In the context of global warming, drought is the most complex and damaging natural disaster, which becomes more and more frequent, causing negative impacts on agriculture, water resources, natural ecosystems, and society activities. There are several kinds of drought indices derived from station-based meteorological data that are widely used for monitoring drought evolution, mainly including the Palmer drought severity index (PDSI), the standardized precipitation index (SPI) and the standardized precipitation evapotranspiration index (SPEI). The SPEI not only considers precipitation and temperature data, but also integrates the sensitivity of PDSI to changes in evaporation demand and the simplicity of calculation and the multi-scale features of the SPI that identify different types of drought. Therefore, the SPEI was used to describe the drought severity determined by the difference between precipitation and potential evapotranspiration, based on the monthly meteorological data from 1961 to 2016 in Henan Province. And the regional SPEI was obtained at different time scales (1-, 3-, 6-, and 12-month) to characterize the dry or wet conditions in the study area. And the 1-month SPEI can clearly see the subtle changes of drought occurrence and reflect a short-term condition; the 3-month SPEI provides the seasonal drought occurrence; the 12-month SPEI reflects the drought variation at inter-annual time scales. In addition, the remote sensing method, which can provide large coverage, and multispectral and multitemporal observations from satellite sensors at various scales, is another method used to monitor drought conditions on a regional scale, especially in the areas with few meteorological stations. Numerous studies have suggested that a combination of surface temperature, normalized difference vegetation index (NDVI) and land surface temperature (LST) can reveal information on the regional drought conditions. Here, the temperature vegetation dryness index (TVDI) based on the interpretation of the simplified NDVI-LST space for estimating drought conditions was selected to monitor drought conditions on a regional scale, and the moderate resolution imaging spectroradiometer (MODIS) was used, which has many advanced characteristics such as wide spectral range, high temporal resolution and low cost. And the correlation between SPEI and TVDI was calculated. The results showed that SPEI was increasing slightly at different time scales during the period of 1961-2016, indicating that Henan was getting more humid. As the time scale increased, the amplitude of the SPEI decreased. However, the distribution in Henan has been uneven. Annually, droughts occurred in 1961, 1965, 1966, 1968, 1972, 1976, 1978, 1981, 1986, 1988, 1997, 2001 and 2013. Moreover, drought frequency was selected to calculate the probability of drought occurrence. During the period of 1961-2016, Zhengzhou had the highest frequency (33.10%), followed by Xinyang and Luanchuan (32.14% and 31.55%, respectively), whereas Luoyang and Xihua had the lowest frequency (25.10% and 25.30%, respectively). Correlation analysis between monthly TVDI and SPEI showed that there existed negative relationship between 1-month SPEI and TVDI, and as TVDI got smaller, SPEI became higher, reflecting that the severity of drought was lighter, and conversely drought would aggravate as TVDI got larger and SPEI became lower. Therefore, our study on the relationship between SPEI and TVDI can provide a scientific basis for early warning and risk management of water resources and agricultural production.