工具，通过数据融合方法提高不同复杂土壤特性的确定精度，并评估与空间和剖面相关的基于传感器的监测对选定土壤类型复合体的适用性。

Sensor-based soil monitoring, which uses infrared spectroscopic (IR) approaches (Vis/NIRS, MIRS) and energy dispersive X-ray fluorescence spectroscopy (XRF), can quantify soil properties that are essential to derive and evaluate soil functions in high spatial and temporal resolutions. However, collection and evaluation in laboratory-based and portable sensor-based methods have not yet been optimised, making it difficult to critically assess possibilities and limitations of these methods.This proposal aims at optimising the IR and XRF data collection for spectrally-active soil properties using laboratory-based and portable methods for representative soil type complexes of selected soil landscapes. The individual methods are optimised with regard to measuring modes (diffuse reflectance infrared Fourier transform vs. attenuated total reflection for MIRS, powder vs. pellets for XRF), sample preparation (in-situ, dried, dried and sieved, dried and ground), measuring conditions and required sample numbers. Specific depth functions for the different soil properties will be defined in the studied sample profiles.A systematic comparison of calibration algorithms for the quantification of spectrally-active soil properties by Vis/NIRS, MIRS and XRF will be performed. Linear and non-linear calibration approaches and spectral deconvolution will be employed as functions of different sample sizes in multiple partitions. Spectral variable selection and spiking using existing databases will be used. The accuracy of soil profile characterisation by portable and laboratory-based spectroscopic methods as well as a potential transferability of calibrated estimation models will be systematically investigated on individual profiles of the studied soil type complexes. The analysis of site-specific relationships between spectrally-active and spectrally-inactive or spectrally poorly-defined soil properties will be performed both chemometrically and by regression analyses using the spectrally-active soil properties as predictors. The synergistic IR and XRF data analysis using the laboratory-based and mobile approaches will be based on low-, mid- and high-level as well as hybrid data fusion approaches with an emphasis on outer-product analysis, low-level fusion with subsequent automatic wavelength range selection, mid-level fusion using the principal components and high-level fusion using the approaches of Bates-Granger and Granger-Ramanathan.This project provides the tools with which to optimize the data collection of sensor-based soil monitoring, to improve the determination accuracy of differently complex soil properties by data fusion approaches, and to evaluate the applicability of a spatial and profile-related sensor-based monitoring for selected soil type complexes.