测绘通报 ›› 2021, Vol. 0 ›› Issue (9): 74-78.doi: 10.13474/j.cnki.11-2246.2021.0277

• 学术研究 • 上一篇    下一篇

多源矢量空间数据可用性评估的可视分析

陈换新1, 马超2, 张吉才3, 陈长林4, 秦志强1, 马京振5, 汪亚群1   

  1. 1. 96911部队, 北京 100011;
    2. 西安测绘研究所, 陕西 西安 710054;
    3. 61618部队, 北京 100088;
    4. 海军研究院, 天津 300061;
    5. 信息工程大学地理空间信息学院, 河南 郑州 450052
  • 收稿日期:2021-04-19 修回日期:2021-07-21 发布日期:2021-10-11
  • 作者简介:陈换新(1984-),男,博士,研究方向为数字制图技术和空间数据融合。E-mail:chx1557@163.com
  • 基金资助:
    国家自然科学基金(41571399;41901397)

The visual analysis of multi-source vector spatial data usability evaluation

CHEN Huanxin1, MA Chao2, ZHANG Jicai3, CHEN Changlin4, QIN Zhiqiang1, MA Jingzhen5, WANG Yaqun1   

  1. 1. Troops 96911, Beijing 100011, China;
    2. Xi'an Institute of Surveying and Mapping, Xi'an 710054, China;
    3. Troops 61618, Beijing 100088, China;
    4. Naval Research Academy, Tianjin 300061, China;
    5. Institute of Geography Spatial Information, Information Engineering University, Zhengzhou 450052, China
  • Received:2021-04-19 Revised:2021-07-21 Published:2021-10-11

摘要: 本文将可视分析引入到多源矢量空间数据可用性评估中,为用户提供探索发现数据可用性的环境。在论证可行性的基础上,制定了多源矢量空间数据可用性评估可视分析应遵循的基本原则。在反映多源空间数据的同时,根据用户需求确定评估内容,触发相应模型计算并可视化表达,将用户需求、人脑认知通过交互界面和计算机算法模型相结合,允许用户按照自身需求了解不同数据的各种信息,帮助用户发现隐藏在数据中的知识,进而制定科学合理的数据使用方案。

关键词: 多源矢量空间数据, 可用性, 可视分析, 人机交互, 可视化

Abstract: This paper introduces visual analytics to the evaluation of multi-source vector spatial data usability, which offers the environment of visual analysis to the user. Analyzing the feasibility from concept and technique, the paper formulates the basic principles. Visualizing the multi-source spatial data, the usability evaluation is driven by user requirements, and then the relevant model program is triggered to calculate and visualize. Visual analysis can link the user demand, human cognition and usability evaluation models together through interactive interface. With the help of visual analytics, user can explore different aspects and details of multi-source vector spatial data, and then make scientific plan of data use based on obtaining the hidden knowledge. The experiments indicate that this method holds higher efficiency and better experience feeling.

Key words: multi-source vector spatial data, usability, visual analysis, human-computer interaction, visualization

中图分类号: