非均质中低分辨率像元土壤含水量地面采样方法研究进展

Ground sampling strategy for surface soil moisture in heterogeneous remote sensing pixels

在一定的精度条件下,如何通过合理的地面采样方法获取非均质混合像元的地面真值,是遥感准确反演土壤含水量需要解决的基本问题。目前常用的地面传统采样方法包括传统统计采样、自助采样、随机组合采样、地统计采样、分层采样、稳定性采样,都需要地面较密集的实测数据才能获得合理的采样方案,然而,在实际中,中低分辨率尺度很难进行地面预采样,传统地面采样方法很难满足区域尺度土壤含水量的地面采样需求。基于先验知识的地面采样方法由于不需要地面较密集的实测数据,已成为中低分辨率像元土壤含水量地面采样的新热点。综合分析土壤含水量不同地面采样方法的特点和优势以及采样方法的适用条件,为土壤含水量反演算法模型的构建和产品的真实性检验提供科学的地面采样参考依据。

The most important question is how to select reasonable ground sampling method to obtain the mean soil moisture within the mixed pixels. Some traditional sampling methods, including traditional statistical sampling, self-sampling, random sampling, geostatistical sampling, stratified sampling and temporal stability, all need to be more intensive ground measured data in order to obtain a reasonable sampling plan. However, in practice, it is very difficult to make the ground pre sampling in the regional scale, so the traditional sampling methods can hardly meet the requirement of the soil moisture monitoring. In recent years, the priori knowledge ground-based sampling method has become a widely used sampling method without the more intensive measured data. The priori knowledge ground soil sampling will be important in future research and development direction. The characteristics, advantages and the applicable conditions of different ground sampling methods were analyzed, which will provide the basis for the construction of the algorithm model and the validation of the soil moisture products.