A Novel Method for Cloud Detection in Modis Imagery

Abstract

Data from the Moderate-Resolution Imaging Spectroradiometer (MODIS) are being widely used for quantitatively estimating parameters in the study of atmospheric and land surface processes. Cloud detection is a preliminarily important step in remotely sensed image processing for many applications. The main purpose of this paper is classification of MODIS image into four classes including cloudy, semi cloudy, snow and clear areas. In this article, we use a new method for MODIS cloud detection based on spatial analysis and generation four RGB images. Several MODIS data were applied to evaluate the performance of the new algorithm and the results show that the new algorithm was acceptable result.