TITLE:
Snow Cover Detection Based on Visible Red and Blue Channel from MODIS Imagery Data
AUTHORS:
Paipai Pan, Guoyue Chen, Kazuki Saruta, Yuki Terata
KEYWORDS:
Akita, MODIS, Remote Sensing, Snow Cover
JOURNAL NAME:
International Journal of Geosciences,
Vol.6 No.1,
January
28,
2015
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 andin-situsnow 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.