Abstract - Two cloud masking methods suitable for Malaysian conditions were developed, based on spectral analysis and principal component 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 ratio band 2/band_1 and the difference between bands 29 and 31 in to detect clouds. 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 images and geographic information about the study area. Key words: cloud masking, spectral analysis, principal component analysis, reflectance, brightness temperature1. INTRODUCTION Typically, 50% of the Earth's surface is covered by clouds at any time, with clouds defined as a visible mass of condensed water droplets or ice crystals suspended in the atmosphere at -above the surface of the Earth. In remote sensing, clouds are generally characterized by higher reflectance and lower temperature than the background. Thick, opaque clouds block almost all information from or near the surface, while thin clouds exhibit some physical characteristics similar to other atmospheric constituents. Misinterpretation of clouds can lead to inaccuracy in 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 have been designed for the global scale (Rossow & Gardner 1993; Ackerman et al 2002), and few...... middle of paper ...... ration mapping. Photogrammetry Engineering and Remote Sensing, 57, p.1163-1169. Rossow, W. B. and Gardner, 1993. Cloud detection using satellite measurement of infrared and visible radiances for ISCCP. Journal of Climate, 6, p.2341 – 2369. Saunders, RW & Kriebel, KT, 1988. An improved method for detecting clear sky and cloud radiation from AVHRR data. International Journal of Remote Sensing, 9, p.123 –150. Saunders, RW, 1986. An automated system for the removal of cloud contamination by AVHRR radiation over Western Europe. International Journal of Remote Sensing, 7, p.867 – 886. Swain, PH and Davis, SM, 1978. Remote sensing: the quantitative approach. New York: McGraw-Hill.Yhann, SR & Simpson, JJ, 1995. Application of neural networks to AVHRR cloud segmentation. IEEE Transactions on Geoscience and Remote Sensing, 33, p..590 – 604.