Analysis of soil salinity in irrigated agricultural land using remote sensing data: case study of Chinoz district in Uzbekistan
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 poo...
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| Format: | Article |
| Language: | English |
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EDP Sciences
2023-01-01
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| Series: | E3S Web of Conferences |
| Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/38/e3sconf_conmechydro23_02004.pdf |
| _version_ | 1797775896075042816 |
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| author | Oymatov Rustam Teshaev Nozimjon Makhsudov Rahimjon Safarov Fayzali |
| author_facet | Oymatov Rustam Teshaev Nozimjon Makhsudov Rahimjon Safarov Fayzali |
| author_sort | Oymatov Rustam |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-12T22:42:11Z |
| format | Article |
| id | doaj.art-5d34359e86044534b69b75e8bf03330a |
| institution | Directory Open Access Journal |
| issn | 2267-1242 |
| language | English |
| last_indexed | 2024-03-12T22:42:11Z |
| publishDate | 2023-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | E3S Web of Conferences |
| spelling | doaj.art-5d34359e86044534b69b75e8bf03330a2023-07-21T09:33:47ZengEDP SciencesE3S Web of Conferences2267-12422023-01-014010200410.1051/e3sconf/202340102004e3sconf_conmechydro23_02004Analysis of soil salinity in irrigated agricultural land using remote sensing data: case study of Chinoz district in UzbekistanOymatov Rustam0Teshaev Nozimjon1Makhsudov Rahimjon2Safarov Fayzali3“Tashkent Institute of Irrigation and Agricultural Mechanization Engineers”, National Research University“Tashkent Institute of Irrigation and Agricultural Mechanization Engineers”, National Research University“Tashkent Institute of Irrigation and Agricultural Mechanization Engineers”, National Research UniversityThe Karshi branch of the Tashkent Institute of Irrigation and Agricultural Mechanization Engineers, National Research UniversitySoil 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.https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/38/e3sconf_conmechydro23_02004.pdf |
| spellingShingle | Oymatov Rustam Teshaev Nozimjon Makhsudov Rahimjon Safarov Fayzali Analysis of soil salinity in irrigated agricultural land using remote sensing data: case study of Chinoz district in Uzbekistan E3S Web of Conferences |
| title | Analysis of soil salinity in irrigated agricultural land using remote sensing data: case study of Chinoz district in Uzbekistan |
| title_full | Analysis of soil salinity in irrigated agricultural land using remote sensing data: case study of Chinoz district in Uzbekistan |
| title_fullStr | Analysis of soil salinity in irrigated agricultural land using remote sensing data: case study of Chinoz district in Uzbekistan |
| title_full_unstemmed | Analysis of soil salinity in irrigated agricultural land using remote sensing data: case study of Chinoz district in Uzbekistan |
| title_short | Analysis of soil salinity in irrigated agricultural land using remote sensing data: case study of Chinoz district in Uzbekistan |
| title_sort | analysis of soil salinity in irrigated agricultural land using remote sensing data case study of chinoz district in uzbekistan |
| url | https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/38/e3sconf_conmechydro23_02004.pdf |
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