Abstract

Satellite data have been used for a long time to assess various properties of arable soils. At the same time, there are certain difficulties associated with the fact that a number of agronomically important soil properties do not directly affect spectral reflectance of their surface, which complicates the remote assessment of such properties. In addition, to obtain reproducible models, it is necessary to take into account the state of the open soil surface during the survey. The aim of the study was to demonstrate a method for detecting agronomically important properties of arable soils based on Landsat 8-9 OLI satellite data and including information about the state of their open surface using the example of a test field in the Serebryano-Prudsky district of the Moscow region. Depending on the soil property, R2cv of the models developed based on Landsat 8-9 OLI satellite data varied from 0.57 to 0.91. The best models with R2cv>0.8 were obtained for organic matter and properties higly correlated with it such as the content of exchangeable calcium and magnesium cations, the content of total nitrogen, pH of water and salt extracts. The involvement of information on the state of the open surface of arable soils for most properties made it possible to obtain models of higher quality and predictive ability, regardless of the survey period. Based on the models obtained, maps of the spatial variation of agronomically important properties of arable soils were constructed as part of the demonstration of the method. The resulting models can be used for remote monitoring of the analyzed properties of arable soils of the test field. At the same time, for such properties as the content of exchangeable potassium and phosphorus compounds, it is necessary to search for the approaches that will take into account their high variability, as well as to perform a prior assessment of the informativity of the survey periods in which the open soil surface is not transformed.

Full Text
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