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POSSIBILITIES OF USING SPECTRAL INDICES IN DETERMINING OF THE BOUNDARIES OF SURFACE WATER FROM LANDSAT IMAGES

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Hydrometeorology and environmental monitoring

Hydrometeorology and environmental monitoring

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ARTICLE ANNOTATION

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A detailed study of the hydrological regime of lakes is an urgent task, however, it should be noted that this issue is complicated by the lack of systematic observations on lakes. In such cases, satellite images can be used to obtain information about water bodies in difficult to reach areas. This article examined several methods for decoding satellite images to determine the water surface area of a lake. Based on the results of the study, it was found that among spectral indices the modified methods of classifying the normalized-difference water index MNDWI (2.6%) and the automated water ectraction index AWEIsh (2.3%) had the smallest error in determining the water surface. Among the tested methods, the spectral index MNDWI is the most acceptable in terms of accuracy of results and time consumption.

AUTHORS

S.Qalabayev

Национальный университет Узбекистана имени Мирзо Улугбека

Tags

# озеро# lake# кўл# сув юзаси майдони# NDWI# MNDWI# WRI# AWEIsh# AWEInsh.# площадь водного зеркала# water surface area# AWEInsh

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Article Identifiers

ROI:

https://eroi.uz/11.0191/A0624-0040

DOI:

Not Available

References

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Южное Приаралье – новые перспективы. Под ред. проф. В.А. Духовного и Ю. Де Шуттера. – Ташкент: «Нори», 2003. – 154 с.

Feyisa G.L., Meilby H., Fensholt R., Proud S.R. Automated Water Extraction Index: A New Technique for Surface Water Mapping Using Landsat Imagery // Remote Sensing of Environment. 2014. Volume 140. – P. 23-35. http://dx.doi.org/10.1016/j.rse.2013.08.029

McFeeters S.K. The Use of the Normalized Difference Water Index (NDWI) in the Delineation of Open Water Features // International Journal of Remote Sensing. 1996. Volume 17. – PР. 1425-1432. http://dx.doi.org/10.1080/01431169608948714

Xu H.Q. Modification of Normalised Difference Water Index (NDWI) to Enhance Open Water Features in Remotely Sensed Imagery // International Journal of Remote Sensing. 2006. Volume 27. – PР. 3025-3033. http://dx.doi.org/10.1080/01431160600589179