智慧巡湖系统在湖泊管理中的探索应用

针对湖泊人工巡查方面存在的巡查效率低下、管理不全面、分工不到位、问题追踪更新不及时等问题，提出利用无人机智慧巡检方式，通过无人机沿湖泊岸线航拍提取大量图像，利用 SIFT 算法完成图像无缝拼接，提取图像主要目标区域，并利用 SIFT 特征完成目标图像与原始图像的比对，从而识别湖泊岸线变化情况。 该方法应用在石臼湖固城湖湖泊巡查中，无人机初次飞行时提取湖泊网格地理数据及建筑物构筑物的信息作为原始数据，完成 2 期巡检，覆盖范围和识别精度较人工巡查有很大提高。在实际应用中发现在水生物识别的细节和巡查频次上还有待提高，目前作为湖泊辅助性巡查上优势明显，作为一种独立的巡查方式及在智能分析决策上值得进一步探讨。

Exploration and application of intelligent Lake patrol system in Lake patrol management

In view of the problems existing in the artifical inspection of lakes, such as low inspection efficiency, incomplete management, inadequate division of labor, untimely problem tracking and updating, this paper proposes to use the smart inspection mode of UAV to extract a large number of images through aerial photography of UAV along the lake and shore line, use SIFT algorithm to complete image seamless splicing and extract the main target area of the image and use the SIFT feature to compare the target image with the original image, so as to identify the changes of lake shoreline. This method is applied to the patrol inspection of Shijiu Lake and Gucheng Lake. During the first flight of UAV, the grid geographic data of the two lakes and the information of buildings and structures are extracted as the original data to complete the two phases of patrol inspection. Compared with manual patrol inspection, the coverage and recognition accuracy are greatly improved. In practical application, it is found that the details of water biometric identification and patrol frequency need to be improved. At present, as an auxiliary patrol of lakes, this method has obvious advantages. As an independent patrol method and in intelligent analysis and decision-making, this method is worthy of further discussion.