• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.385-387
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• 2005

Polarimetric measurements of the sky radiation by the PSR-I000, which is the multi-spectral polarimeter developed by the Opt Research Corporation and has the same wavelength regions (443nm, 490nm, 565nm, 670nm, 765nm and 865nm) as the ADEOSII/POLDER sensor, have been carried out at the ground station in Kanazawa city, Japan from March to May. First of all, the wavelength dependency of degrees of polarization is examined and it is shown that degrees of polarization measured under the hazy dust cloud are lower than those measured in the clear sky and decrease as the wavelength increases. Next, a new method for estimating optical properties, such as the optical thickness, the number size distribution and the refractive index, of the Asian dust and the ground reflectance from degrees of polarization measured by PSR-I000 is described. Finally, this method is applied to polarization data acquired on April 15,2002. As a result, it is shown that our estimation algorithm provides a good result.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.343-345
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• 2003

This paper describes the system development for the Ground Control Point collection and management through the major coastline region in KOREA, which will collect and manage the ground control point based on high resolution satellite image database. The module of this system is following 1) GCP/Coarstline research plan module 2) GCP/Coarstline ground collection module 3) GCP/Coarstline post processing module Our team developed the core components of ‘High Resolution Satellite Image Processing Technique’ project, and this system, among applications of our project, is constructed to apply to practical use. In this application, you will also see how to apply core components of our project.

• Korean Journal of Remote Sensing
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• v.35 no.5_2
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• pp.763-772
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• 2019

High-resolution satellites capable of observing the Earth periodically enhance applicability of remote sensing in the field of national disaster management from national disaster pre-monitoring to rapid recovery planning. The National Disaster Management Research Institute (NDMI) has been developed various satellite-based disaster management technologies and applied to disaster site operations related to typhoons and storms, droughts, heavy snowfall, ground displacement, heat wave, and heavy rainfall. Although the limitation of timely imaging of satellite is a challenging issue in emergent disaster situation, it can be solved through international cooperation to cope with global disasters led by domestic and international space development agencies and disaster organizations. This article of special issue deals with the scientific disaster management technologies using remote sensing and advanced equipments of NDMI in order to detect and monitor national disasters occurred by global abnormal climate change around the Korean Peninsula: satellite-based disaster monitoring technologies which can detect and monitor disaster in early stage and advanced investigation equipments which can collect high-quality geo-information data at disaster site.

• Korean Journal of Remote Sensing
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• v.31 no.2
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• pp.137-148
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• 2015

The National Institute of Meteorological Research (NIMR) has operated the Fourier Transform InfraRed (FTIR) spectrometer which is the Atmospheric Emitted Radiance Interferometer (AERI) in Anmyeon island, Korea since June 2010. The ground-based AERI with similar hyper-spectral infrared sensor to satellite could be an alternative way to validate satellite-based remote sensing. In this regard, the NIMR has focused on the improvement of retrieval quality from the AERI, particularly cloud-data filtering method. The AERI spectrum which is measured on a typical clear day is selected reference spectrum and we used region of atmospheric window. We performed test of threshold in order to select valid threshold. We retrieved methane using new method which is used reference spectrum, and the other method which is used KLAPS cloud cover information, each retrieved methane was compared with that of ground-based in-situ measurements. The quality of AERI methane retrievals of new method was significantly more improved than method of used KLAPS. In addition, the comparison of vertical total column of methane from AERI and GOSAT shows good result.

• Korean Journal of Remote Sensing
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• v.31 no.5
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• pp.409-419
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• 2015

The Atmospheric Emitted Radiance Interferometer (AERI) which is the Fourier Transform InfraRed (FTIR) spectrometer has been operated by the National Institute of Meteorological Research (NIMR) in Anmyeon island, South Korea since June 2010. The ground-based AERI with similar hyper-spectral infrared sensor to satellite could be an alternative way to validate satellite-based remote sensing. In this regard, the NIMR has focused on the improvement of Cloud data Filtering Method (CFM) which employed only one reference spectrum of clear sky in winter season. This study suggests Seasonal-Cloud data Filtering Method (S-CFM) which applied seasonal AERI reference spectra. For the comparison of applied S-CFM and CFM, the methane retrievals (surface volume mixing ratio) from AERI spectra are used. The quality of AERI methane retrieval applied S-CFM was significantly more improved than that of CFM. The positive result of S-CFM is similar pattern with the seasonal variation of methane from ground-based in-situ measurement, even if the summer season's methane is retrieved over-estimation. In addition, the comparison of vertical total column of methane from AERI and GOSAT shows good result except for the summer season.

• Korean Journal of Remote Sensing
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• v.20 no.2
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• pp.139-152
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• 2004

This paper proposes to improve the results of image classification with spatial region growing segmentation by using an MRF-based classifier. The proposed approach is to re-classify the pixels in the boundary area, which have high probability of having classification error. The MRF-based classifier performs iteratively classification using the class parameters estimated from the region growing segmentation scheme. The proposed method has been evaluated using simulated data, and the experiment shows that it improve the classification results. But, conventional MRF-based techniques may yield incorrect results of classification for remotely-sensed images acquired over the ground area where has complicated types of land-use. A multistage MRF-based iterative class-modification in boundary is proposed to alleviate difficulty in classifying intricate land-cover. It has applied to remotely-sensed images collected on the Korean peninsula. The results show that the multistage scheme can produce a spatially smooth class-map with a more distinctive configuration of the classes and also preserve detailed features in the map.

• Korean Journal of Remote Sensing
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• v.27 no.5
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• pp.587-599
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• 2011

As one measure of image interpretability, NIIRS(National Imagery Interpretability Rating Scale) has been used. Unlike MTF(Modulation Transfer Function), SNR(Signal to Noise Ratio), and GSD(Ground Sampling Distance), NIIRS can describe the quality of overall image at user's perspective. NIIRS is observed with human observation directly or estimated by edge analysis. For edge analysis specially manufactured artificial target is used commonly. This target, formed with a tarp of black and white patterns, is deployed on the ground and imaged by the satellite. Due to this, the artificial target-based method needs a big expense and can not be performed often. In this paper, we propose a new edge analysis method that enables to estimate NIIRS accurately. In this method, natural targets available in the image are used and characteristics of the target are considered. For assessment of the algorithm, various experiments were carried out. The results showed that our algorithm can be used as an alternative to the artificial target-based method.

• Korean Journal of Remote Sensing
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• v.31 no.6
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• pp.583-598
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• 2015

This paper presents derivation of background temperature from geostationary satellite and its validation based on ground measurements and Geographic Information System (GIS) for future use in weather and surface heat variability. This study only focuses on daily and monthly brightness temperature in 2012. From the analysis of COMS Meteorological Data Processing System (CMDPS) data, we have found an error in cloud distribution of model, which used as a background temperature field, and in examining the spatial homogeneity. Excessive cloudy pixels were reconstructed by statistical reanalysis based on consistency of temperature measurement. The derived Brightness temperature has correlation of 0.95, bias of 0.66 K and RMSE of 4.88 K with ground station measurements. The relation between brightness temperature and both elevation and vegetated land cover were highly anti-correlated during warm season and daytime, but marginally correlated during cold season and nighttime. This result suggests that time varying emissivity data is required to derive land surface temperature.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.1-8
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• 2024

Busan is the 6th largest port city in the world, where nitrogen dioxide (NO₂) emissions from transportation and port industries are significant. This study aims to assess the NO₂ products of the Geostationary Environment Monitoring Spectrometer (GEMS) over Busan using ground-based instruments (i.e., surface in-situ network and Pandora). The GEMS vertical column densities of NO₂ showed reasonable consistency in the spatiotemporal variations, comparable to the previous studies. The GEMS data showed a consistent seasonal trend of NO₂ with the Korea Ministry of Environment network and Pandora in 2022, which is higher in winter and lower in summer. These agreements prove the capability of the GEMS data to monitor the air quality in Busan. The correlation coefficient and the mean bias error between the GEMS and Pandora NO₂ over Busan in 2022 were 0.53 and 0.023 DU, respectively. The GEMS NO₂ data were also positively correlated with the ground-based in-situ network with a correlation coefficient of 0.42. However, due to the significant spatiotemporal variabilities of the NO₂, the GEMS footprint size can hardly resolve small-scale variabilities such as the emissions from the road and point sources. In addition, relative biases of the GEMS NO₂ retrievals to the Pandora data showed seasonal variabilities, which is attributable to the air mass factor estimation of the GEMS. Further studies with more measurement locations for longer periods of data can better contribute to assessing the GEMS NO₂ data. Reliable GEMS data can further help us understand the Asian air quality with the diurnal variabilities.

• Atmosphere
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• v.14 no.1
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• pp.24-43
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• 2004

This paper describes the detailed characteristics of heavy rainfall events occurred in Chungcheong province on 15 and 16 April and from 6 to 8 August 2002 based on the analysis of raingauge rainfall rate and radar reflectivity from the METRI's X-band Weather Radar located in Cheongju. A synoptic analysis of the case is carried out, first, and then the analysis is devoted to seeing how the radar observes the case and how much information we obtain. The highly resolved radar reflectivity of horizontal and vertical resolutions of 1 km and 500 m, respectively shows a three-dimensional structure of the precipitating system, in a similar sequence with the ground rainfall rate. The radar echo classification algorithm for convective/stratiform cloud is applied. In the convectively-classified area, the radar reflectivity pattern shows a fair agreement with that of the surface rainfall rate. This kind of classification using radar reflectivity is considered to be useful for the precipitation forecasting. Another noteworthy aspect of the case includes the effect of topography on the precipitating system, following the analysis of the surface rainfall rate, topography, and precipitating system. The results from this case study offer a unique opportunity of the usefulness of weather radar for better understanding of structural and variable characteristics of flash flood-producing heavy rainfall events, in particular for their improved forecasting.