DocumentCode :
1681924
Title :
Rapid Calculation Research on Water Area Extraction from ASAR Image
Author :
Lingjun, Zhao ; Yan, Ma ; GuoQing, Li ; Wenyang, Yu ; Jing, Zhang
Author_Institution :
Center for Earth Obs. & Digital Earth, Chinese Acad. of Sci., Beijing, China
fYear :
2009
Firstpage :
339
Lastpage :
343
Abstract :
Flooded area is a piece of the most important information wepsilave got to know in flood supervision and disaster evaluation. And water area extraction is one of the decisive preconditions in confirming the size of flooded areas. With the appearance of remote sensing technology, people could extract the water areas from the space, and the radar images gotten from the flooded area provide us the exact size of water areas. However, the speed of water area extraction affects flood evaluation directly, which matters a lot to the rescue work after flood. To shorten the extracting time of water areas, parallelization process is used as one of the most efficient ways. Based on some normal methods frequently used in water area extraction, such as threshold method, NDVI, and so on, a new way is put forward, that is, to use Self-organized Feature Map to extract the water areas from ASAR images automatically and accurately, and then to analyze the SOM calculation flows to find out what influences the extraction speed, finally to optimize the calculation by using parallel I/O of parallel file system and the asynchronous parallel model of I/O hidden strategy. All of the above enhances the calculation speed so as to ensure that the subsequent flood evaluation and rescue work can be carried out as soon as possible.
Keywords :
feature extraction; geophysics computing; radar imaging; remote sensing by radar; self-organising feature maps; synthetic aperture radar; ASAR image; I/O hidden strategy; advanced synthetic aperture radar; asynchronous parallel model; decisive preconditions; disaster evaluation; flood supervision; parallel I/O; parallel file system; parallelization process; remote sensing technology; self-organized feature map; threshold method; water area extraction; Data mining; Feature extraction; Floods; Image analysis; Optimization methods; Radar imaging; Radar remote sensing; Remote sensing; Space technology; Spaceborne radar; I/O hidden strategy; parallel I/O; parallel computing; self-organized feature map; water area extraction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Grid and Cooperative Computing, 2009. GCC '09. Eighth International Conference on
Conference_Location :
Lanzhou, Gansu
Print_ISBN :
978-0-7695-3766-5
Type :
conf
DOI :
10.1109/GCC.2009.43
Filename :
5279553
Link To Document :
بازگشت