Geological and Environmental Engineering | Article | Published 2019

Multi-temporal monitoring of cotton growth through the vegetation profie classifiation for Tashkent province, Uzbekistan

Publisher: Geoscape
Keywords: Agriculture, Land use classification, Remote sensing, NDVI profile, Spectral correlation mapper, Uzbekistan

Abstract

As satellite data of the Earth's surface seems to be of vital importance for many applications, classification of land use and land cover has been found to vary dramatically in different approaches. In this paper, a modified classification algorithm of remote sensing data is presented for processing medium and high spatial resolution satellite images like Landsat and Sentinel in Tashkent province of Uzbekistan. The results of NDVI (Normalized difference vegetation index) profile analysis via Spectral Correlation Mapper classification are shown for the period 1994-2017. It is implied, that combination of optical and radar data with the application of Spectral Correlation Mapper classification improves the results of classification for a specific dataset by considering such factors as overall classification accuracy and time and labor involved

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