Soil properties could be identified at any depth using radar
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A team of scientists from RUDN University and the Dokuchyaev Soil Science Institute have developed a method for identifying the soil colour and structure at any depth using ground-penetrating radar. This allows for the identification of the chemical composition of soil without digging.
Colour is one of the key indicators of soil properties. Based on soil colour, it is possible to identify soil type, humus (fine organic matter) content, soil density, humidity, salinity, and other properties. For instance, black soil is rich in humus, while reddish tones indicate a high iron content.
In order to analyse soil colour, however, it is necessary to dig a soil section. Presenting an alternative to this labour-intensive process, Russian scientists have proposed using ground-penetrating radar (GPR) to determine soil colour at various depths.
“Colour is one of the main properties of soils that has been used for their classification for a long time; that is why many names of soils are associated with colour. Moreover, colour is an integral indicator of many other characteristics of soils,” said Professor Igor Savin of RUDN University. “Theoretically, this parameter could be measured with GPR. We wanted to confirm a correlation between colours of soil layers and GPR profiling data.”
Savin and his colleagues conducted an experiment in Kamennaya Steppe in Western Russia; this area is recognised for its large variety of soil types and is home to a soil research institute. The scientists probed the soils in seven sites with GPR and took 30 soil samples from each (at 10cm intervals down to a maximum depth of 3m). These soil samples were dried and ground to identify colour.
The DPR readings were compared with the soil sample colours, allowing the team to develop a correlation model. The colours calculated with the model matched the actual colours in 80 per cent of cases. This model could allow for the chemical composition of soils to be identified without digging, with applications spanning construction, agriculture, and mining.
Although the model is at present only applicable to this area (due to being calibrated based on the samples from Kamennaya Steppe), the researchers hope to adapt it to other areas.
“Our models cannot be used in territories with different soil coverings. However, it is not a disadvantage but rather a peculiarity of our method,” explained Savin. “To secure modelling accuracy, the model should include information about soil colours that are typical for the area of the study. In the initial stages, control soil sections would still have to be made using traditional methods.
“However, as soon as we accumulate enough field data, we would be able to eliminate this step, and no digging would be required to identify soil colour at any depth.”
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