东北大学学报(自然科学版) ›› 2021, Vol. 42 ›› Issue (11): 1585-1590.DOI: 10.12068/j.issn.1005-3026.2021.11.010

• 资源与土木工程 • 上一篇    下一篇

基于并行叠加的国土空间开发适宜性评价

杨宜舟1, 吴立新2, 郭甲腾1, 刘善军1   

  1. (1. 东北大学 资源与土木工程学院, 辽宁 沈阳110819; 2. 中南大学 地球科学与信息物理学院, 湖南 长沙410083)
  • 修回日期:2020-12-24 接受日期:2020-12-24 发布日期:2021-11-19
  • 通讯作者: 杨宜舟
  • 作者简介:杨宜舟(1987 -),男,湖北荆门人,东北大学博士研究生; 吴立新(1966-),男,江西宜春人,中南大学教授,博士生导师; 刘善军(1965-),男,河北涿鹿人,东北大学教授,博士生导师.
  • 基金资助:
    国家高技术研究发展计划项目(2011AA120302).

Assessment of Suitability of Land Space Development Based on Parallel Spatial Overlay Analysis

YANG Yi-zhou1, WU Li-xin2, GUO Jia-teng1, LIU Shan-jun1   

  1. 1. School of Resources & Civil Engineering, Northeastern University, Shenyang 110819, China; 2. School Geosciences & Infor-Physics, Central South University, Changsha 410083, China.
  • Revised:2020-12-24 Accepted:2020-12-24 Published:2021-11-19
  • Contact: YANG Yi-zhou
  • About author:-
  • Supported by:
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摘要: 在国土空间大数据环境下,基于传统串行叠加分析计算的国土空间开发适宜性评价性能已达极限,需研究并行化方法,以利用更多的计算资源提升国土空间开发适宜性评价的效率.在分析基于多空间对象叠加综合评价原理的基础上,通过引入空间数据预处理方法、空间数据划分方法及并行空间索引,提出并实现了以并行叠加分析为核心的国土空间开发适宜性评价方法.西南四省的国土空间建设用地适宜性评价应用实验表明:本文方法相比传统方法性能提升了至少30倍,且节约了大量的人力物力资源,解决了传统架构下国土空间开发适宜性评价计算效率低或无法胜任的难题.

关键词: 空间开发;适宜性评价;并行空间索引;空间数据划分;叠加分析

Abstract: In the environment of land space big data, the performance of spatial development suitability evaluation based on serial superposition analysis has reached the extreme. In order to use more computing resources to improve the efficiency of spatial development suitability evaluation, it is necessary to study the parallelization method. Based on overlay analysis for multi factor of the principle of comprehensive evaluation, the spatial data preprocessing method, spatial data partition method and parallel spatial index are introduced, and the spatial development suitability evaluation based on parallel overlay analysis is realized. The application of this method in the suitability evaluation of space construction land in four provinces in Southwest China breaks the situation of low efficiency or incompetence in large-scale calculation under the traditional framework, and the efficiency has increased more than 30 times.

Key words: spatial development; suitability assessment; parallel spatial index; spatial data partitioning; overlay analysis

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