| Issue |
E3S Web of Conf.
Volume 401, 2023
V International Scientific Conference “Construction Mechanics, Hydraulics and Water Resources Engineering” (CONMECHYDRO - 2023)
|
|
|---|---|---|
| Article Number | 02004 | |
| Number of page(s) | 8 | |
| Section | Ecology, Hydropower Engineering and Modeling of Physical Processes | |
| DOI | https://doi.org/10.1051/e3sconf/202340102004 | |
| Published online | 11 July 2023 | |
Analysis of soil salinity in irrigated agricultural land using remote sensing data: case study of Chinoz district in Uzbekistan
1 “Tashkent Institute of Irrigation and Agricultural Mechanization Engineers”, National Research University, Tashkent, Uzbekistan
2 The Karshi branch of the Tashkent Institute of Irrigation and Agricultural Mechanization Engineers, National Research University, Karshi city, Uzbekistan
* Corresponding author: rustam.oymatov@gmail.com
Soil salinity is a serious agricultural concern in Uzbekistan, causing plant growth to be hampered and crop productivity to be diminished. This issue is especially prevalent in semi-desert and desert regions, compounding problems such as soil erosion, land degradation, subsidence, corrosion, and poor groundwater quality. On the other hand, Geographic Information Systems (GIS) and Remote Sensing (RS) technologies provide more efficient, cost-effective, and timely tools and procedures for mapping soil salinity. Different indices and methods can be used to detect and quantify soil salinity levels using the spectral information acquired by the Landsat-8 OLI sensor. Among these are the Normalized Difference Salinity Index (NDSI) and the Normolazed Difference Vegetation Index (NDVI). GIS software integrates satellite imagery with auxiliary data such as soil type and topography, allowing for a thorough assessment of soil salinity distribution over the research area. Compared to traditional methods, integrating remote sensing data with GIS analysis provides a more efficient and cost-effective approach to soil salinity assessment. The findings of this study will help us understand the distribution of soil salinity in the study area and provide insights for decision-making processes connected to sustainable land management.
© The Authors, published by EDP Sciences, 2023
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.