测绘通报 ›› 2020, Vol. 0 ›› Issue (4): 116-120.doi: 10.13474/j.cnki.11-2246.2020.0123

• 技术交流 • 上一篇    下一篇

土地利用图中线状要素综合的质量评价

王晓妍1,2   

  1. 1. 燕山大学信息科学与工程学院, 河北 秦皇岛 066004;
    2. 燕山大学河北省软件工程重点实验室, 河北 秦皇岛 066004
  • 收稿日期:2019-07-08 修回日期:2019-09-05 出版日期:2020-04-25 发布日期:2020-05-08
  • 作者简介:王晓妍(1986-),女,博士,副教授,研究方向为地图综合和土地信息系统。E-mail:wxyhmm@163.com
  • 基金资助:
    燕山大学基础研究专项青年课题(16LGB010);河北省教育厅高等学校科技计划重点项目(ZD2018219);国家自然科学基金面上项目(61671401)

Quality evaluation of generalization of linear features in land use map

WANG Xiaoyan1,2   

  1. 1. School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, China;
    2. Key Laboratory of Hebei Software Engineering, Yanshan University, Qinhuangdao 066004, China
  • Received:2019-07-08 Revised:2019-09-05 Online:2020-04-25 Published:2020-05-08

摘要: 作为土地利用图综合的一个重要组成部分,线状要素综合质量的好坏对于有效提高自动制图综合的正确率具有重要意义。本文基于模糊综合评判理论对土地利用图中线状要素的综合进行了质量评价。首先,基于制图综合约束,确定评价指标体系,组成评价因素集;其次,在确定评判集和权重集的基础上,建立线状要素综合质量评价模型;最后,利用试验验证了评价方法的有效性。该研究为客观评价土地利用图中线状要素的综合质量提供了新的思路。

关键词: 地图综合, 土地利用图, 线状要素, 质量评价, 模糊综合评判

Abstract: As an important component of land use map generalization, the comprehensive quality of linear features has great significance to improve the accuracy of automatic cartographic generalization. So based on the theory of fuzzy comprehensive evaluation, quality evaluation of comprehensive linear features in land use map will be studied in this paper. First of all, evaluation indicators,which include geometric factors, topological factors, structural factors and gestalt factors are chose using method of cartographic generalization constraints. Secondly, evaluation rank and weight set are confirmed, and then a quality evaluation model of comprehensive linear features will be built. At last, the validity of the evaluation method will be verified by experiment. It is concluded that the quality evaluation model in this paper can be provided a new thought for evaluating generalization quality of linear features in land use map.

Key words: map generalization, land use map, linear features, quality evaluation, fuzzy comprehensive evaluation

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