Cloud Masking for Remotely Sensed Data Using Spectral and Principal Components Analysis

Asmala, A. and Shaun, Quegan (2012) Cloud Masking for Remotely Sensed Data Using Spectral and Principal Components Analysis. ETASR - Engineering, Technology & Applied Science Research, 2 (3). pp. 221-225. ISSN 1792-8036

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Abstract

Two methods of cloud masking tuned to tropical conditions have been developed, based on spectral analysis and Principal Components Analysis (PCA) of MODIS (Moderate Resolution Imaging Spectroradiometer) data. In the spectral approach, thresholds were applied to four reflective bands (1, 2, 3, and 4), three thermal bands (29, 31 and 32), the band 2/band 1 ratio, and the difference between band 29 and 31 in order to detect cloud. The PCA approach applied a threshold to the first principal component derived from the seven quantities used for spectral analysis. Cloud detections were compared with the standard MODIS cloud mask, and their accuracy was assessed using reference images and geographical information on the study area.

Item Type:	Article
Uncontrolled Keywords:	cloud masking; spectral analysis; principal components analysis; reflectance; brightness temperature
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Faculty of Information and Communication Technology > Department of Industrial Computing
Depositing User:	Dr. Asmala Ahmad
Date Deposited:	29 Jun 2012 01:11
Last Modified:	01 Oct 2021 12:07
URI:	http://eprints.utem.edu.my/id/eprint/3384
Statistic Details:	View Download Statistic

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