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Irrigation and Melioration

Abstract

The paper presents the methods of data handling for LANDSAT 8 OLI satellite images with the spatial resolution of 30 meters in the case of WCA “Sofoqoltin” study area in Tashkent province. The main principles are described and the results are shown for three types of classification procedures, such as 1) maximum likelihood; 2)on the basis of indices analysis and 3) classification based on NDVI profile analysis in 2014. The overall classification accuracy is evaluated for the each procedure, pros, cons and the most suitable cases for their application are analyzed. The third studied type of land use classification showed the best result: the overall accuracy for this method was found as 94.2%.

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8

References

1. Lillesand T., R. W. Kiefer Remote Sensing and Image Interpretation USA 2004 2. Черепанов А.С. Вегетационные индексы. Москва, Геоматика №2, 2011 г., 98 с. 3. Виноградов Б.В. Аэрокосмический мониторинг экосистем. Москва, Наука 1984 г., 320 с. 4. Xu H. Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery // International Journal of Remote Sensing. – 2006. – No 27. – P. 3025–3033. 5. Feyisa G. L., Meilby H., FensholtR., Proud S. R. Automated Water Extraction Index: A new technique for surface water mapping using Landsat imagery // Remote Sensing of Environment. – 2014. – No 140. – P. 23–35. 6. Платонов А., Акрамова И. Классификация растительно-земляного покрова с использованием продуктов NDVI спутниковых снимков MODIS.

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