Abstract
Satellite data has often been used to investigate damage from natural disasters (e.g., flood, drought, forest fire and volcano eruption) close to real-time. In particular, Terra/MODIS and Aqua/MODIS have been widely used for retrieving information on natural disasters and land cover changes because of their advantage of good ground resolution (maximum 250 m) and daily availability (full daily coverage of the Earth). However, the observation of areas covered by clouds using optical sensors does not work. Although the composite method is widely used to reduce the influence of clouds, clouds are likely to remain in some compositing periods. This paper presents the White Object Index (WOI), used for estimating the cloud fraction of a pixel in satellite imagery. The WOI was obtained from differences in reflectance of visible and short-wave infrared spectral bands using a mixture model. The efficiency of the WOI was tested by comparing the maximum value composite (MVC) method with MOD35 using time series data. As a result, WOI was confirmed to be an efficient tool for estimating the influence of clouds within a pixel.
