Essay about A Localised Cloud Masking Method for Malaysia

Essay about A Localised Cloud Masking Method for Malaysia

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Abstract - Two methods of cloud masking tuned to Malaysian conditions have been developed, based on spectral analysis and Principal Components Analysis (PCA) of MODIS 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 test 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.

Keywords: Cloud masking, spectral analysis, Principal Components Analysis , reflectance, brightness temperature


Typically, 50% of the Earth’s surface is covered by cloud at any time, where cloud is defined as a visible mass of condensed water droplets or ice crystals suspended in the atmosphere above the Earth's surface. In remote sensing, clouds are generally characterized by higher reflectance and lower temperature than the background. Thick opaque cloud blocks almost all information from the surface or near surface, while thin cloud has some physical characteristics similar to other atmospheric constituents. Misinterpretation of cloud may result in inaccuracy of various remote sensing applications, ranging from land cover classification to retrieval of atmospheric constituents (e.g. in air pollution studies).

Several cloud detection and masking studies have been reported in the literature. However, most of these algorithms were designed for the global scale (Rossow & Gardner 1993; Ackerman et al 2002), and little e...

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...ration mapping. Photogrammetry Engineering and Remote Sensing, 57, p.1163-1169.

Rossow, W.B., & Gardner, 1993. Cloud detection using satellite measurement of infrared and visible radiances for ISCCP. Journal of Climate, 6, p.2341 – 2369.

Saunders, R. W. & Kriebel, K. T., 1988. An improved method for detecting clear sky and cloudy radiances from AVHRR data. International Journal of Remote Sensing, 9, p.123 –150.

Saunders, R.W., 1986. An automated scheme for the removal of cloud contamination form AVHRR radiances over Western Europe. International Journal of Remote Sensing, 7, p.867 – 886.

Swain, P. H., & Davis, S. M., 1978. Remote Sensing: The Quantitative Approach. New York: McGraw-Hill.

Yhann, S. R. & Simpson, J. J., 1995. Application of neural networks to AVHRR cloud segmentation. IEEE Transactions on Geoscience and Remote Sensing, 33, p.590 – 604.

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