<b>Reconstruction of Maritime Route Network in Nearshore Waters with Noise Removal Using Step-by-Step Density-based Clustering</b>

code:1.preprocess.py -AIS trajectory preprocessing code2.Similarity calculation.py -Calculate the sub-trajectory Hausdorff distance, course over ground (COG) similarity of key turning points and average COG similarity3.S²-dbscan clustering.py -Code implementation of S2-DBSCAN algorithm for clustering problems under multi-objective conditions4.Delaunay triangulation.py -Perform Delaunay triangulation on the sub-trajectory clustering results5.Extract center line.py -Code for extracting centerline based on triangulation resultsdata：1.perprocess. Preprocessed ship trajectory data2.arcgis pro. Results Visualization### 代码（code）部分： 1. `preprocess.py`：船舶自动识别系统（Automatic Identification System，AIS）轨迹预处理代码 2. `Similarity calculation.py`：用于计算子轨迹豪斯多夫距离、关键转弯点对地航向（Course Over Ground，COG）相似度以及平均对地航向相似度的代码 3. `S²-DBSCAN聚类.py`：面向多目标场景下聚类问题的S²-DBSCAN算法代码实现 4. `Delaunay triangulation.py`：针对子轨迹聚类结果执行德劳内（Delaunay）三角剖分的代码 5. `Extract center line.py`：基于三角剖分结果提取中心线的代码 ### 数据（data）部分： 1. `preprocess`：预处理后的船舶轨迹数据 2. `ArcGIS Pro`：结果可视化成果