Scholarly record
SPECTRAL CHARACTERISTICS OF GROUPS AND TYPES OF LANDS, CONSTRUCTED BY AVERAGIN LONG-TERM SERIES OF VEGETATION INDECES
Abstract
The optimal solution of intensification and ecologisation of agricultural production is achieved in adaptive-landscape farming systems. To solve the problems of adaptive landscape agriculture, classical methods of soil-landscape mapping and new methods of remote diagnostics of intra-field heterogeneity were combined to identify features that will further improve the efficiency of producing maps of groups and types of land and increase their accuracy. Identification of the spectral characteristics of groups and types of land has become possible due to neural network filtering of big remote sensing data. By intersecting the map of groups and types of lands with the bare soil surface map in geographical information systems, the median values of the -C- coefficient for different land groups and types were calculated. Each agroecological group of lands has its own spectral characteristics, which are influenced by the granulometric composition, moisture regime and humus content. It was established for the first time that groups of lands differing in productivity have different reflectivity. Differences in spectral characteristics of land groups can be used for their remote diagnostics, quantitative assessment, and design of systems to improve low-productive areas.
Publication Impact Profile
Publication details
References19
Fridland V.M. Structure of the soil mantle, Geoderma, vol. 12, pp. 35-42, 1974. DOI: 10.1016/0016-7061(74)90036-6
Krenz J., Greenwood P., Kuhn N.J. Soil Degradation Mapping in Drylands Using Unmanned Aerial Vehicle (UAV) Data. Soil Systems, vol. 3, pp. 33:1�33:19, 2019 DOI: 10.3390/soilsystems3020033
V. I. Kiryushin. Methodology for integrated assessment of agricultural land. Eurasian Soil Science, vol. 53, pp. 960�967, 2020. DOI: 10.1134/S1064229320070066
The Application of Soil�Agroclimatic Index for Assessing the Agronomic Potential of Arable Lands in the Forest�Steppe Zone of Russia. Eurasian Soil Science, vol. 51, pp. 448�459, 2018. DOI: 10.1134/S1064229318040038.
V. I. Kiryushin. The Management of Soil Fertility and Productivity of Agrocenoses in Adaptive-Landscape Farming Systems, Eurasian Soil Science, vol. 52, pp. 1137�1145, 2019. DOI: 10.1134/S1064229319070068.
D. S. Bulgakov. A concept of agroecological assessment of soils of cultivated lands. Eurasian Soil Science, vol. 32. No.6, pp 630-633, 2002.
URL: https://www.esri.com/ru�ru/home
URL: https://qgis.org/ru/site/
Kulyanitsa A.L., Rukhovich D.I., Koroleva P.V., Vilchevskaya E.V., Kalinina N.V. Analysis of the informativity of big satellite precision�farming data processing for correcting large�scale soil maps. Eurasian Soil Science, vol. 53/ issue 12, pp. 1709�1725, 2020. DOI: 10.1134/S1064229320110083.
Ischenko T.A. All-Union instruction on soil surveys and the compilation of large-scale soil maps for land use. Kolos, Moscow, 1973.
Soil map of the USSR. Scale: 1:16000000. 1983. Atlas of the USSR. Nature maps. Soil map / Main Directorate of Geodesy and Cartography under the Council of Ministers of the USSR. Moscow. 1983. P. 104-105.
Simakova M.S. Soil maps. Cartographic knowledge of Russia (topographic and thematic maps). Publishing house of the Institute of Geography of the Russian Academy of Sciences, Moscow, pp. 113-133, 1999.
Liu P. A survey of remote-sensing big data. Front. Environ. Vol. 3. Art. 45, 2015. DOI: 10.3389/fenvs.2015.00045.
Rukhovich D.I., Koroleva P.V., Kalinina N.V., Vilchevskaya Y.V. Detecting degraded arable land on the basis of remote sensing big data analysis. Eurasian Soil Science. Vol. 54/ issue 2, pp. 161�175. 2021. DOI: 10.31857/S0032180X21020131. https://doi.org/10.1134/s1064229321020137
Rukhovich D.I., Koroleva P.V., Kalinina N.V., Rukhovich D.D. The use of deep machine learning for the automated selection of remote sensing data for determination of areas of arable land degradation prosses distribution. Remote Sensing. Vol. 13/ issue 1, pp. 2�4, 2021. DOI: 10.3390/rs13010155
Koroleva P.V., Rukhovich D.I., Kalinina N.V. Location of bare soil surface and soil line on the red�nir spectral plane. Eurasian Soil Science, vol. 50/ issue 12. �. 1375�1385, 2017. DOI: 10.7868/S0032180X17100045 https://doi.org/10.1134/s1064229317100040
Kurbanov R.K., Zakharova N.I. Application of vegetation indexes to assess the condition of crops Sel'skokhozyaystvennye mashiny i tekhnologii, Vol. 14/ issue 2, pp. 4�11. DOI: 10.22314/2073�7599�2020�14�4�4�11. -7599-2020-14-4-4-11
URL: https://agronote.ru/en/
URL: https://operations.cropwise.com/
View or Download full articleAccess options
SWS access login
Login as SWS Scientific CommitteeLogin as SWS Scientific PartnerLogin as SWS AuthorAuthors and approved SWS contributors will read and export their own linked papers after identity matching by SWS profile, email and SGEM GlobalID.
For librarian assistance: [email protected]
Purchase Instant Access
- Article can be downloaded after successful payment.
- Article may be used according to SWS library access terms.
- Article cannot be redistributed.