Kyohei Yoshida
Characteristic extraction and comparison collation of a snow distribution history by an MODIS image
Atushi Rikimaru
Snow is a factor to cause a disaster and holds two-facedness to be precious aquatic resources. Therefore it is very important that we grasp snow for time and space. But in late years the snowfall situation shows a big difference year by year. Therefore this study extracts time andĦĦspatial characteristic with MODIS data.
Also, it is thought that a digital camera can observe the latest snow area. Therefore this study collates with a ground picture and a satellite image.
These studies extract the snow area from MODIS data from 2003 to 2006. And I make a snow frequency image of each year. We make a domain by DEM data and a snow frequency image next. And we compare Snow distribution in each domain and extracted an annual characteristic and a domainĦĦcharacteristic .
We performed collation with ASTER data and MODIS data as inspection afterwards. These two accorded percentages were 78.9%.We performed collation with ASTER data and ground observation data next. These two accorded percentages were 58%.Also we compared depth data of the snow with snow distribution as another inspection.
As a result of these, we were able to extract a time characteristic and a spatial characteristic from snow distribution history information.
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