Abstract - Two cloud masking methods adapted to Malaysian conditions were developed, based on spectral analysis and principal component analysis (PCA) of the data MODIS. 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 to detect the cloud. The PCA test applied a threshold to the first principal component derived from the seven quantities used for the spectral analysis. Cloud detections were compared to the standard MODIS cloud mask and their accuracy was assessed using reference imagery and geographic information on the study area. Keywords: cloud masking, spectral analysis, principal component analysis, reflectance, brightness temperature1. INTRODUCTION Typically, 50% of the Earth's surface is permanently covered by clouds, where cloud is 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. The thick, opaque cloud blocks almost all information from or near the surface, while the thin cloud has some physical characteristics similar to other atmospheric constituents. Misinterpretation of clouds can lead to inaccuracies in various remote sensing applications, ranging from land cover classification to retrieval of atmospheric constituents (e.g. in air pollution studies). Numerous 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 and… middle of the paper… ration mapping. Photogrammetry Engineering and Remote Sensing, 57, p.1163-1169. Rossow, W.B. and Gardner, 1993. Cloud detection by 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 cloud radiation 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 from AVHRR radiation over Western Europe. International Journal of Remote Sensing, 7, p.867 – 886. Swain, P.H. and 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.