地理科学进展 ›› 2016, Vol. 35 ›› Issue (4): 401-408.doi: 10.18306/dlkxjz.2016.04.001

• 研究综述 •    下一篇

高精度曲面建模方法研究进展与分类

赵明伟1,**(), 岳天祥2   

  1. 1. 滁州学院,安徽省地理信息集成应用协同创新中心,安徽 滁州 239000
    2. 中国科学院地理科学与资源研究所,资源与环境信息系统国家重点实验室,北京 100101
  • 出版日期:2016-04-27 发布日期:2016-04-27
  • 通讯作者: 赵明伟 E-mail:zhaomw@lreis.ac.cn
  • 作者简介:

    作者简介:赵明伟(1986-),男,山东莱芜人,博士,讲师,主要研究方向为高精度曲面建模与环境生态信息学,E-mail: zhaomw@lreis.ac.cn

  • 基金资助:
    国家自然科学基金创新群体项目(41421001);安徽省教育厅高校自然科学研究重点项目(KJ2016A536)

Classification of high accuracy surface modeling (HASM) methods and their recent developments

Mingwei ZHAO1,*(), Tianxiang YUE2   

  1. 1. Anhui Center for Collaborative Innovation in Geographical Information Integration and Application, Chuzhou University, Chuzhou 239012, Anhui, China
    2. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
  • Online:2016-04-27 Published:2016-04-27
  • Contact: Mingwei ZHAO E-mail:zhaomw@lreis.ac.cn
  • Supported by:
    Science Fund for Creative Research Groups of the National Natural Science Foundation of China, No.41421001;Key Project of Natural Science Research of Anhui Provincial Department of Education, No;KJ2016A536

摘要:

高精度曲面建模方法(HASM)作为新一代的曲面模拟方法,经过20多年的发展,其理论体系不断完善,算法体系不断丰富,应用领域不断拓广。然而,目前HASM方法尚未建立科学的分类体系,仅依据求解算法为标准进行简单区分,忽视了HASM所研究问题本质上的差异,阻碍了HASM方法在相关领域的进一步应用。为此,本文在总结HASM方法发展过程的基础上,按照研究问题的本质特点,以输入数据的类型为依据,将HASM分为空间插值方法和空间数据融合方法。其中,HASM空间插值方法是根据离散采样点得到目标曲面,而HASM空间数据融合方法则是融合多源数据,并综合各个数据源优势而得到新曲面的过程。该分类科学、合理,为今后HASM方法的进一步应用提供了理论指导。最后本文叙述了应用两种HASM方法求解问题时的一般步骤,同时还对两种方法的发展前景进行了展望。

关键词: 高精度曲面建模方法(HASM), 精度, 空间插值, 数据融合, 综述

Abstract:

High accuracy surface modeling (HASM) is a new generation of surface simulation method. After 20 years of development, its theoretical basis has continuously improved, the algorithm is enriched, and the application field is expanding. However, a scientific classification system of HASM methods has not been established and this has prevented further application of HASM in various fields. To solve this problem, this article first summarizes the development process of HASM, then according to the nature of given research problems, HASM is divided into spatial interpolation and spatial data fusion methods based on the type of input data. The HASM spatial interpolation method generates target surface according to discrete sampling points. The HASM spatial data fusion method is the fusion of multi-source data that integrates the advantages of each data source to obtain a new surface. This classification provides a theoretical guidance for the further application of HASM. The article also introduces the general steps of solving spatial simulation problems using the two HASM methods, and the development prospect of the two methods is discussed.

Key words: high accuracy surface modeling (HASM), accuracy, interpolation, data fusion, review