摘要
Vis-NIR光谱应用于野外土壤质地分析时,其分析精度将受到土壤含水量的影响。该文旨在定量研究基于Vis-NIR光谱对土壤质地分析时,土壤含水量对精度的影响。在实验室条件下分别测定8种不同含水量状态下土壤样品（78个）的Vis-NIR光谱反射率,运用偏最小二乘回归（PLSR）分别建立不同含水量状态下土壤质地分析模型,每一模型分别分析8种不同含水量状态下验证集的土壤质地。结果表明,当土壤处于同一湿度状态时,各含水量状态下均可获得较好的结果,粘粒含量和砂粒含量最佳分析模型对应的含水量分别为150-200g/kg和200-250g/kg。当土壤含水量差异较大时,分析精度随着验证样本与建模样本水分含量的差异增大而急剧降低。研究认为,当土壤处于同一湿度状态时,可直接应用Vis-NIR光谱分析湿土的土壤质地,在土壤水分状态差异较大时,宜根据含水量建立分组分析模型。
Soil moisture may influence the accuracy of analysis of soil texture when directly using Vis-NIR spectroscopy in the field. To demonstrate the effect of soil moisture on the analysis accuracy, reflection spectra of 78 soil samples were obtained in the laboratory under eight moisture conditions, and the prediction models for each moisture conditions were built using partial least-squares regression. Each model then applied to the eight validation sets with various moisture conditions to explore the effect of different soil moisture on the analysis accuracy. Results show that analysis models for each moisture condition performant well with acceptable prediction accuracy when it is applied to the validation set under the same moisture conditions with the calibration set, and the best model of clay content and sand content occur when soil water content is 150-200 g/kg, 200- 250 g/kg, respectively. However, the accuracy decreased dramatically with the increase of difference on soil moisture conditions between the built data set and validation data set. Spectroscopy could be directly used to analysis soil texture on moist samples that with the similar soil moisture condition. Separate models under the same soil moisture condition should he established to improve the analysis accuracy when soil moisture content shows a large difference.
出处
《地理与地理信息科学》
CSCD
北大核心
2015年第6期52-55,共4页
Geography and Geo-Information Science
基金
国家自然科学基金资助项目(41201210)
