Transformation of the Surface Layer in the Arable Soil Horizon under the Impact of Atmospheric Precipitation

Prudnikova, E. Yu.; Savin, I. Yu.; Лебедева, М. П.; Volkov, Dmitry S.; Rogova, Olga B.; Варламов, Е. Б.; Абросимов, К. Н.

doi:10.1134/s1064229321110119

Cited by 4 publications

(2 citation statements)

References 27 publications

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“…Even though the finest soils are being occupied, the good soils are the first prisoners of urban development, 13 no matter what management level 14 . It is not uncommon for urban growth to take advantage of the most excellent soils available 15,16 . Most of the world's largest cities are on flood plains, productive agricultural areas.…”

Section: Introductionmentioning

confidence: 99%

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An optimized deep network based soil texture prediction and vegetation analysis using satellite image database

Anand

Jain

Shukla

2023

Concurrency and Computation

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Summary The usage of satellite images has grown rapidly in digital applications. Predicting features in the satellite images using conventional techniques is not an easy task as the images captured from satellites are more complex with highly noisy features. Hence, traditional imaging algorithms cannot analyze the image features and specify the soil textures. In this work, the Tarakeswar satellite images were taken to estimate the soil textures and crops yielding. Hence, to find the soil's chemical properties and suitable crops, the novel bat‐based U‐Net feature prediction system (BUFPS) was developed with the required features. The imported satellite images were initially filtered and entered into the classification phase to forecast the present chemical features and suitable crops in specific soils. After detecting the chemical features, soil textures like sandy, silt, and clay were categorized; the crops like jute, rice, lentil, and potato were considered. Finally, the planned model is executed in the MATLAB environment and has gained outstanding results by achieving the lowest error rate of 8% and a high prediction score of 92%. The proposed model has achieved exact soil texture analysis for complex satellite images. The gained texture analysis outcome is quite better than other existing models.

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Section: Introductionmentioning

confidence: 99%

“…14 It is not uncommon for urban growth to take advantage of the most excellent soils available. 15,16 Most of the world's largest cities are on flood plains, productive agricultural areas. Hence, predicting the soil texture is an important task.…”

Section: Introductionmentioning

confidence: 99%

An optimized deep network based soil texture prediction and vegetation analysis using satellite image database

Anand

Jain

Shukla

2023

Concurrency and Computation

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Soil dust aerosol in the atmosphere: sources, quantities, properties (overview)

Romanovskaya

Savin

2021

DSB

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Dust is a major component of atmospheric aerosols – 75% of the global aerosol load. Natural and anthropogenic sources are listed, as well as dust research methods. According to different estimates, the average mineral dust load in the atmosphere ranges from 20 to 33 Tg, and the annual dust emission is 1 200–5 900 Tg/year. Reports from the Intergovernmental Panel on Climate Change (IPCC) inform about the total direct radiative forcing of dust ranging from -0.56 to +0.1 W/m2, with little scientific understanding of the processes leading to this result. The particle size, including soil aerosol, is divided into fine (<5 μm), medium (5–10(20) μm) and coarse (>20 μm) dust. Fine dust cools the global climate due to dispersion of solar radiation, while coarse dust (greater than 5 μm) warms the climate by absorbing solar and thermal radiation. However, the coarse dust (above 20 μm) remains poorly investigated, with very little data on its content and emission. Recent studies suggest that coarse dust (17 Tg), missed by the global models, contributes on average 0.15 W/m2 (0.10 to 0.24 W/m2) to atmospheric heating and also affects the global distribution of clouds and precipitation. In addition, soil dust is characterised by a complex and diverse particle shape and structure, heterogeneous mineralogical and chemical composition; due to its dispersion ability and large surface area dust reacts with other types of aerosols, resulting in the formation of different films on the particle surface or internal mixing. All this significantly changes the optical properties of mineral dust and complicates the development of models for its investigation.

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Peculiarities of spectral reflectance of fractions with sizes from 20 to 5,000 microns in soil samples

Savin

Shishkin

Sharychev

2022

DSB

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By the example of arable horizon samples taken from three soil types (sod-podzolic, gray forest, and leached chernozem) the peculiarities of electromagnetic waves reflection from their different particle size fractions were studied. The extraction of fractions by dry sieving was carried out using Retsch AS 200 BASIC equipment. As a result, 14 fractions ranging in size from less than 20 microns to more than 5,000 microns were isolated. Spectral reflectance was determined for each fraction and for the soil sample before sieving in the electromagnetic wave range from 350 to 2,500 nm using a SR-6500 field spectroradiometer (Spectral Evolution, USA). Analysis of similarities and differences in the obtained spectral reflectance curves of individual fractions was carried out using their visual analysis, the method of similarity dendrogram construction, as well as regression analysis between light reflectance and fraction particle size. It was confirmed that at a more detailed level of analysis compared to the one carried out by other researchers earlier, the general patterns of light reflectance of the samples do not change. A higher reflection of waves by thinner fractions and a lower reflection by more coarse fractions are observed. At the same time, spectral reflection curves for individual fractions are out of the general pattern, the level of intensity of local extremes of the curves’ changes. This confirms the difference of the material composition, which forms the color of soils, of these fractions from others. The color of the mixed sample is a spectral mixture of colors of its separate fractions. Presumably, this is the main reason for such a phenomenon as change of spectral reflectivity of open surface of soils under the influence of atmospheric precipitation.

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Transformation of the Surface Layer in the Arable Soil Horizon under the Impact of Atmospheric Precipitation

Cited by 4 publications

References 27 publications

An optimized deep network based soil texture prediction and vegetation analysis using satellite image database

An optimized deep network based soil texture prediction and vegetation analysis using satellite image database

Soil dust aerosol in the atmosphere: sources, quantities, properties (overview)

Peculiarities of spectral reflectance of fractions with sizes from 20 to 5,000 microns in soil samples

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