• Journal of the Institute of Electronics Engineers of Korea TC
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• 제45권8호
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• pp.114-120
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• 2008

In this paper, we extract the parasitic elements of the metal-insulate-metal(MIM) capacitor using short-open calibration (SOC). The scattering matrixes of short, open, and MIM structures in strip lines are measured by full electro-magnetic (EM) simulator and vector network analyser. The full EM simulations are performed by finite element method (FEM) that was fitted three dimensional structure analysis. The electro-magnetic effects of MIM capacitor laminated in the multi-layered structures are proposed the II equivalent circuit with lumped elements, and the relations between the measured scattering parameters of the MIM structures and lumped elements in the circuits are shown by performing 2 port network analysis. The extracted lumped elements using the proposed SOC method are independent to frequencies.

• Korean Journal of Remote Sensing
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• 제23권6호
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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.

• Korean Journal of Remote Sensing
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• 제38권5_2호
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• pp.747-763
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• 2022

Ocean salinity affects ocean circulation on a global scale and low salinity water around coastal areas often has an impact on aquaculture and fisheries. Microwave satellite sensors (e.g., Soil Moisture Active Passive [SMAP]) have provided sea surface salinity (SSS) based on the dielectric characteristics of water associated with SSS and sea surface temperature (SST). In this study, a Light Gradient Boosting Machine (LGBM)-based model for generating high resolution SSS from Geostationary Ocean Color Imager (GOCI) data was proposed, having machine learning-based improved SMAP SSS by Jang et al. (2022) as reference data (SMAP SSS (Jang)). Three schemes with different input variables were tested, and scheme 3 with all variables including Multi-scale Ultra-high Resolution SST yielded the best performance (coefficient of determination = 0.60, root mean square error = 0.91 psu). The proposed LGBM-based GOCI SSS had a similar spatiotemporal pattern with SMAP SSS (Jang), with much higher spatial resolution even in coastal areas, where SMAP SSS (Jang) was not available. In addition, when tested for the great flood occurred in Southern China in August 2020, GOCI SSS well simulated the spatial and temporal change of Changjiang Diluted Water. This research provided a potential that optical satellite data can be used to generate high resolution SSS associated with the improved microwave-based SSS especially in coastal areas.

• Korean Journal of Remote Sensing
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• 제33권6_1호
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• pp.947-960
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• 2017

Soil moisture plays an important role to affect the Earth's radiative energy balance and water cycle. In general, satellite observations are useful for estimating the soil moisture content. Passive microwave satellites have an advantage of direct sensitivity on surface soil moisture. However, their coarse spatial resolutions (10-36 km) are not suitable for regional-scale hydrological applications. Meanwhile, in-situ ground observations of point-based soil moisture content have the disadvantage of spatially discontinuous information. This paper presents an experimental soil moisture retrieval using Sentinel-1 SAR (Synthetic Aperture Radar) with 10m spatial resolution for cropland in South Korea. We developed a soil moisture retrieval algorithm based on the technique of linear regression and SVR (support vector regression) using the ground observations at five in-situ sites and Sentinel-1 SAR data from April to October in 2015-2017 period. Our results showed the polarization dependency on the different soil sensitivities at backscattered signals, but no polarization dependence on the accuracies. No particular seasonal characteristics of the soil moisture retrieval imply that soil moisture is generally more affected by hydro-meteorology and land surface characteristics than by phenological factors. At the narrower range of incidence angles, the relationship between the backscattered signal and soil moisture content was more distinct because the decreasing surface interference increased the retrieval accuracies under the condition of evenly distributed soil moisture (during the raining period or on the paddy field). We had an overall error estimate of RMSE (root mean square error) of approximately 6.5%. Our soil moisture retrieval algorithm will be improved if the effects of surface roughness, geomorphology, and soil properties would be considered in the future works.

• Korean Journal of Remote Sensing
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• 제34권6_2호
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• pp.1273-1282
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• 2018

Recently, active research on the Arctic Ocean has been conducted due to the influence of global warming and new Arctic ship route. Although previous studies already calculated quantitative extent of sea ice using passive microwave radiometers, melting at the edge of sea ice and surface roughness were hardly considered due to low spatial resolution. Since Sentienl-1A/B data in Extended Wide (EW) mode are being distributed as free of charge and bulk data for Arctic sea can be generated during a short period, the entire Arctic sea ice data can be covered in high spatial resolution by mosaicking bulk data. However, Sentinel-1A/B data in EW mode, especially in HV polarization, needs significant radiometric correction for further classification. Thus, in this study, we developed algorithms that can correct thermal noise and scalloping effects, and confirmed that Arctic sea ice and open-water were well classified using the corrected dual-polarization SAR data.

• Korean Journal of Remote Sensing
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• 제39권3호
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• pp.257-268
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• 2023

Sea ice plays an important role in Earth's climate by regulating the amount of solar energy absorbed and controlling the exchange of heat and material across the air-sea interface. Its growth, drift, and melting are monitored on a regular basis by satellite observations. However, low-resolution products with passive microwave radiometer have reduced accuracy during summer to autumn when the ice surface changes rapidly. Synthetic aperture radar (SAR) observations are emerging as a powerful complementary, but previous researches have mainly focused on winter ice. In this study, sea ice drift tracking was evaluated and analyzed using SAR images and tracker with global positioning system (GPS) during late summer-early autumn period when ice surface condition changes a lot. The results showed that observational uncertainty increases compared to winter period, however, the correlation coefficient with GPS measurements was excellent at 0.98, and the performance of the ice tracking algorithm was proportional to the sea ice concentration with a correlation coefficient of 0.59 for ice concentrations above 50%.

• Journal of the Korean earth science society
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• 제39권2호
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• pp.139-153
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• 2018

The sea surface wind field has long been obtained from satellite scatterometers or passive microwave radiometers. However, the importance of satellite altimeter-derived wind speed has seldom been addressed because of the outstanding capability of the scatterometers. Satellite altimeter requires the accurate wind speed data, measured simultaneously with sea surface height observations, to enhance the accuracy of sea surface height through the correction of sea state bias. This study validates the wind speeds from the satellite altimeters (GFO, Jason-1, Envisat, Jason-2, Cryosat-2, SARAL) and analyzes characteristics of errors. In total, 1504 matchup points were produced using the wind speed data of Ieodo Ocean Research Station (IORS) and of Korea Meteorological Administration (KMA) buoys at Marado and Oeyeondo stations for 10 years from December 2007 to May 2016. The altimeter wind speed showed a root mean square error (RMSE) of about $1.59m\;s^{-1}$ and a negative bias of $-0.35m\;s^{-1}$ with respect to the in-situ wind speed. Altimeter wind speeds showed characteristic biases that they were higher (lower) than in-situ wind speeds at low (high) wind speed ranges. Some tendency was found that the difference between the maximum and minimum value gradually increased with distance from the buoy stations. For the improvement of the accuracy of altimeter wind speed, an equation for correction was derived based on the characteristics of errors. In addition, the significance of altimeter wind speed on the estimation of sea surface height was addressed by presenting the effect of the corrected wind speeds on the sea state bias values of Jason-1.