Snow cover detection based on two-dimensional scatter plots from MODIS imagery data

Snow cover detection (SCD) using remote sensing imagery has received increasing attention since the development of satellite remote sensing technology. In the present work, a SCD method based on two-dimensional (2-D) scatter plots generated from MODIS imagery data over Akita Prefecture in Japan is proposed. The imagery of the study area is preprocessed, including a geographic correction, clipping, an atmospheric correction, and a topographic correction, before SCD is conducted. For this, snow and cloud pixels are extracted from other ground surface features according to a 2-D scatter plot of bands 1 and 3 in the reflectance spectrum. Finally, a snow cover map of Akita Prefecture is obtained after removal of the cloud pixels detected from a 2-D scatter plot of bands 6 and 7. Comparison and validation with AMeDAS in situ snow depth data from the study area shows that the average accuracy obtained from our proposed method represents an improvement of 11.79% over the MOD10A1 product, and 22.05% over the SCD results from a combination of normalized difference snow index and normalized difference vegetation index. In addition, Aomori Prefecture and Mt. Chokaizan are also evaluated as further tests of the proposed method. All results suggest that the proposed method is feasible for SCD in the study areas and can provide information for agricultural development, water resource management, and ecological environment construction. (C) 2015 Society of Photo-Optical Instrumentation Engineers (SPIE).