The importance of snow in providing water supply has led to the fact that the identification and estimation of snow-covered areas is essential. However, field methods are expensive, time-consuming, and hard to do. Therefore, alternative methods are required to overcome the difficulties with field approaches. Remote sensing and GIS techniques can be used as effective approaches to estimate snow characteristics compared to traditional field methods. In this study, MODIS images were used to satisfy this objective in the Saghez basin, Kurdistan, Iran. The study used and compared two methods of Pixelbase and Subpixel. These two methods were then compared with IRS images (sensor LISSIII), as ground truth, which have a high spatial resolution (24 m). Therefore, concurrent image of 27 January 2007 by the MODIS and LISSIII sensors of this basin was prepared. The snow-covered areas of the images were compared. The pixels of different regions of the images were selected, compared using t-test. The results of this comparison show that the method of Subpixel compared with Pixelbase has a higher accuracy in the estimation of the snow surface.
