深度优先搜索策略下水系结构构建与可视化方法

    Automatic construction and visualization method for complex water system structures based on deep prior search

    • 摘要: 水系是地图制图的核心要素之一,由于河湖水网数据普遍缺乏精确的拓扑结构,且数据骨架错综复杂、等级划分不明确,导致水系数据的分级与渐变绘制难度较大,无法满足应急制图等场景对水系数据处理与可视化的时效性要求。为此,面向复杂水系数据,提出了一种基于水系拓扑和河段溯源长度的水系结构自动构建与分级方法,并在水系分级的基础上,提出了一种基于凸角圆弧法的水系数据渐变宽度计算和可视化方法。以武汉市和江西省水系为例,以相关地图资料为参考,探究了所提方法在水系分级和渐变式表达方面的有效性。实验结果表明,所提方法能够较为精确地识别水系的主、支流结构,并且实现了满足自动化制图需求的河流渐变效果。该方法能够有效应对传统地图制图在水系分级处理及渐变绘制上的诸多难题,显著提升了水系数据表达的效率与准确性,可为智能快速地图制图提供技术与方法借鉴。

       

      Abstract: Water systems are one of the core elements in cartography. However, river and lake network data often lack precise topological structures, while contains complex skeletons and unclear hierarchical classifications. These issues complicate the grading and width transition of water system data, making it challenging to meet the timeliness requirements for data processing and visualization in scenarios like emergency mapping. To address these challenges, we first introduce an automated method for constructing and grading water system structures, based on water system topology and the upstream tracing length of river segments, specifically designed for complex water systems. Secondly, a method for calculating and visualizing gradual width changes in water systems using the convex angle arc approach is presented, which is built upon the graded water system data. Finally, using Wuhan City and Jiangxi Province as study areas and referencing relevant map data, we evaluated the proposed methods′ effectiveness in water system grading and gradient representation. Experimental results demonstrate that the proposed approach can accurately identify the main and tributary structures of water systems, achieving a gradient rendering effect that supports automated cartography needs. This method effectively addresses numerous challenges in traditional cartography related to water system grading and gradient rendering, significantly enhancing the efficiency and accuracy of water system data representation. It provides valuable technical and methodological support for intelligent and rapid map creation.

       

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