International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Volume XLII-3/W10
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W10, 931–936, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W10-931-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W10, 931–936, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W10-931-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  08 Feb 2020

08 Feb 2020

INDIRECT ESTIMATION OF SOIL WATER CONTENT IN PLOUGH LAYER BASED ON TOPSOIL SPECTRUM

H. R. Zhai, X. C. Li, and H. Zhong H. R. Zhai et al.
  • College of Information Science and Engineering, Shandong Agricultural University, Tai'an, China

Keywords: Soil Water content, Hyperspectral Remote Sensing, Indirect Estimation, Estimation Model

Abstract. In order to estimate the soil water content of the plough layer using the surface soil spectrum, based on the water content data and hyperspectral data of 85 surface layers and ploughed soil samples in Jiyang County, Shandong Province, 10 transformation methods such as square root are used. The spectral reflectance of the topsoil is transformed, and the estimation factor is selected according to the principle of maximal correlation. Then, according to the correlation between the water content of the surface layer and the plough layer, two indirect estimation models are constructed.Six kinds of modeling methods such as multiple linear regression, partial least squares regression and support vector machine were used to estimate the soil water content of the cultivated layer, and the effectiveness of the two indirect estimation models was compared and analyzed. The results show that the decision coefficient R2 of the first mode is 0.8138, the average relative error is 9.6061% and the decision coefficient R2 of the second mode is 0.8115, the average relative error is 12.1403%. The researches show that it is feasible and effective to estimate the soil water content of the plough layer by using the surface soil spectrum. It provides a new idea for the rapid diagnosis of soil moisture and nutrients by using optical satellite remote sensing technology.