Synergetic use of mobile and lab-based spectroscopic techniques (vis-NIR, lab and hand-held MIR, portable hyperspectral frame camera) to optimize the determination of soil properties with high variability in time and space

协同使用移动和实验室光谱技术（可见近红外、实验室和手持式中红外、便携式高光谱框架相机），以优化时间和空间变化较大的土壤特性的测定

• 批准号: 387000394
• 负责人: Professor Dr. Bernard Ludwig
• 金额: --
• 依托单位: Institut für Geographie
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2017
• 资助国家: 德国
• 起止时间: 2016-12-31 至 2021-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/387000394?language=en
• 关键词: Synergetic; use; mobile; lab; based

Total contents of soil organic carbon (SOC), nitrogen (N) and phosphorus (P) are only of limited use for studies of management (e.g. fertilizations or tillage) on soil fertility; SOC and N fractions as well as soil microbial properties are much more sensitive indicators. However, a high spatial and temporal density of samples can only be achieved with non-destructive sampling techniques. In this context, the project studies the potentials of spectroscopic techniques to determine key soil properties (SOC, N, pH, fractions of SOC and N, P, sulphur, potassium, iron, cation exchange capacity, soil texture, microbial and hot water-soluble C and N) with high accuracy by combining non-imaging spectroscopy in the near and middle (vis-NIR and MIR) domain with hyperspectral imaging. In addition to the lab scale, we focus on the field scale with on-site spectroscopic measurements, which is favoured by new instrumental developments, a portable MIR spectrometer and a portable hyperspectral frame camera. The MIR range is essential for soil spectroscopy, as fundamental bands of chemical groups can be measured (different from the NIR range with only combination bands and overtones). For a total of eight arable sites with soils of differing textures, top soils and soil profiles will be sampled to investigate the potentials of lab spectroscopy compared to on-site spectroscopy by combining the different spectroscopic techniques for the estimation of the soil properties mentioned above. To improve obtained accuracies, methods of multivariate calibration will be optimized by using e.g. Support Vector Machines or Random Forest instead of PLSR, by applying spectral variable selection techniques, by substituting global by local calibrations (i.e., a sample-wise selection of appropriate calibration samples is performed) and by using the approach of spiking to locally adapt calibration models. The optimized techniques will then be validated on existing data sets. Additionally, it will be analysed, whether and to what extent disturbances originating from different soil surface roughness or from different soil water contents can be compensated. Already existing soil spectral libraries (LUCAS, ICRAF-ISRIC) are evaluated to select appropriate samples which may support the definition and optimization of calibration models. In addition, the underlying spectral predictive mechanisms will be analysed (e.g., by 2D-correlation spectroscopy) to elucidate whether a direct or only indirect spectral prediction is feasible for each of the studied soil properties. This is fundamental to clarify whether a prediction model, once calibrated, may be in principle transferred in space and time.

土壤有机碳（SOC），氮（N）和磷（P）的总含量仅在土壤肥力研究（例如肥料或耕作）的研究中有限； SOC和N部分以及土壤微生物特性是更敏感的指标。但是，只有通过非破坏性抽样技术才能实现样品的高空间密度和时间密度。在这种情况下，该项目研究了光谱技术的潜力，以确定SOC，N，pH，pH，SOC和N，N，P，P，P，硫，钾，铁，阳离子交换能力，土壤质地，微生物和热水溶质C和N的潜在，通过在近距离和中间（vissir）（vissir）中（访问NIR）结合非准确性（和无数）（均）和niriir（viss）。除了实验室量表外，我们还通过现场光谱测量值专注于现场尺度，该测量值受到新的仪器开发，便携式mir光谱仪和便携式高光谱框架摄像头的青睐。 miR范围对于土壤光谱是必不可少的，因为可以测量化学基的基本带（与仅组合带和泛音的NIR范围不同）。对于八个具有不同纹理的土壤的可耕地，将对顶部的土壤和土壤剖面进行采样，以研究实验室光谱的潜力与现场光谱相比，通过将不同的光谱技术结合以估计上述土壤性能的估计。为了提高获得的准确性，将使用例如使用例如通过应用频谱变量选择技术，通过局部校准替换全局（即执行适当的校准样品的样本选择），并通过使用SPIKING对局部适应校准模型来替换全局。然后，将在现有数据集上验证优化的技术。此外，将分析它，无论是源自不同土壤表面粗糙度还是来自不同土壤水含量的干扰。评估已经存在的土壤光谱库（Lucas，ICRAF-ISRIC）以选择可以支持校准模型的定义和优化的合适样品。此外，将分析潜在的光谱预测机制（例如，通过2D相关光谱法）阐明直接或仅间接光谱预测对于每个研究的土壤特性都是可行的。这是澄清一旦校准的预测模型的基础，这是否可能是在时空中转移的。