Drought significantly impacts vegetation health, particularly in arid regions like Saudi Arabia, where water scarcity and extreme temperatures exacerbate ecological stress. This study examines the spatiotemporal dynamics of drought and its effects on vegetation health from 2004 to 2021 using advanced wavelet analysis techniques. Key indices employed include the Vegetation Health Index (VHI), Normalized Difference Vegetation Index (NDVI), Temperature Condition Index (TCI), and the Standardized Precipitation Evapotranspiration Index (SPEI). Continuous wavelet transform (CWT) and bivariate Morlet wavelet coherence analysis were applied to reveal multi-scale temporal relationships between drought conditions and vegetation health. The results demonstrate a strong positive correlation between SPEI and VHI, indicating that moisture availability is the dominant factor influencing vegetation health. High wavelet coherence values between SPEI and VHI were observed during major drought years such as 2008, 2012, and 2017, highlighting periods when reduced precipitation closely aligned with increased vegetation stress. In contrast, TCI and VCI showed weaker and more variable correlations with VHI, suggesting that temperature stress and vegetation greenness alone are less predictive of vegetation health dynamics. These findings underscore the importance of integrating moisture, temperature, and vegetation condition indices for effective drought monitoring and mitigation. The novel application of wavelet coherence analysis offers a robust framework for understanding the complex interactions between climatic variables and vegetation health over multiple temporal scales. This approach can inform resource management and policy decisions aimed at improving drought resilience in arid environments prone to climate extremes. Implementing integrated drought mitigation strategies that prioritize moisture management can enhance vegetation resilience and support sustainable land management in regions facing similar climatic challenges.