Cloud detection method for Pleiades images using spectral indices

Autor:	Y Prabowo, D S Candra, Shadiq Ali
Rok vydání:	2020
Předmět:	History Computer science business.industry Cloud cover Omission error Cloud detection Satellite Cloud computing Pleiades business Computer Science Applications Education Remote sensing
Zdroj:	Journal of Physics: Conference Series. 1528:012011
ISSN:	1742-6596 1742-6588
DOI:	10.1088/1742-6596/1528/1/012011
Popis:	Satellite images such as Pleiades have been widely used to monitor the earth. But there is a main issue regarding cloud cover which interferes the information of the images. Another issue is that there are very few studies discussing cloud detection for very-high-spatial-resolution such as Pleiades imagery. In this study, we proposed a cloud detection approach for Pleiades images to address these issues. In the first step, whiteness test was used to detect thick cloud. We also used modified HOT test in the second step to address the issue of detecting thin cloud. We modified the original HOT algorithm to decrease the omission error especially caused by thin cloud. We used visual assessments to evaluate the results. As a result, we found that cloud can be detected accurately by combining these algorithms. The results showed that the proposed approach can be used to detect cloud for Pleaides-1A images.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::9b4165a4f13b7d6c1a1c466a3ea83a43 https://doi.org/10.1088/1742-6596/1528/1/012011 Zobrazit plný text záznamu