Issue |
E3S Web Conf.
Volume 563, 2024
International Conference on Environmental Science, Technology and Engineering (ICESTE 2024)
|
|
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Article Number | 03070 | |
Number of page(s) | 8 | |
Section | Green Environment | |
DOI | https://doi.org/10.1051/e3sconf/202456303070 | |
Published online | 30 August 2024 |
Monitoring and Mapping rangeland health using remote sensing and GIS methods: A case study in the foothill Artemisia-ephemeral rangeland region in Samarkand
1 Tashkent Institute of Irrigation and Agricultural Mechanization Engineers National Research University 100000, Uzbekistan, Tashkent, Mirzo Ulugbek, Street Kari Niyazi, 39
2 Samarkand State University named after Sharof Rashidov 140104, Uzbekistan, Samarkand Boulevard, 15
3 National University of Uzbekistan named after Mirzo Ulugbek
4 Tashkent State Technical University named after Islam Karimov
* Corresponding author: maxmudjon-83@mail.ru
This paper describes the use of NDVI analysis to assess the health condition of the rangeland in a specific study area. NDVI values were used to determine the vegetation cover and its condition by dividing the values into different classes based on field samples. The study found that the rangeland health condition could be classified into four classes based on the NDVI values ranging from -0.26 to 0.63. The results indicated the presence of both healthy and unhealthy vegetation cover in the study area. However, the study emphasizes that NDVI values can vary depending on different factors, such as season, weather conditions, and vegetation type, and therefore, these factors must be considered when interpreting the results. Overall, the study highlights the importance of using NDVI analysis as a valuable tool to assess the health condition of rangelands and to inform management practices. The paper presents the results of a study on rangeland health classification in a particular study area. The study utilized remote sensing and GIS technologies to classify the rangeland into healthy and degraded categories. The results showed that only 4.4% of the land area was classified as healthy rangeland, while most of the study area was classified as degraded. Specifically, 36.1% of the land area was classified as moderately degraded, 24.3% as low degraded, and 35.2% as highly degraded. These findings suggest that the health of rangelands in the study area is poor and requires effective management and restoration practices to improve productivity. The study demonstrates the usefulness of remote sensing and GIS technologies in monitoring rangeland health and supporting sustainable management practices.
© The Authors, published by EDP Sciences, 2024
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.
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