| Budget Amount *help |
¥1,700,000 (Direct Cost: ¥1,700,000)
Fiscal Year 1997: ¥500,000 (Direct Cost: ¥500,000)
Fiscal Year 1996: ¥1,200,000 (Direct Cost: ¥1,200,000)
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| Research Abstract |
Measurement of the seasonal cycle and interannual variations of Antarctic sea ice is important for investigations of global climate and ship navigation. While satellite data give a great amount of information about ice conditions, there still remains a need for in situ validations. Resolution of ground truth reference data is much higher than NOAA satellite data. In order to compare the ground truth data with satellite data, analyzing area of ground truth data have to be expanded by patching the ground based data continuously ; and both need to be analyzed quantitatively.
In the video image analysis, a technique for measuring sea ice characteristics over a wide area using video images taken from a ship is proposed. The sea ice was photographed by video camera from the ship. Continuous video images are obtained using geometric transformation and template matching. Both size of the ice and concentration along the ship's route can be obtained continuously.
The other hand, remote sensing obs
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ervation from a meteorological satellite offers the best available means to understand polar surface conditions, because of their homogeneity over a wide area. However, in the polar region, cloud, snow and ice have almost the same albedo in the visible channel and the same brightness temperature in the infrared channel. Therefore, it is difficult to distinguish among these regions using only the threshold of gray level of a satellite image. In this work, a method to classify clud, sea ice and ground is proposed. This study is based upon analysis of the NOAA/AVHRR infrared images in Antarctica. The algorithm consists of two major approaches : extraction of image features and a classification algorithm. Minimum distance classifier was used to classify that region into one of three categories using five image features. To improve the classification accuracy, threshold boundaries for minimum distance classifier were changed. Both classified and misclassfied areas were decreased with increasing the threshold levels. In geneal, the error rates will be decided according to the purpose.
Since both methods of anarysis of sea ice characteristics using video image and extraction of sea ice area using satellite data, it is useful for exanining tke correlation of these two data. Less
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