[18] used Suomi NPP/VIIRS data for June-August drought monitoring in the eastern region of Qinghai Province, and the TVDI index was examined to be the index with the highest accuracy among all drought index models, and the inversion results were consistent with the actual drought conditions. [PERSON] et al. [19], in the drought monitoring of Eurasia in April-September during the period from 2005 to 2014, used the Vegetation Index Trapezoidal Trapezoidal Feature Space (VITT) to complete the calculation of TVDI index and discuss the performance and performance of TVDI index in Asia and Europe. [PERSON] et al. [20] used the constraint line method to improve on the original TVDI index model and evaluated the spatial and temporal characteristics of drought in the Yellow River Basin. [PERSON] et al. [21] used NOAA-AVHRR data for arithmetic to propose a drought monitoring index, namely the conditional vegetation temperature index (VTCI), which was successfully applied in drought monitoring in the Guanzhong Plain of Shaanxi. [PERSON] et al. [22] used the VTCI index to monitor the drought time series during the summer maize growing period in central Hebei and successfully tested the reliability of the VTCI index. [PERSON] and [PERSON] [23] proposed a new microwave remote sensing drought index, the Microwave Integrated Drought Index (MIDI), which utilizes microwave sensor-obtained precipitation, soil moisture, and surface temperature for integration. It enhances the ability of timely monitoring of short-term drought in semi-arid regions of northern China. The data sources required for the integrated remote sensing drought monitoring index are easy to obtain and relatively uncomplicated to compute and operate, but its construction is usually related to the characteristics of the study area. In this paper, Landsat series images (Landsat 7 ETM+, Landsat 8 OLI, Landsat 9 OLI-2 images) are used as the primary data source for drought monitoring and analysis. Laibin City, Guangxi Zhuang Autonomous Region, is selected as the study area for conducting drought monitoring based on multispectral remote sensing data. The TVDI drought index model was selected to analyze drought conditions in the vegetation areas of Laibin City, and suitable drought validation indexes are utilized to validate the accuracy of the drought monitoring model. The drought index with the highest accuracy is ultimately selected to complete the drought monitoring analysis of the vegetation in Laibin City for the year 2021, 2022 and 2023.The innovation of this article lies in verifying the applicability and superiority of TVDI in drought monitoring in Laibin City. Compared to indices such as RVI, NDWI, and VTCI, TVDI exhibits higher accuracy in reflecting the vegetation drought status in Laibin City. This finding fully demonstrates the significant advantages of TVDI in vegetation drought monitoring work in Laibin City. Through monitoring and analyzing the vegetation drought situation in Laibin City, we can conclude that TVDI, as a monitoring tool, performs better than other common indices such as RVI, NDWI, and VTCI. This indicates that TVDI has stronger sensitivity and reliability in capturing vegetation drought information, providing more accurate data support for vegetation drought monitoring in Laibin City. On this basis, we can better understand and evaluate the vegetation growth status in Laibin City, providing a scientific basis for agricultural irrigation, ecological environment protection, and other fields.