• Korean Journal of Remote Sensing
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• v.23 no.6
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• pp.507-520
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• 2007

Satellite passive microwave(PM) sensors have been observing polar sea ice concentration(SIC), ice temperature, and snow depth since 1970s. Among them SIC is playing an important role in the various studies as it is considered the first factor for the monitoring of global climate and environment changes. Verification and correction of PM SIC is essential for this purpose. In this study, we calculated SIC from KOMPSAT-1 EOC images obtained from Arctic sea ice edges from July to August 2005 and compared with SSM/I SIC calculated from NASA Team(NT) algorithm. When we have no consideration of sea ice types, EOC and SSM/I NT SIC showed low correlation coefficient of 0.574. This is because there are differences in spatial resolution and observing time between two sensors, and the temporal and spatial variation of sea ice was high in summer Arctic ice edge. For the verification of SSM/I NT SIC according to sea ice types, we divided sea ice into land-fast ice, pack ice, and drift ice from EOC images, and compared them with SSM/I NT SIC corresponding to each ice type. The concentration of land-fast ice between EOC and SSM/I SIC were calculated very similarly to each other with the mean difference of 0.38%. This is because the temporal and spatial variation of land-fast ice is small, and the snow condition on the ice surface is relatively dry. In case of pack ice, there were lots of ice ridge and new ice that are known to be underestimated by NT algorithm. SSM/I NT SIC were lower than EOC SIC by 19.63% in average. In drift ice, SSM/I NT SIC showed 20.17% higher than EOC SIC in average. The sea ice with high concentration could be included inside the wide IFOV of SSM/I because the drift ice was located near the edge of pack ice. It is also suggested that SSM/I NT SIC overestimated the drift ice covered by wet snow.

• The Korean Journal of Nuclear Medicine
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• v.35 no.6
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• pp.378-388
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• 2001

Purpose: In this study, we developed a new method for the determination of renal depth with anterior and posterior renal scintigrams in a dual-head gamma camera, considering the attenuation factor $e^{-{\mu}x}$ of the conjugate-view method. Material and Method: We developed abdomen and kidney phantoms to perform experiments using Technetium-99m dimercaptosuccinic acid ($^{99m}Tc$-DMSA). The phantom images were obtained by dual-head gamma camera equipped with low-energy, high-resolution, parallel-hole collimators (ICONf, Siemens). The equation was derived from the linear integration of omission ${\gamma}$-ray considering attenuation from the posterior abdomen to the anterior abdomen phantom surface. The program for measurement was developed by Microsoft Visual C++ 6.0. Results : Renal depths of the phantoms were derived from the derived equations and compared with the exact geometrical values. Differences between the measured and the calculated values were the range of 0.1 to 0.7 cm ($0.029{\pm}0.15cm,\;mean{\pm}S.D.$). Conclusion: The present study showed that the use of the derived equations for renal depth measurements, combined with quantitative planar imaging using dual-head gamma camera, could provide more accurate results for individual variation than the conventional method.