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The development of high-fidelity 3D digital models of the land surface environment in real-time has become essential in many fields, including urban planning, agricultural surveying and mapping, disaster management, and military applications. Building a high-fidelity digital model of the land surface environment in real time is the key foundation for realizing the virtual mapping of the geographic environment and then forming a digital twin geographic environment.However, current methods for constructing these models suffer from several challenges such as slow speed, low timeliness, and limited application in large scenarios.To overcome these challenges, this paper proposes a new real-time dense point cloud generation and digital model construction method based on unmanned aerial vehicle (UAV) platforms. The proposed algorithm significantly improves the speed and accuracy of land surface model construction compared to existing algorithms. It enables the degree of online data collection and real-time modeling. The algorithm is based on a general simultaneous localization and mapping framework, the technical chain from data acquisition to 3D point cloud generation, digital model reconstruction, and result analysis is unobstructed. At the meantime, the algorithm breaks through key technologies such as online data acquisition and pose problem solving, real-time dense point cloud generation, digital surface model (DSM) and digital orthophoto map (DOM) construction. According to the experimental results of the dataset containing different land surface environments such as cities, farmland, mountains, and deserts, the algorithm proposed in this paper can process high-quality land surface environment dense point clouds and digital models while being 30-50 times faster than existing algorithms such as Pix4DMapper. On average, it can process a high-resolution image in less than one second, while the interval for general aerial survey drones is 1-2 seconds. Furthermore, the application of the algorithm proposed in this paper to emergency rescue work of mountain flood disasters can assist in real-time reconstruction of inaccessible areas, surveying the area and location of washed-out and sediment areas, and support emergency rescue work. In conclusion, the proposed real-time dense point cloud generation and digital model construction method based on UAV platforms represents a significant advancement in the field of geographic information systems. It has the potential to revolutionize various fields, including disaster management, emergency response, military applications, and urban planning. Additionally, due to the breakthrough of the algorithm, the core problem of real-time mapping from reality to virtual in the construction of digital twins in geographic environments has been solved. Therefore, it can empower digital twins and provide a digital foundation for digital twin applications in geographic environments. Based on the real-time mapping of three-dimensional information of the ground environment, parallel simulation and decision-making can be carried out. Therefore, it is also expected to achieve functions such as emergency warning, scheme evaluation and decision optimization based on the dynamic monitoring of target information in the scene, further improving the automation and intelligence level of the applied system.