Abstract: Existing drought monitoring technologies are liable to be affected by the environment and suffer poor timeliness. Given this, this study utilized the MODIS_TVDI and GNSS_PWV data to investigate the spatial-temporal changes in the drought characteristics in spring from 2016 to 2020 in Yunnan province through correlation analysis and regression analysis. The research results are as follows. The TVDI inversion results can accurately reflect the spatial-temporal changes in the regional drought characteristics during 2016—2020. In space, the drought showed the trend of increasing from northwest to southeast in Yunnan. In terms of time, the drought increased first and then alleviated in spring, especially from March to April. In addition, there was a strong correlation between PWV and TVDI according to Pearson correlation analysis. The correlation coefficient was largely greater than 0.5 on a quarterly scale. On a monthly scale, the variation trend of PWV was roughly consistent with that of TVDI, except that the variation of TVDI showed a certain time delay. On a daily scale, the variation amplitude of PWV was highly consistent with that of TVDI, especially during rainfall, and both of them showed certain signals of drought characteristics. Therefore, PWV can serve as a new technical means for drought monitoring.