Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B2, 95-100, 2016
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B2/95/2016/
doi:10.5194/isprs-archives-XLI-B2-95-2016
 
07 Jun 2016
CLOUD AND CLOUD SHADOW MASKING USING MULTI-TEMPORAL CLOUD MASKING ALGORITHM IN TROPICAL ENVIRONMENTAL
D. S. Candra1,2, S. Phinn1, and P. Scarth1 1Remote Sensing Research Center, School of Geography, Planning and Environmental Management, University of Queensland, Brisbane, Australia
2National Institute of Aeronautics and Space of Indonesia (LAPAN), Jakarta, Indonesia
Keywords: Multitemporal Cloud Masking Algrithm, Cloud, Cloud Shadow, Multitemporal Images, Landsat-8, Tropical Environmental Abstract. A cloud masking approach based on multi-temporal satellite images is proposed. The basic idea of this approach is to detect cloud and cloud shadow by using the difference reflectance values between clear pixels and cloud and cloud shadow contaminated pixels. Several bands of satellite image which have big difference values are selected for developing Multi-temporal Cloud Masking (MCM) algorithm. Some experimental analyses are conducted by using Landsat-8 images. Band 3 and band 4 are selected because they can distinguish between cloud and non cloud. Afterwards, band 5 and band 6 are used to distinguish between cloud shadow and clear. The results show that the MCM algorithm can detect cloud and cloud shadow appropriately. Moreover, qualitative and quantitative assessments are conducted using visual inspections and confusion matrix, respectively, to evaluate the reliability of this algorithm. Comparison between this algorithm and QA band are conducted to prove the reliability of the approach. The results show that MCM better than QA band and the accuracy of the results are very high.
Conference paper (PDF, 1286 KB)


Citation: Candra, D. S., Phinn, S., and Scarth, P.: CLOUD AND CLOUD SHADOW MASKING USING MULTI-TEMPORAL CLOUD MASKING ALGORITHM IN TROPICAL ENVIRONMENTAL, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B2, 95-100, doi:10.5194/isprs-archives-XLI-B2-95-2016, 2016.

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