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Time-series analysis of Landsat imagery for monitoring grazing impact in a rangeland ecosystem of Forish district, Uzbekistan

Abstract

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The vegetation changes of semi-desert and desert landscapes are temporally and spatially heterogeneous. Vegetation indices derived from remotely sensed data have long been proposed as a source of information for predicting green biomass levels. This research aimed to assess vegetation status via remote sensing techniques using various vegetation indices (NDVI and SAVI) in semi-desert and desert environments. The feasibility of applying such techniques is tested for assessing grazing impact in Forish district of Uzbekistan.

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Time-series of ecological indicators of land degradation that are collected synoptically from local to global spatial scales can be derived from the 43-year and continuing Landsat satellite archive. Consequently, this study was conducted in the Forish rangeland ecosystem using a time-series of standardized Landsat imagery for the period 2010 to 2015. Two common vegetation indices derived from Landsat Surface Reflectance (LSR) imagery were analysed. Landsat TM/ETM+ LSR images were used for calculations and analysis.

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The research had the objectives to estimate NDVI and SAVI based on Landsat Surface Reflectance imagery, investigate a correlation between vegetation indices values and the field geo-botanical monitoring results, map of the study area according to the degradation levels (weak, average, strong and very strong), determine the relationship between the degradation process and the weather conditions of the study area for 2010-2015 years period.

 

Key words:  grassland degradation, Landsat time-series, unsupervised classification, NDVI, SAVI.

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