测绘通报 ›› 2018, Vol. 0 ›› Issue (5): 65-70,135.doi: 10.13474/j.cnki.11-2246.2018.0145

• 学术研究 • 上一篇    下一篇

“高分一号”卫星影像业务流程化处理平台研究

孙钰珊1,2, 艾海滨2, 韩晓霞2   

  1. 1. 武汉大学测绘学院, 湖北 武汉 430079;
    2. 中国测绘科学研究院, 北京 100830;
    3. 城市空间信息工程北京市重点实验室, 北京 100038
  • 收稿日期:2017-09-23 修回日期:2017-12-26 出版日期:2018-05-25 发布日期:2018-05-31
  • 作者简介:孙钰珊(1982-),女,博士生,助理研究员,研究方向为摄影测量与遥感、高分辨率遥感影像数据处理。E-mail:sunys@casm.ac.cn
  • 基金资助:

    中国测绘科学研究院基本科研业务项目(7771608);城市空间信息工程北京市重点实验室开放研究课题(2015207)

Business Flow Processing System Applied for GF1 High Resolution Satellite Imagery

SUN Yushan1,2, AI Haibin2, HAN Xiaoxia2   

  1. 1. School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China;
    2. Chinese Academy of Surveying & Mapping, Beijing 100830, China;
    3. Beijing Key Laboratory of Urban Spatial Information Engineering, Beijing 100038, China
  • Received:2017-09-23 Revised:2017-12-26 Online:2018-05-25 Published:2018-05-31

摘要:

应用高时间分辨率、高空间分辨率、高光谱、高重叠度等成像方式为对地观测提供大量数据的同时,也给数据处理和数据产品的生产带来了新的挑战。本文针对“高分一号”卫星影像的特点,通过对高分辨率卫星影像数据处理核心算法和一键式全流程自动化处理关键技术的研究,提出了一种主体基于C/S架构的业务流程化数据处理平台。该平台融合了GPU与CPU异构计算架构,能够根据不同卫星影像产品需求实现相应的业务流程化处理,有效提高了影像产品生产的自动化程度和业务灵活性。为了验证该平台的可行性,本文给出了实际的数据生产案例,结果表明,该平台能够实现“高分一号”卫星影像数据的业务流程化处理,能够在减少人工干预的同时生产各级影像校正产品和专题影像产品。

关键词: 高分一号, 卫星影像, 影像处理, 业务流程, 任务调度, 生产调度, 质量检查, GPU/CPU, 并行计算

Abstract:

Multiple imaging modes such as high time resolution, high space resolution, hyperspectral and high overlaps acquire mass data for surveying and mapping, and also bring new challenges for image processing technology. In this paper, based on the features of the GF1 satellite imagery and the research of high resolution satellite imagery processing algorithm and key technology of automatic processing flow, we proposed a C/S architecture based business flow processing system for the GF1 high resolution satellite imagery. The system supports the heterogeneous computing of GPU and CPU and can customize the business flow accroding to the different demands of the satellite imagery production, the system is able to improve the automation and business flexibility for the high resolution satellite imagery processing. To verify feasibility of the system, we show several experiments about the production of the satellite imagery products. The results show that the proposed business flow system has the capability of massive parallel processing for GF1 satellite images based on the different business demand, and reducing the manual intervention while producing the correcting imagery and thematic imagery.

Key words: GF1, satellite imagery, image processing, business flow, task scheduling, production scheduling, quality checking, GPU/CPU, parallel computing

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