Vegetation temperature condition index (VTCI) is proved to be a quantitative drought monitoring approach by using the high temporal resolution remotely sensed data. However, with low temporal resolution data, the monitoring results are relatively wet and dry. A new model called the median fusion model (MFM) was developed for spatially down scaling the coarse spatial quantitative VTCI (1km) derived from the moderate resolution imaging spectroradiometer (MODIS) data products and the relative VTCI (30m) derived from the Landsat OLI/TIRS products in the Guanzhong Plain, China to a scale of the quantitative drought monitoring results (30m) called MFM-VTCI, and their quantifications were proved. The results showed that the good agreements between the MFM-VTCIs and the Landsat-VTCIs were found in terms of correlation coefficient and structural similarity index (SSIM) values, and the two VTCIs had similar spatial distribution and texture features. The root mean square error (RMSE) and the differences between the MFM-VTCIs and the Landsat-VTCIs were consistent with the systematic error between the quantitative drought monitoring results and the relatively wet and dry monitoring results, indicating that it was comparable between the MFM-VTCIs and the Landsat-VTCIs. The correlation coefficients between the MFM-VTCIs and the cumulative precipitation were similar to those between the MODIS-VTCIs and the cumulative precipitation, which were larger than those between the Landsat-VTCIs and the cumulative precipitation, indicating that the downscaled MFM-VTCIs were quantitative drought monitoring results.