Assessment of Soil Cover Contrasts on Arable Land Using Sentinel-2 Images

It is proposed to identify the hierarchy of federal districts in terms of ecological opportunities for consolidation of vegetation cover according to three classes of soil cover according to the UN classification (grass + shrub + trees) on the land territory of Russia by ranking the shares of vegetation cover and human-modified lands, as well as ecological coefficients. The total ecological coefficient is calculated by dividing the share of vegetation by the total share of anthropogenic land. The forest-agricultural coefficient is convenient as the ratio of the forest area to the arable land area. The identification method revealed stable regularities of rank distributions in the form of trends and wave equations.

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Digital modeling of erosion soil cover patterns development over the last 300 years (Moscow region, Russia)

10.5194/egusphere-egu2020-969 ◽

2020 ◽

Author(s):

Daria Fomicheva ◽

Andrey Zhidkin

Keyword(s):

Land Use ◽

Soil Erosion ◽

Crop Rotation ◽

Soil Loss ◽

Soil Cover ◽

Field Survey ◽

Arable Land ◽

Digital Modeling ◽

History Of ◽

Last 300 Years

Digital modeling of soil erosion has been actively developed in recent decades, including for solving practical problems of agriculture. This paper presents a new approach to mapping the degree of erosion of the soil cover based on a detailed retrospective analysis of the history of land use over the last 300 years.The study site is located in the Moscow region, characterized by a stage history of plowing. The analysis of the boundaries of arable land was carried out using the digitization of maps for 1797, 1860, 1871, 1931, 1954, 1985, 2000 and 2018 years.Erosion processes were simulated using the WATEM / SEDEM. LS factor was calculated based on a digital elevation model based on the digitized detail topographic map. Soil erodibility factor was calculated according to the formula [1] based on our own analytical data on soil properties (K=0.065&#8211;0.090 kg*h*MJ-1mm-1). The rain erosivity factor was taken from the [2]. The crop erosivity factor was taken from regional data, taking into account a detailed analysis of the history of crop rotation.Soil erosion was calculated for each of 8 periods. Estimated rates were multiplied by the duration of the periods. The soil loss volumes were summarized using the raster calculator. The authors have database of soil surveys at 1567 points. The obtained estimated long-term volumes of soil loss were correlated with the data of a field survey of soils. Based on the obtained dependencies between the calculated soil loss volumes and the field survey data, a map of the erosion soil cover structures was constructed.In the territory, the volume of soil loss varied from 0.02 tons to 1170 tons. The average volume of soil loss over 300 years was about 63.33 tons. It was revealed that the volume of soil loss is determined not only by the area of &#226;&#128;&#139;&#226;&#128;&#139;arable land, but also by the location and topography of the plowed plots and the composition of crop rotation. The most intense erosion was observed in the first decades after the abolition of serfdom law (after 1860).Despite the long period of land use, the soil cover of the study area is not very eroded, primarily due to the low erosion potential of the relief. However, the territory is divided into sections, to a different degree, transformed by soil erosion due to plowing of different duration and the composition of crop rotation.This work was supported by the Russian Foundation for Basic Research (project for young scientists no. 18-35-20011)[1] Renard K., Foster G., Weesies G., McCool D., Yoder D. (1997) Predicting soil erosion by water: a guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE). USDA Agriculture Handbook &#226;&#132;&#150;703, 384 p.[2] Panagos P, Borrelli P, Meusburger K, et al. Global rainfall erosivity assessment based on high-temporal resolution rainfall records. Sci Rep. 2017;7(1):4175.

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Ecological consolidation of lands and federal districts in Russia

10.33920/sel-04-2109-07 ◽

2021 ◽

Author(s):

P.M. Mazurkin

Keyword(s):

Vegetation Cover ◽

Wave Equations ◽

Soil Cover ◽

Arable Land ◽

Forest Area ◽

Land Area ◽

Identification Method ◽

Federal Districts ◽

Rank Distributions

It is proposed to identify the hierarchy of federal districts in terms of ecological opportunities for consolidation of vegetation cover by three classes of soil cover according to the UN classification (grass + shrub + trees) on the territory of Russia by ranking the shares of vegetation cover and human-modified lands, as well as ecological coefficients. The total ecological coefficient is calculated by dividing the share of vegetation by the total share of anthropogenic land. The forest-agricultural coefficient is convenient as the ratio of the forest area to the arable land area. The article contains the identification method revealing stable regularities of rank distributions in the form of trends and wave equations.

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Testing the spatial significance of weed patterns in arable land using Mead?s test

Weed Research ◽

10.1111/j.1365-3180.2007.00577.x ◽

2007 ◽

Vol 47 (5) ◽

pp. 396-405 ◽

Cited By ~ 9

Author(s):

S HEIJTING ◽

W VAN DER WERF ◽

W KRUIJER ◽

A STEIN

Keyword(s):

Arable Land ◽

Land Using

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Degradation of Arable Soils in Central Yakutia: Negative Consequences of Global Warming for Yedoma Landscapes

Frontiers in Earth Science ◽

10.3389/feart.2021.683730 ◽

2021 ◽

Vol 9 ◽

Author(s):

Roman Desyatkin ◽

Nikolai Filippov ◽

Alexey Desyatkin ◽

Dmitry Konyushkov ◽

Sergey Goryachkin

Keyword(s):

Global Warming ◽

Organic Carbon ◽

Carbon Content ◽

Soil Cover ◽

Arable Land ◽

Organic Carbon Content ◽

Negative Consequences ◽

Central Yakutia ◽

Soil Subsidence ◽

Wavy Line

Global warming, which is especially intensive (up to 0.08°C yr−1) in permafrost area of Central Yakutia, has dramatic consequences for scarce arable land resources in this region. In Yedoma landscapes, intense permafrost thawing on arable fields unprotected by forest vegetation transforms the surface microtopography with the formation of residual thermokarst mounds (byllars) of 6–10 m in diameter surrounded by a polygonal network of hollows of 0.3–1.5 m in depth above melting ice wedges. This process also takes place on former croplands abandoned in the recent decades because of socioeconomic reasons. It is accompanied by a significant transformation of the previously highly likely homogeneous soil cover composed of Cambic Turbic Cryosols (Sodic) into differentiated complexes of permafrost-affected Stagnic Cambisols or Calcic Solonetzes (Turbic) on the mounds and Calcic Stagnic Solonetzes (Turbic) in the microlows. Surface soil horizons on the mounds have a strongly to very strongly alkaline reaction (pH 8.5–9.5) and low (<2%) organic carbon content; a wavy line of effervescence is found at a depth of 15–30 cm. Soils in the microlows have a close to neutral reaction in the upper horizons (pH 6.2–7.5); higher organic carbon content (2–3%); more pronounced textural differentiation of the profile with the formation of typical natric Btn and, in some cases, overlying eluvial E horizons; deeper (50–60 cm) line of effervescence; and clear stagnic features in the lower part of the profile. In the case of shallow embedding by ice wedge, the lowermost part of the soil in the microlow is characterized by the low bulk density (1.04 g cm−3) because of the appearance of hollows after thawing of the ice-rich transient layer and melting of the top of ice wedges. This may be indicative of the further soil subsidence in the future and the appearance of initial thermokarst lakes (dyuedya) within the Yedoma terrain with its transformation into the alas type of landscape. Rapid thermokarst-driven development of microtopography followed by differentiation of the soil cover with increasing soil alkalinity on the microhighs and soil textural differentiation and overmoistening of deep layers in the microlows prevents the return of abandoned arable land to agriculture in Yedoma landscapes.

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Assessment of the agricultural soil use by remote sensing (Perm Region, on the example of LLC “Krona-Agro”)

SOCIALNO-ECOLOGICHESKIE TECHNOLOGII ◽

10.31862/2500-2961-2020-10-1-76-96 ◽

2020 ◽

Vol 10 (1) ◽

pp. 76-96

Author(s):

Aleksey N. Chashchin ◽

Vladimir P. Zhizhilev

Keyword(s):

Remote Sensing ◽

Agricultural Soil ◽

Large Scale ◽

Soil Cover ◽

Arable Land ◽

Contrast Ratio ◽

Landsat 8 ◽

Soil Map ◽

Open Source Gis ◽

Perm Region

For rapid and accurate assessment of the agricultural soil use it is effective to use remote sensing methods. The aim of the work was to evaluate the modern agricultural use of soil according to the data of remote sensing of the Earth of one of the agricultural enterprises of Perm region. Digitization of a large-scale soil map of land use was carried out, the rate of soil overgrowing by woody and shrub vegetation was estimated. Based on satellite data, the modern boundaries of cultivated soils are identified. The basis for creating digital soil maps was the “Krone Agro” scanned soil map, the SRTM radar survey data of 2003 and multispectral images of the Landsat 5 series (March 1988), Landsat 8 (February 2018) and Sentinel 2 (July 2018) were used from remote materials. Creation of cartographic materials and processing of satellite images was carried out in a full-featured open source GIS Quantum GIS. Soddy-podzolic soils predominate on the farm territory and their area is 1,448.1 hectares or 27.3%. As a result of study, it was found that over the period from 1988 to 2018, soil overgrowth occurred. The area of overgrowing was 1575,9 of the total area of the studied territory. Sodbrown (50%), sod-calcareous (10%) and sod-weakly podzolic (40%) soils passed into the fallow state. As a result of the analysis of multi-temporal satellite information, we have established a tendency to reduce arable land. The area ofarable land was reduced by 40 percent, while the number of fields decreased from 35 to 26. In the soil cover of existing fields, the proportion of soil cover with a strong contrast ratio is significant.

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The influence of landscape conditions on the properties of soil cover of arable land on a gentle slope lake-glacial plains

Rossiiskaia selskokhoziaistvennaia nauka ◽

10.31857/s2500-26272019239-43 ◽

2019 ◽

pp. 39-43

Author(s):

A. I. Ivanov ◽

Zh. A. Ivanova ◽

V. I. Dubovitskaya

Keyword(s):

Agricultural Landscape ◽

Soil Cover ◽

Arable Land ◽

Chemical Properties ◽

Soil Formation ◽

Organic Fertilizers ◽

Significant Heterogeneity ◽

Gentle Slope ◽

Physico Chemical ◽

Agrochemical Properties

In order to lay the landscape experience, the soil cover of the agro-landscape on the gentle slope of the lake-glacial plain was studied and the factors and parameters of spatial differentiation of some physical, physico-chemical and agrochemical properties were established. The different degree of differentiation of individual properties associated with the characteristics of soil-ing rocks, geochemical regimes and the nature of anthropogenic impact is established. Significant heterogeneity in the power of eluvial horizons, the degree of development of the gley process, the structural state, the content of organic matter, nitrogen and moderate- granulometric composition, physico chemical properties and nutritional regime. The main factor of variation of soil properties in the agricultural landscape is heterogeneity of soil-forming rocks, estimated in terms of physical, chemical and agrochemical properties in 19-59 %. Natural and anthropogenic soil formation process reduced the average coefficient of variation of these properties within the arable layer by 2.6 times (from 36% to 14 %). The factor of increasing the heterogeneity of a number of agrochemical properties by 1.3-1.9 times in the tranzitno-eluvial facies was planar erosion, in the eluvial facies by 3 times uneven application of organic fertilizers.

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EFFECTIVENESS OF DIFFERENTIATION OF FERTILIZERS DOSES IN GRAIN FALLOW CROP ROTATION LINK

Vestnik of the Russian agricultural science ◽

10.30850/vrsn/2019/1/20-24 ◽

1970 ◽

pp. 20-24

Author(s):

А. I. Ivanov ◽

Zh. А. Ivanova ◽

N. А. Tsyganova

Keyword(s):

Crop Rotation ◽

Soil Cover ◽

Arable Land ◽

Mineral Fertilizer ◽

Fertilizer Application ◽

Perennial Grasses ◽

Low Fertility ◽

Mineral Fertilizers ◽

The Impact ◽

Fertilizer Rates

To assess the efficiency of spatial differentiation of the organic and mineral fertilizer rates in the grain-fallow rotation link the landscape field trial was established in 2013 at the Menkovo experimental station of the Agrophysical Research Institute. The object of study was a historically formed plot of arable land on a mild glacial origin slope of northwestern and western expositions with total area - 53.64 ha (including 47.3 ha of plowed field and 6.34 ha of hayland). The structure of the soil cover consists of a combination of small-contour complexes of light and medium-loamy varieties of soddy gleyed podzolic and gleyic soils. Parent rock is mainly represented by thin and medium loamy and clay sandy moraine underlying by glacial sandy loam on a depth of 75 – 120cm. Soils of medium fertility with plots of high and low fertility are dominated on plowed field. Five key plots of agromicrolandscape (AML) with different geochemical regimes have been selected. The impact of zonal and precision organo-mineral fertilizer system was studied in the "complete fallow – winter wheat – oats plus perennial grasses" crop rotation. Significant differentiation of the soil cover properties of arable land on a mild slope depending on the landscape and environmental conditions was established. The transition to precision agrochemical survey is relevant. The crop rotation link productivity within the five facies of the agricultural landscape varied from 4.98 to 8.68 t/ha in the variant without fertilizer application and from 7.59 to 14.6 t/ha in the variant with fertilizer application. The sufficiency of 1 kg NPK in the fertilizer application variant varied from 1.7 to 5.6 grain units. Sufficient grounds have not been revealed to explain this variability of the indicators only with the relief location and geochemical regime. The optimization of fertilizer rates with regard to specific geochemical regimes (an increase of 12% in AML and a decrease of 14% in AML due to the redistribution of organic and mineral fertilizers) provided increase the sufficiency of 1 kg NPK by 35 %. The methodological basis of such optimization induces a need to develop more detailed scientific argumentation.

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Selecting Relevant Biological Variables Derived from Sentinel-2 Data for Mapping Changes from Grassland to Arable Land Using Random Forest Classifier

Land ◽

10.3390/land9110420 ◽

2020 ◽

Vol 9 (11) ◽

pp. 420

Author(s):

Jiří Šandera ◽

Přemysl Štych

Keyword(s):

Land Use ◽

Random Forest ◽

Change Detection ◽

Satellite Data ◽

Arable Land ◽

Random Forest Classifier ◽

Area Index ◽

Permanent Grassland ◽

Biological Variables ◽

Sentinel 2

Permanent grassland is one of the monitored categories of land use, land use change, and forestry (LULUCF) within the climate concept and greenhouse gas reduction policy (Regulation (EU) 2018/841). Mapping the conditions and changes of permanent grasslands is thus very important. The area of permanent grassland is strongly influenced by agricultural subsidy policies. Over the course of history, it is possible to trace different shares of permanent grassland within agricultural land and areas with significant changes from grassland to arable land. The need for monitoring permanent grassland and arable land has been growing in recent years. New subsidy policies determining farm management are beginning to affect land use, especially in countries that have joined the EU in recent waves. The large amount of freely available satellite data enables this monitoring to take place, mainly owing to data products of the Copernicus program. There are a large number of parameters (predictors) that can be calculated from satellite data, but finding the right combination is very difficult. This study presents a methodical, systematic procedure using the random forest classifier and its internal metric of mean decrease accuracy (MDA) to select the most suitable predictors to detect changes from permanent grassland to arable land. The relevance of suitable predictors takes into account the date of the satellite image, the overall accuracy of change detection, and the time required for calculations. Biological predictors, such as leaf area index (LAI), fraction absorbed photosynthetically active radiation (FAPAR), normalized difference vegetation index (NDVI), etc. were tested in the form of a time series from the Sentinel-2 satellite, and the most suitable ones were selected. FAPAR, canopy water content (CWC), and LAI seemed to be the most suitable. The proposed change detection procedure achieved a very high accuracy of more than 95% within the study site with an area of 8766 km2.

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