Remote sensing-based assessment of pasture vegetation and moisture dynamics in the lower Amu Darya Delta

Abstract

The lower Amu Darya delta is one of the most ecologically sensitive areas in the Aral Sea region, where the condition of pasture vegetation is shaped by water availability, moisture regime, arid climate, and degradation processes. Therefore, regular assessment of pasture conditions in the region using remote sensing is scientifically and practically important. In this study, multi-year changes in vegetation and moisture conditions in the lower Amu Darya Delta were assessed using annual mean NDVI and NDMI time series obtained between 2014 and 2024. Trends over time were assessed using trend analysis, and relationships between indices were assessed using Pearson correlation, Spearman rank correlation, and simple linear regression. The results revealed a very strong positive correlation between NDVI and NDMI (r = 0.979; ρ = 0.973; p < 0.001), indicating that annual changes in pasture vegetation are closely related to moisture dynamics. At the same time, both indices showed a weak downward trend over the study period, with the rate of decline in NDMI slightly higher than that of NDVI. The results indicate that moisture deficit is one of the main factors determining the condition of the lower delta pastures. The combined use of NDVI and NDMI is an effective approach for regional pasture monitoring, identifying areas at high risk of degradation, and scientifically justifying land resource management decisions.