Snow Cover Detection Based on Visible Red and Blue Channel from MODIS Imagery Data

Abstract

In the present work, a new snow cover detection method based on visible red and blue bands from MODIS imagery data is proposed for Akita prefecture under the sunny cloud-free conditions. Before the snow cover detection, the MODIS imagery of the study area is pre-processed by geographic correction, clipping, atmospheric correction and topographic correction. Snow cover detection is carried out by applying the reflectance similarities of snow and other substances in the visible red band 1 and blue band 3. Then, the threshold values are confirmed to distinguish snow pixels from other substances by analyzing the composited true color images and 2-dimensional scatter plots. The MOD10_L2 products and in-situ snow depth data from 31 observation stations across the whole study area are chosen to compare and validate the effectivity of proposed method for snow cover detection. We calculate the overall accuracy, over-estimation error and under-estimation error of snow cover detection during the snowy season from May 2012 to April 2014, and the results are compared by classifying all of the observation stations into forest areas, basin areas and plain areas. It proves that the snow cover can be detected effectively in Akita prefecture by the proposed method. And the average overall accuracy of proposed method is higher than MOD10_L2 product, improved by 26.27%. The proposed method is expected to improve the environment management and agricultural development for local residents.