compared these three NDVI products, as well as the Landsat 8 NDVI dataset, on the Mongolian Plateau from 2000 to 2014 and found that the consistency between the SPOT-VGT NDVI and Landsat 8 NDVI was better than that of GIMMS NDVI3g or MODIS NDVI. Widely used NDVI datasets include the Global Inventory Modeling and Mapping Studies (GIMMS) NDVI3g, Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI, and Systeme Probatoire d’Observation de la Terra-vegetation (SPOT-VGT) NDVI datasets. The normalized difference vegetation index (NDVI) is one of the most popular remote sensing means for monitoring vegetation and ecological changes. These findings provide a scientific foundation for environmental preservation in the region. The NDVI lag times behind SPEI in grasslands, coniferous forests, and broad-leaved forests were 1–1.5, 4.5, and 7–7.5 months, respectively. In eastern Inner Mongolia, the grassland NDVI was positively correlated with SPEI and significantly affected by drought events, while NDVI in forestlands, including shrubs, broad-leaved forests, and coniferous forests, was negatively correlated with SPEI in the short term and weakly affected by drought. The results reveal that in 82.4% of the study area, NDVI exhibited rising trends, and the SPEI values exhibited declining trends in 78.5% of the area. We then discussed changes in different vegetation responses to drought across eastern Inner Mongolia using cross wavelet transform (XWT) and wavelet coherence (WTC). We investigated the spatiotemporal characteristics of vegetation and drought in the region in the past 38 years. The standardized precipitation evapotranspiration index (SPEI) derived from gridded meteorological data was used to measure drought over the same period. The obtained 1 km-resolution NDVI dataset spanning Inner Mongolia from 1982 to 2019 was used to represent the refined vegetation distribution. Herein, we combined Global Inventory Modeling and Mapping Studies (GIMMS) normalized difference vegetation index (NDVI3g) with Systeme Probatoire d’Observation de la Terra-vegetation (SPOT-VGT) NDVI data through spatial downscaling. Ecological security is one of the most concerned issues of the region’s sustainable development. ![]() Inner Mongolia is an important ecological barrier in northern China. However, in existing research, the response relationships (correlations and lags) were typically determined based on Pearson correlation coefficient and the resultant lag times were constrained by the spatial and temporal resolutions of the analyzed data. Quantifying vegetation responses to drought is essential for ecological management. Drought events cause ecological problems, including reduced water resources and degraded vegetation.
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