E3S Web of Conf.
Volume 222, 2020International Scientific and Practical Conference “Development of the Agro-lndustrial Complex in the Context of Robotization and Digitalization of Production in Russia and Abroad” (DAIC 2020)
|Number of page(s)||6|
|Section||Creation and use of Modern Digital, Intelligent, Robotic Systems and Technologies, New Materials and Methods of Construction, Big Data Processing and the Internet of Things in the Agro-Industrial Complex|
|Published online||22 December 2020|
Digital mapping of solonchak complexes using Sentinel-2A data
Ufa Institute of Biology, Ufa Federal Research Centre, Russian Academy of Sciences 450054, Prospekt Octyabrya, 69, Ufa, Russia
* Corresponding author: email@example.com
Land salinization is an up-to-date issue being broadly studied all over the world. In Russia, salinization processes are predominantly observed in the southern regions, where the main areas of arable land are situated. This research is devoted to mapping of saline lands with the help of satellite data. The study was performed on a 100-hectare plot in the Trans-Ural steppe zone (Republic of Bashkortostan, Russia). A correlation was determined between the level of soil salinity and the main spectral indices associated with Sentinel-2A satellite data. Regression models used 5 salinity indices, vegetation index NDVI, and values of soil conductivity. Linear, quadratic, and logarithmic functions were used. By calculation, the salinity index 5 (G×R)/B demonstrated the best correlation values with the salinity level of (R=0.88, R2=0.77) while using the quadratic function. The vegetation index NDVI revealed no correlation, owing to the poor development or dried-up condition of vegetation. On the basis of the developed regression models, salinity maps are drawn, in which the areas of solonchak complexes are defined.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.