NDVI is a widely used index for monitoring plant health from satellite or drone images. However, in areas with very dense or healthy vegetation, NDVI often stops responding to changes — a problem called 'saturation.' This makes it harder to detect subtle differences in vegetation condition. In this study, we explain why saturation happens and introduce a new index called NDVIsm (Saturation Mitigated NDVI). NDVIsm modifies the NDVI formula to stay more responsive, even when vegetation is dense. It highlights small changes in plant health that NDVI usually misses. We tested NDVIsm across different land types and imaging platforms. Compared to NDVI, NDVIsm showed more detailed variation in high-growth areas and better matched real plant traits like leaf area and chlorophyll content. It also improved the accuracy of crop yield prediction models. Overall, NDVIsm is a more sensitive and reliable tool for detecting changes in dense vegetation, helping researchers and land managers make better-informed decisions.