| Issue |
E3S Web Conf.
Volume 223, 2020
Regional Problems of Earth Remote Sensing (RPERS 2020)
|
|
|---|---|---|
| Article Number | 03003 | |
| Number of page(s) | 6 | |
| Section | Monitoring of the Environment, Natural and Anthropogenic Objects and Phenomena | |
| DOI | https://doi.org/10.1051/e3sconf/202022303003 | |
| Published online | 21 December 2020 | |
Use of spectral surface characteristics for mapping soil cover structure under Krasnoyarsk forest-steppe conditions
1 Federal State Budget Educational Institution of Higher Education Krasnoyarsk State Agrarian University, 90 Mira Avenue, Krasnoyarsk City, 660049, Russia
2 Institute of Biophysics SB RAS, Krasnoyarsk 660036, Russia
* Corresponding author: t-demyanen@mail.ru
The relations between the spectral surface characteristics of the elements of the soil cover structure and soil properties in the Krasnoyarsk forest-steppe of Central Siberia were investigated. It was revealed that the most informative parameters for field spectrometry are the content of humus, carbonate carbon dioxide and the prevailing particle-size fractions. A statistically significant relationship between the elements of the soil cover structure and the reflectivity of soils has been confirmed by means of multidimensional statistics. The wave lengths with the greatest coupling force are highlighted. Regression equations for remote study of soil cover structure have been obtained, which can be used if additional point studies are carried out in a wider range of test parameters.
Key words: soil cover structure / spectral brightness coefficient / humus / particle-size distribution / multiple regression
© 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.