• Korean Journal of Remote Sensing
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• v.20 no.6
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• pp.419-425
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• 2004

This study has proposed a data fusion method based on the Dempster-Shafer evidence theory The Dempster-Shafer fusion uses mass functions obtained under the assumption of class-independent Gaussian assumption. In the Dempster-Shafer approach, uncertainty is represented by 'belief interval' equal to the difference between the values of 'belief' function and 'plausibility' function which measure imprecision and uncertainty By utilizing the Dempster-Shafer scheme to fuse the data from multiple sensors, the results of classification can be improved. It can make the users consider the regions with mixed classes in a training process. In most practices, it is hard to find the regions with a pure class. In this study, the proposed method has applied to the KOMPSAT-EOC panchromatic image and LANDSAT ETM+ NDVI data acquired over Yongin/Nuengpyung. area of Kyunggi-do. The results show that it has potential of effective data fusion for multiple sensor imagery.

• Korean Journal of Remote Sensing
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• v.21 no.2
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• pp.145-162
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• 2005

To improve the accuracy of land-cover discrimination in SAB data classification, this paper presents a methodology that includes feature extraction and fusion steps with multi-temporal SAR data. Three features including average backscattering coefficient, temporal variability and coherence are extracted from multi-temporal SAR data by considering the temporal behaviors of backscattering characteristics of SAR sensors. Dempster-Shafer theory of evidence(D-S theory) and fuzzy logic are applied to effectively integrate those features. Especially, a feature-driven heuristic approach to mass function assignment in D-S theory is applied and various fuzzy combination operators are tested in fuzzy logic fusion. As experimental results on a multi-temporal Radarsat-1 data set, the features considered in this paper could provide complementary information and thus effectively discriminated water, paddy and urban areas. However, it was difficult to discriminate forest and dry fields. From an information fusion methodological point of view, the D-S theory and fuzzy combination operators except the fuzzy Max and Algebraic Sum operators showed similar land-cover accuracy statistics.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1491-1495
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• 2023

This study utilized automated machine learning (AutoML) to calculate Arctic ice surface temperature (IST). AutoML-derived IST exhibited a strong correlation coefficient (R) of 0.97 and a root mean squared error (RMSE) of 2.51K. Comparative analysis with deep neural network (DNN) models revealed that AutoML IST demonstrated good accuracy, particularly when compared to Moderate Resolution Imaging Spectroradiometer (MODIS) IST and ice mass balance (IMB) buoy IST. These findings underscore the effectiveness of AutoML in enhancing IST estimation accuracy under challenging polar conditions.

• Journal of Korean Society of Forest Science
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• v.83 no.1
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• pp.75-87
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• 1994

The states of development of remote sensing, GIS and forest management technology are such that new directions in forest surveys and management are possible. The technologies can not be considered separately. With the increasing power and decreasing cost of computer processing and the development of inexpensive mass storage media, digital remote sensing applications are becoming more practical. Powerful microcomputer-based image analysis systems and GIS are important advancements. As well, it is only a matter of time before the integration of remote sensing image analysis systems and GIS becomes transparent to the users. Implementation of operational applications by both centralized agencies and local units is, therefore, becoming practical. This paper discussed the state of remote sensing technology and its application to forest surveys and management. The relative advantages and disadvantages of readily available remote sensing products for regional biodiversity assessment were summarized. Discussion is limited to the sources of up-to-date imagery suitable for regional land use/cover mapping, specifically : LANDSAT MSS and TM, and SPOT.

• Proceedings of the Korean Vacuum Society Conference
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• 2014.02a
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• pp.413-413
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• 2014

In this paper, we present a fabrication method of functionalized gold nanostructures on flexible substrate that can be implemented for plasmonic sensing application. For biomolecular sensing, many researchers exploit unconventional lithography method like nanoimprint lithography (NIP), contact transfer lithography, soft lithography, colloidal transfer printing due to its usability and easy to functionalization. In particular, nanoimprint and contact transfer lithography need to have anti-adhesion layer for distinctive metallic properties on the flexible substrates. However, when metallic thin film was deposited on the anti-adhesion layer coated substrates, we discover much aggravation of the mold by repetitive use. Thus it would be impossible to get a high quality of metal nanostructure on the transferred substrate for developing flexible electronics based transfer printing. Here we demonstrate a method for nano-pillar mold and transfer the controllable nanoparticle array on the flexible substrates without an anti-adhesion layer. Also functionalization of gold was investigated by the different length of thiol applied for effectively localized surface plasmonic resonance sensing. First, a focused ion beam (FIB) and ICP-RIE are used to fabricate the nanoscale pillar array. Then gold metal layer is deposited onto the patterned nanostructure. The metallic 130 nm and 250 nm nanodisk pattern are transferred onto flexible polymer substrate by bi-layer functionalized contact imprinting which can be tunable surface energy interfaces. Different thiol reagents such as Thioglycolic acid (98%), 3-Mercaptopropionic acid (99%), 11-Mercaptoundecanoic acid (95%) and 16-Mercaptohexadecanoic acid (90%) are used. Overcoming the repeatedly usage of the anti-adhesion layer mold which has less uniformity and not washable interface, contact printing method using bi-layer gold array are not only expedient access to fabrication but also have distinctive properties including anti-adhesion layer free, functionalized bottom of the gold nano disk, repeatedly replicate the pattern on the flexible substrate. As a result we demonstrate the feasibility of flexible plasmonic sensing interface and anticipate that the method can be extended to variable application including the portable bio sensor via mass production of stable nanostructure array and other nanophotonic application.

• Korean Journal of Remote Sensing
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• v.28 no.4
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• pp.449-458
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• 2012

Using the MODerate resolution Imaging Spectro-radiometer (MODIS) retrieved aerosol optical thickness (AOT) along with ground measurements of PM2.5 mass concentration, we assessed local air quality over Dukjuk and Jeju island and estimated possibility of satellite derived PM2.5 during nine intensive observation periods in 15 October 2005 - 24 October 2007. Averaged PM2.5 mass concentrations showed relatively variable as $25.61{\pm}22.92{\mu}g/m^3$ at Dukjuk and $17.33{\pm}10.79{\mu}g/m^3$ at Jeju. The maximum values of $188.89{\mu}g/m^3$ (Dukjuk) and $50.46{\mu}g/m^3$ (Jeju) were recorded during Asian dust storm day. Similarly, the maximum values of MODIS AOT were found as 3.73 (Gosan) and 1.14 (Jeju). Averaged MODIS AOTs at Dukjuk ($0.79{\pm}0.81$) were larger than that at Jeju ($0.42{\pm}0.24$). An empirical relationship between MODIS AOT and PM2.5 mass was obtained and results show that there was a good correlation between satellite and ground based values with a linear correlation coefficient of 0.85 at Dukjuk. The result clearly demonstrates that satellite derived AOT is a good surrogate for monitoring PM air quality over study area. However, meteorological and other ancillary datasets are necessary to further apply satellite data for air quality research.

• Korean Journal of Remote Sensing
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• v.30 no.6
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• pp.743-754
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• 2014

In this present paper, we, for the first time, calculated $SO_2$ inflow from China to Korea peninsula based on OMI $SO_2$ products and HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory Model) backward trajectory calculations. The major factors used to estimate $SO_2$ flux are long range transported $SO_2$ concentration, transport speed of air mass, and thickness of transported air mass layer. The mean and maximum $SO_2$ fluxes are estimated to be 0.81 and $2.11g{\cdot}m^{-2}{\cdot}h^{-1}$, respectively based on OMI products while, those of $SO_2$ fluxes are 0.50 and $1.18g{\cdot}m^{-2}{\cdot}h^{-1}$ respectively using insitu data obtained at the surface. For most cases, larger $SO_2$ inflow values were found at the surface than those estimated for the air mass layer which extends from surface up to 1.5 km. However, increased transport speed of air mass leads to the enhanced $SO_2$ flux at the altitude up to 1.5 km at the receptor sites. Additionally, we calculate uncertainties of $SO_2$ flux using error propagation method.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1235-1243
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• 2023

This study proposes the detection algorithm for the cold water mass (CWM) along the eastern coast of the Korean Peninsula using sea surface temperature (SST) data provided by the Korea Institute of Ocean Science and Technology (KIOST). Considering the occurrence and distribution of the CWM, the eastern coast of the Korean Peninsula is classified into 3 regions("Goseong-Uljin", "Samcheok-Guryongpo", "Pohang-Gijang"), and the K-means clustering is first applied to SST field of each region. Three groups, K-means clusters are used to determine CWM through applying a double threshold filter predetermined using the standard deviation and the difference of average SST for the 3 groups. The estimated sea area is judged by the CWM if the standard deviation in the sea area is 0.6℃ or higher and the average water temperature difference is 2℃ or higher. As a result of the CWM detection in 2022, the number of CWM occurrences in "Pohang-Gijang" was the most frequent on 77 days and performance indicators of the confusion matrix were calculated for quantitative evaluation. The accuracy of the three regions was 0.83 or higher, and the F1 score recorded a maximum of 0.95 in "Pohang-Gijang". The detection algorithm proposed in this study has been applied to the KIOST SST system providing a CWM map by email.

• Korean Journal of Remote Sensing
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• v.33 no.5_3
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• pp.855-866
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• 2017

Several research cases using remote sensing methods to analyze changes of storage and dynamics of groundwater aquifer were reviewed in this paper. The status of groundwater storage, in an area with regional scale, could be qualitatively inferred from geological feature, surface water altimetry and topography, distribution of vegetation, and difference between precipitation and evapotranspiration. These qualitative indicators could be measured by geological lineament analysis, airborne magnetic survey, DEM analysis, LAI and NDVI calculation, and surface energy balance modeling. It is certain that GRACE and InSAR have received remarkable attentions as direct utilization from satellite data for quantification of groundwater storage and dynamics. GRACE, composed of twin satellites having acceleration sensors, could detect global or regional microgravity changes and transform them into mass changes of water on surface and inside of the Earth. Numerous studies in terms of groundwater storage using GRACE sensor data were performed with several merits such that (1) there is no requirement of sensor data, (2) auxiliary data for quantification of groundwater can be entirely obtained from another satellite sensors, and (3) algorithms for processing measured data have continuously progressed from designated data management center. The limitations of GRACE for groundwater storage measurement could be defined as follows: (1) In an area with small scale, mass change quantification of groundwater might be inaccurate due to detection limit of the acceleration sensor, and (2) the results would be overestimated in case of combination between sensor and field survey data. InSAR can quantify the dynamic characteristics of aquifer by measuring vertical micro displacement, using linear proportional relation between groundwater head and vertical surface movement. However, InSAR data might now constrain their application to arid or semi-arid area whose land cover appear to be simple, and are hard to apply to the area with the anticipation of loss of coherence with surface. Development of GRACE and InSAR sensor data preprocessing algorithms optimized to topography, geology, and natural conditions of Korea should be prioritized to regionally quantify the mass change and dynamics of the groundwater resources of Korea.

• Korean Journal of Remote Sensing
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• v.32 no.2
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• pp.119-131
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• 2016

Descriptions are provided of the automated aerosol-type classification and mass concentration calculation algorithm for real-time data processing and aerosol products in Korea Aerosol Lidar Observation Network (KALION, http://www.kalion.kr). The KALION algorithm provides aerosol-cloud classification and three aerosol types (clean continental, dust, and polluted continental/urban pollution aerosols). It also generates vertically resolved distributions of aerosol extinction coefficient and mass concentration. An extinction-to-backscatter ratio (lidar ratio) of 63.31 sr and aerosol mass extinction efficiency of $3.36m^2g^{-1}$ ($1.39m^2g^{-1}$ for dust), determined from co-located sky radiometer and $PM_{10}$ mass concentration measurements in Seoul from June 2006 to December 2015, are deployed in the algorithm. To assess the robustness of the algorithm, we investigate the pollution and dust events in Seoul on 28-30 March, 2015. The aerosol-type identification, especially for dust particles, is agreed with the official Asian dust report by Korean Meteorological Administration. The lidar-derived mass concentrations also well match with $PM_{10}$ mass concentrations. Mean bias difference between $PM_{10}$ and lidar-derived mass concentrations estimated from June 2006 to December 2015 in Seoul is about $3{\mu}g\;m^{-3}$. Lidar ratio and aerosol mass extinction efficiency for each aerosol types will be developed and implemented into the KALION algorithm. More products, such as ice and water-droplet cloud discrimination, cloud base height, and boundary layer height will be produced by the KALION algorithm.