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Proceedings Paper

Automatic cloud coverage assessment of Formosat-2 image
Author(s): Kuo-Hsien Hsu
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Paper Abstract

Formosat-2 satellite equips with the high-spatial-resolution (2m ground sampling distance) remote sensing instrument. It has been being operated on the daily-revisiting mission orbit by National Space organization (NSPO) of Taiwan since May 21 2004. NSPO has also serving as one of the ground receiving stations for daily processing the received Formosat- 2 images. The current cloud coverage assessment of Formosat-2 image for NSPO Image Processing System generally consists of two major steps. Firstly, an un-supervised K-means method is used for automatically estimating the cloud statistic of Formosat-2 image. Secondly, manual estimation of cloud coverage from Formosat-2 image is processed by manual examination. Apparently, a more accurate Automatic Cloud Coverage Assessment (ACCA) method certainly increases the efficiency of processing step 2 with a good prediction of cloud statistic. In this paper, mainly based on the research results from Chang et al, Irish, and Gotoh, we propose a modified Formosat-2 ACCA method which considered pre-processing and post-processing analysis. For pre-processing analysis, cloud statistic is determined by using un-supervised K-means classification, Sobel's method, Otsu's method, non-cloudy pixels reexamination, and cross-band filter method. Box-Counting fractal method is considered as a post-processing tool to double check the results of pre-processing analysis for increasing the efficiency of manual examination.

Paper Details

Date Published: 26 October 2011
PDF: 9 pages
Proc. SPIE 8177, Remote Sensing of Clouds and the Atmosphere XVI, 81770S (26 October 2011); doi: 10.1117/12.897894
Show Author Affiliations
Kuo-Hsien Hsu, National Space Organization (Taiwan)


Published in SPIE Proceedings Vol. 8177:
Remote Sensing of Clouds and the Atmosphere XVI
Evgueni I. Kassianov; Adolfo Comeron; Richard H. Picard; Klaus Schäfer, Editor(s)

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