长期以来，为准确表达海底地形以确保舰船的海上航行安全，通常需由专业人员全程、自主进行水深测量和制图综合，并构建出航海用数字水深模型来实现。然而，受人力、物力等限制，我国已很难由自主测量、专业人员全程负责的经典作业模式来获取所有国家海洋利益相关海域的水深数据，这就给自主、专业测量水深数据未覆盖区域的航海用数字水深模型构建带来了困难。为此，本项目将突破当前单纯依靠自主、专业测量的水深数据构建数字水深模型的局限，挖掘航渡式水深数据、国外水深数据等众源水深数据在数字水深建模中的潜能，建立众源水深数据的质量评估与控制模型，构建基于众源水深数据的航海用数字水深模型。本项目的成功实施，可望为水深建模开辟新的研究思路和提出新的技术方法，实现自主、专业测量水深数据未覆盖区域的航海用数字水深模型构建。

For a long time, the submarine topography is usually represented by Digital Depth Model for ensuring ship’s navigational safety, of which the depth data derived from the professional workers through making a series of process with hydrographic survey and chart generalization. As a limitation of the number of the professional workers, the depth data inside the areas related to national interests cannot be acquired only from our professional officials. So that some difficulties occur that the construction of DDM serving for navigation inside which there is not any depth data derived from the professional officials. Therefore, aiming at the drawbacks of the current methods for constructing DDM serving for navigation only based on the depth data from the professional workers, the crowd-sourced depth data is utilized for constructing DDM serving for navigation. The potential of the crowd-sourced depth data is mined in the depth modeling, then the quality of the crowd-sourced depth data is estimated and controlled, finally DDM serving for navigation is constructed. The achievements of the project are possible to inaugurate a new thought and propose new technical methods for utilizing crowd-sourced depth data, which can construct DDM serving for navigation without the depth data from the professional workers.