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Vegetation temperature condition index (VTCI) drought monitoring results retrieved from Landsat remotely sensed data (30m) in Guanzhong Plain, China were spatially transformed to a scale of the Aqua MODIS resolution (930m) by using point spread function, mixed pixel area weighting method and median pixel variability weighting method. The transformed VTCIs were compared with the ones retrieved from Aqua MODIS data for agreement analysis of the two drought monitoring results. Taking MODIS VTCIs as the ‘real’ droughts, correlation coefficients and root mean square errors between the upscaled Landsat VTCIs and MODIS VTCIs, and the texture and semivariances of the two VTCIs were applied to select the best transformation method. The results showed that the transformed VTCIs from the point spread function and the mixed pixel area weighting method were better than those from the median pixel variability weighting method, which indicates that the point spread function and the mixed pixel area weighting method were both suitable for transforming the retrieved VTCI drought monitoring results from Landsat remotely sensed data, and the data processing procedure of the point spread function was relatively simple. The transformed VTCIs in the selected sampling sites covered by winter wheat showed that the smaller the spatial heterogeneity, the higher the transformed accuracy.