• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2015, Vol. 37 ›› Issue (07): 1325-1330.

• 论文 • Previous Articles     Next Articles

Software design and implementation of snow
cover extraction based on FY-3A/VIRR data  

ZHANG Yonghong1,2,CAO Ting2,REN Wei2 ,TIAN Wei3,WANG Jiangeng4,Yang Runzhi5,LU Jing6   

  1. (1.Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters,
    Nanjing University of Information Science & Technology,Nanjing 210044,China;
    2. School of Information and Control,Nanjing University of Information Science & Technology,Nanjing 210044,China;
    3.School of Computer Science & Technology,Nanjing University of Information Science & Technology,Nanjing 210044,China;
    4.School of Atmospheric Physics,Nanjing University of Information Science & Technology,Nanjing 210044,China;
    5.National Meteorological Information Center,Beijing 100081,China;
    6.Department of Computer Science,Oklahoma State University,Oklahoma 74078,USA)
  • Received:2014-08-29 Revised:2014-11-04 Online:2015-07-25 Published:2015-07-25

Abstract:

So far little research has been carried out on the process of FY3A/VIRR data which has a huge amount of data.Current commercial remote sensing image processing softwares can not accomplish the preprocessing work directly.So it brings great difficulties in subsequent image processing and the spread of FY3A/VIRR data. In order to solve this problem,we combine a modified normalized difference snow index (NDSI) and the comprehensive threshold method with IDL and VB mixed technology,and design a snow information batch extraction software.We achieve the snow information extraction and accuracy validation of a single image or multiple images for FY3A/VIRR data.Experimental results show that the proposed software is fast and realtime,and it can do batch extraction of snow information,thus saving great human resources and improving the ability of dispatching and sharing the VIRR data. It can be extended in industrial production and automation in the future.

Key words: FY-3A/VIRR;pre-processing;snow information extraction;batch extraction