Accurate estimation of carbon storage is crucial for assessing the carbon sink function of ecosystems and formulating carbon reduction policies. Traditional methods for estimating carbon storage based on plot inventory are constrained by data acquisition and spatial scale limitations, making it difficult to balance the need for both large-scale coverage and high accuracy. This study proposes a method for estimating the carbon storage of natural resource elements that combines remote sensing technology with plot observations. It utilizes high-resolution remote sensing data to extract key vegetation parameters and establishes regression models in conjunction with plot observation data to achieve spatialized estimation of carbon storage for all natural resource elements. The results indicate that this method can effectively improve the accuracy of carbon storage estimation and is more adaptable and has greater promotional value compared to traditional methods. This study provides a scientific basis for refined carbon storage assessment at the regional scale and offers technical support for forest resource management, ecosystem carbon sink assessment, and the development of carbon trading mechanisms.