Abstract
Normalized Difference Vegetation Index (NDVI) is one of the most commonly used remote sensing indices to study the condition of vegetation. The long time series data of NDVI is of great significance to the study of vegetation change. However, due to the limitations of sensors, remote sensing data cannot obtain both high temporal resolution and high spatial resolution. Therefore, among the widely used NDVI data products, the data with high spatial and temporal resolution is still scarce. Based on the Cubist model, we integrated MODIS data with Landsat and Sentinel remote sensing data, and obtained the MODIS-Landsat fusion data of Tajikistan from 2010 to 2020, and the MODIS-Sentinel fusion data of 2020. This dataset can reflect the temporal and spatial changes of NDVI in Tajikistan from 2010 to 2020, and provide long-term data support for vegetation change analysis and ecological environment monitoring in Tajikistan.
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