• Journal of Satellite, Information and Communications
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• v.7 no.2
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• pp.87-96
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• 2012

In this research, we describe recent technologies and system requirements of the passive microwave radiometer used in Earth observation satellites. And we classify types of microwave radiometer system for Earth observation satellites according to observation targets and ways to scan and discuss a design method. Also, requirements of passive radiometer for Earth observation missions in the latest practical examples used and developed are analyzed in this research.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.19-28
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• 2005

Passive microwave remote sensing technique have shown great potential for mon monitoring regional/global surface soil moisture. Given a single measurement at dual polarization/single frequency/single view angle, a strategic approach to artificially generating multiple microwave brightness temperatures is presented. And then the statistically generated microwave brightness temperature data are applied to the inverse algorithm, which mainly relies on a physically based microwave emission model and an advanced single-criterion multi-parameter optimization technique, to simultaneously retrieve soil moisture and vegetation characteristics. . The procedure is tested with dual polarized Tropical Rainfall Measurement Mission Microwave Imager (TRMM/TMI) over two different cover sites in Oklahoma and Beltsville field experimental data. The retrieval results are analyzed and show excellent performance.

• Journal of Astronomy and Space Sciences
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• v.33 no.4
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• pp.305-311
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• 2016

The spatial size and variation of Arctic sea ice play an important role in Earth's climate system. These are affected by conditions in the polar atmosphere and Arctic sea temperatures. The Arctic sea ice concentration is calculated from brightness temperature data derived from the Defense Meteorological Satellite program (DMSP) F13 Special Sensor Microwave/Imagers (SSMI) and the DMSP F17 Special Sensor Microwave Imager/Sounder (SSMIS) sensors. Many previous studies point to significant reductions in sea ice and their causes. We investigated the variability of Arctic sea ice using the daily sea ice concentration data from passive microwave observations to identify the sea ice melting regions near the Arctic polar ice cap. We discovered the abnormal melting of the Arctic sea ice near the North Pole during the summer and the winter. This phenomenon is hard to explain only surface air temperature or solar heating as suggested by recent studies. We propose a hypothesis explaining this phenomenon. The heat from the deep sea in Arctic Ocean ridges and/or the hydrothermal vents might be contributing to the melting of Arctic sea ice. This hypothesis could be verified by the observation of warm water column structure below the melting or thinning arctic sea ice through the project such as Coriolis dataset for reanalysis (CORA).

• Korean Journal of Remote Sensing
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• v.20 no.1
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• pp.47-55
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• 2004

We have constructed a level-1 processor to generate brightness temperatures using the direct-broadcast data from the passive microwave radiometer onboard Aqua satellite. Although 50-minute half-orbit data, called a granule, are being routinely produced by global data centers, to our knowledge, this is the first attempt to process 10-minute long direct-broadcast (DB) data. We found that the processor designed for a granule needs modification to apply to the DB data. The modification includes the correction to path number, the selection of land mask and the manipulation of dummy scans. Pixel-to-pixel comparison with a reference indicates the difference in brightness temperature of about 0.2 K rms and less than 0.05 K mean. The difference comes from the different length of data between 50-minute granule and about 10-minute DB data. In detail, due to the short data length, DB data do not always have correct cold sky mirror count. The DB processing system is automated to enable the near-real time generation of brightness temperatures within 5 minutes after downlink. Through this work, we would be able to enhance the use of AMSR-E data, thus serving the objective of direct-broadcast.

• Journal of Satellite, Information and Communications
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• v.7 no.1
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• pp.116-121
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• 2012

For the purpose of drawing out the technological criteria for the development of an Low Earth Orbit Meteorological Satellite some characteristics of infrared and microwave sensors on the payload were analysed by approaching theoretically. In addition, the channel requirements and interface requirements of the microwave sensors equipped on the payloads of the existing foreign Low Earth Orbit Meteorological Satellites were analysed with respect to the development of an Earth Orbit Meteorological Satellite payload. In this paper, the multipurpose satellite bus and the CAS 500 platform as the interface requirements of an Low Earth Orbit Meteorological Satellite, and core subsystem and principle functional requirements of a satellite control system were systematically described.

• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.677-686
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• 2014

Sea ice covers wide area in Terra Nova Bay in East Antarctica where the Jangbogo Antarctic Research Station was built in 2014, which affects greatly on the sailing of an icebreaker research vessel. In this study, we analyzed the optimum sea route and sailable period of the icebreaker to visit the Jangbogo Antarctic Research Station by using sea ice concentration data observed by passive microwave sensors such as Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager/Sounder (SSMIS) for the last decade, and by using sea route of the Araon, an icebreaker of Republic of Korea, from 2010 to 2012. It is found that Araon sailed in the route of sea ice concentration up to 78%. Sailing speed of the Araon decreased due to increasing sea ice concentration. However, Araon maintained the speed close to the average speed for the entire sailing period (~11 kn) in the route of sea ice concentration up to 70%. Therefore, we confirm that the Araon can sail typically in the route which shows sea ice concentration below 70%. We derived annually available sailing period in recent 10 years for the sea route of the Araon in 2010, 2011 and 2012, which is defined as the period showing sea ice concentration below 70% through the route. Maximum sailable period was analyzed to be 61 and 62 days for the route of the Araon in 2010 and 2011, respectively. However, the typical sailing in the routes was unavailable in some years because sea ice concentration was higher than 70% through the routes. Meanwhile, the sailable period for the routes of the Araon in 2012 was observed in every year, which was a minimum of 15 days and is a maximum of 89 days. Therefore, we could suggest that optimum route of icebreaker to visit the Jangbogo Antarctic Research Station is the route of the Araon in 2012. High resolution images from SAR or optical sensors are necessary to investigate sea ice condition near shoreline of Jangbogo research station due to several kilometers of low resolution of sea ice concentration.

• Journal of the Korean earth science society
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• v.31 no.5
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• pp.465-474
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• 2010

Real-time rainfall monitoring is of great practical importance over the highly populated Indochina area, which is prone to natural disasters, in particular in association with rainfall. With the goal of d etermining near real-time half-hourlyrain estimates from satellite, the three-layer, artificial neural networks (ANN) approach was used to train the brightness temperatures at 6.7, 11, and $12-{\mu}m$ channels of the Japanese geostationary satellite MTSAT against passive microwavebased rain rates from Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and TRMM Precipitation Radar (PR) data for the June-September 2005 period. The developed model was applied to the MTSAT data for the June-September 2006 period. The results demonstrate that the developed algorithm is comparable to the PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) results and can be used for flood monitoring across the Indochina area on a half-hourly time scale.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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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.