基于实测数据及遥感图片的土壤采样方法

    Soil sampling method based on field measurements and remote sensing images

    • 摘要: 如何结合土壤特性和先进手段,制定具有代表性,同时又经济的土壤采样方案一直是土壤分析的难题。该文根据陕西省卤泊滩盐碱地改良区土壤含盐量的实测资料和相应的遥感图片数据,并结合土壤属性空间分布特性,提出一种新的土壤水盐含量采集方案。结果表明,用33个已知点的实测数据可以估算出101个未测点的含量并最终构成插值343个点的空间分布图,且水分与盐分含量预测结果相关的确定系数分别为0.869和0.817。在此基础上进而对工程改良措施下的卤泊滩盐渍土表层水盐空间变异性进行研究。分析结果表明,研究区土壤水盐含量具有中等较强的空间自相关性和较弱的变异性。通过对该地区水盐空间变异性的研究可以及时了解盐渍地试验区的改良效果及水资源管理情况。

       

      Abstract: Seeking a representative and economical soil sampling solution that combines soil properties with advanced technologies has been a difficult task in soil related studies. A new method for soil sampling was presented based on measured soil moisture and salinity data, remote sensing images and analysis of spatial distributions of soil properties in Lubotan land reclamation area in Shaanxi, China. The results showed that with the available data sets of 33 points, up to 101 unknown points could be estimated, and further interpolation of 343 points displayed spatial distribution of soil salinity in the study area. The coefficients of determination (R2) for the predicted soil moisture and soil salinity were 0.867 and 0.817, respectively. Furthermore, Kriging analysis for top soil salinity distribution in the study area showed that soil salinity had a medium degree of autocorrelation and low variability. This study may provide timely understanding of soil reclamation efforts and local water management practice.

       

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