• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5B
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• pp.487-495
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• 2010

Soil moisture is a crucial factor in hydrological system which influences runoff, energy balance, evaporation, and atmosphere. United States National Aeronautic and Space Administration (NASA) and Department of Agriculture (USDA) have established Soil Moisture Experiment (SMEX) since 2002 for the global observations. SMEX provides useful data for the hydrological science including soil moisture and hydrometeorological variables. The purpose of this study is to investigate the relationship between remotely sensed soil moisture data from aircraft and satellite and ground based experiment. C-band of Polarimetric Scanning Radiometer (PSR) that observed the brightness temperature provides soil moisture data using a retrieval algorithm. It was compared with the In-situ data for 2-30 cm depth at four sites. The most significant depth is 2-10 cm from the correlation analysis. Most of the sites, two data are similar to the mean of data at 10 cm and the median at 7 cm and 10 cm at the 10% significant level using the Rank Sum test and t-test. In general, soil moisture data using the C-band of the PSR was established to fit the Normal, Log-normal and Gumbel distribution. Soil moisture data using the aircraft and satellites will be used in hydrological science as fundamental data. Especially, the C-band of PSR will be used to prove soil moisture at 7-10 cm depths.

• Journal of KIISE
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• v.42 no.4
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• pp.459-467
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• 2015

The analysis platform of remote-sensing big data is a system that downloads data from satellites, transforms it to a data type of L3, and then analyzes it and produces its analysis results. The objective of this paper is to develop ISO/IEC 9126-1 software quality model-based assessment criteria, in order to evaluate the quality of remote-sensing big data analysis platform. Its detailed research contents are as follows. First, the ISO/IEC 9216 standards and previous software evaluation models will be reviewed. Second, this paper will define evaluation areas, evaluation elements, and evaluation items for measuring the quality of big data analysis platform. Third, the validity of the assessment criteria will be verified by statistical experiments through content validity, reliability validity, and construct validity, by using SPSS 20.0 and Amos 20.0 software. The construct validity will also be conducted by performing the confirmatory factor analysis and path analysis. Lastly, it is significant that our research result demonstrates the first evaluation criteria in measuring the quality of big data analysis platform. It is also expected that our assessment criteria could be used as the basis information for evaluation criteria in the platforms that will be developed in the future.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1507-1515
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• 2021

If chlorophyll-a is estimated through ocean color remote sensing, it is able to understand the global distribution of phytoplankton and primary production. However, there are missing data in the ocean color observed from the satellites due to the clouds or weather conditions. In thisstudy, the missing data of the GOCI (Geostationary Ocean Color Imager) chlorophyll-a product wasreconstructed by using DINEOF (Data INterpolation Empirical Orthogonal Functions). DINEOF reconstructs the missing data based on spatio-temporal data, and the accuracy was cross-verified by removing a part of the GOCI chlorophyll-a image and comparing it with the reconstructed image. In the study area, the optimal EOF (Empirical Orthogonal Functions) mode for DINEOF wasin 10-13. The temporal and spatialreconstructed data reflected the increasing chlorophyll-a concentration in the afternoon, and the noise of outliers was filtered. Therefore, it is expected that DINEOF is useful to reconstruct the missing images, also it is considered that it is able to use as basic data for monitoring the ocean environment.

• Journal of the Korean earth science society
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• v.41 no.6
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• pp.599-616
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• 2020

Sea-surface temperature (SST) is one of the most important oceanic variables for understanding air-sea interactions, heat flux variations, and oceanic circulation in the global ocean. Extremely low SSTs from 0℃ down to -2℃ should be more important than other normal temperatures because of their notable roles in inducing and regulating global climate and environmental changes. To understand the temporal and spatial variability of such extremely low SSTs in the global ocean, the long-term SST climatology was calculated using the daily SST database of satellites observed for the period from 1982 to 2018. In addition, the locations of regions with extremely low surface temperatures of less than 0℃ and monthly variations of isothermal lines of 0℃ were investigated using World Ocean Atlas (WOA) climatology based on in-situ oceanic measurements. As a result, extremely low temperatures occupied considerable areas in polar regions such as the Arctic Ocean and Antarctic Ocean, and marginal seas at high latitudes. Six earth science textbooks were analyzed to investigate how these extremely low temperatures were visualized. In most textbooks, illustrations of SSTs began not from extremely low temperatures below 0℃ but from a relatively high temperature of 0℃ or higher, which prevented students from understanding of concepts and roles of the low SSTs. As data visualization is one of the key elements of data literacy, illustrations of the textbooks should be improved to ensure that SST data are adequately visualized in the textbooks. This study emphasized that oceanic literacy and data literacy could be cultivated and strengthened simultaneously through visualizations of oceanic big data by using satellite SST data and oceanic in-situ measurements.

• Korean Journal of Remote Sensing
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• v.36 no.2_1
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• pp.167-178
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• 2020

KOMPSAT-3A images have been used in various kinds of applications, since its launch in 2015. However, there were limits to scientific analysis and application extensions of these data, such as vegetation index estimation, because no tool was developed to obtain the surface reflectance required for analysis of the actual land environment. The surface reflectance is a product of performing an absolute atmospheric correction or calibration. The objective of this study is to quantitatively verify the accuracy of top-of-atmosphere reflectance and surface reflectance of KOMPSAT-3A images produced from the OTB open-source extension program, performing the cross-validation with those provided by a site measurement data of RadCalNet, an international Calibration/Validation (Cal/Val) portal. Besides, surface reflectance was obtained from Landsat-8 OLI images in the same site and applied together to the cross-validation process. According to the experiment, it is proven that the top-of-atmosphere reflectance of KOMPSAT-3A images differs by up to ± 0.02 in the range of 0.00 to 1.00 compared to the mean value of the RadCalNet data corresponding to the same spectral band. Surface reflectance in KOMPSAT-3A images also showed a high degree of consistency with RadCalNet data representing the difference of 0.02 to 0.04. These results are expected to be applicable to generate the value-added products of KOMPSAT-3A images as analysisready data (ARD). The tools applied in thisstudy and the research scheme can be extended as the new implementation of each sensor model to new types of multispectral images of compact advanced satellites (CAS) for land, agriculture, and forestry and the verification method, respectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.1-6
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• 2020

UAV (Unmanned Aerial Vehicles) are used widely for military purposes because they are more economical than general manned aircraft and satellites, and have easy access to the object. Recently, owing to the development of IT technology, UAV equipped with various sensors have been released, and their use is increasing in a wide range of fields, such as surveying, agriculture, meteorological observation, communication, broadcasting, and sports. An increasing number of studies and attempts have made use of it. On the other hand, existing research was related mostly to photogrammetry, but there has been a lack of analytical research on LiDAR (Light Detection And Ranging). Therefore, this study examined the characteristics of a UAV LiDAR sensor for the application of a geospatial information field. In this study, the performance of commercialized LiDAR sensors, such as the acquisition speed and the number of echoes, was investigated, and data acquisition and analysis were conducted by selecting Surveyor Ultra and VX15 models with similar accuracy and data acquisition distances. As a result, a DSM of each study site was generated for each sensor, and the characteristics of data density, precision, and acquisition of ground data from vegetation areas were presented through comparison. In addition, the UAV LiDAR sensor showed an accuracy of 0.03m ~ 0.05m. Hence, it is necessary to select equipment considering the characteristics of data for effective use. In the future, the use of UAV LiDAR may be suggested if additional data can be obtained and analyzed for various areas, such as urban areas and forest areas.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.2
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• pp.150-157
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• 2014

Li-Ion battery is used in the most satellites now due to advantages such as weight, thermal dissipation and self discharge compared to the previous generations of electrochemical batteries. The performance analysis model of the Li-Ion battery is needed to aid the design of new satellite electrical power subsystem. This paper develops the performance analysis model of the Li-Ion battery to apply to the electrical power subsystem design and energy balance analysis on geostationary orbit. The analysis model receives the satellite bus power, solar array power and battery temperature and gives the battery voltage, charge and discharge currents, taper index, state of charge and power dissipation. The results from the performance analysis are compared and analyzed with the flight data to verify the model. The compared results show satisfactory without significant difference with the flight data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.19 no.3
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• pp.263-272
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• 2001

For a high resolution real-time kinematic GPS surveying using carrier phase, positioning accuracy according to the OTF initialization was better than 1 cm with more than 5-minute initialization within 20 km baseline. Also, it is recommended that measurements be carried out when PDOP and RDOP can be kept less than 4.0 since the geometrical layout of satellites has a great influence on the positioning accuracy. After considering the initial conditions and measuring time zone for real-time kinematic GPS. post-processed continuous kinematic GPS and real-time kinematic GPS measurements have been carried out. A new system has been proposed to store measured data by using a program developed to store GPS data in real time and to monitor the satellite condition through controller at the time of measurement. As a result, it has been revealed that possible noise in surveying could be corrected and the accuracy could be improved.

• Korean Journal of Remote Sensing
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• v.29 no.3
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• pp.307-314
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• 2013

The Bidirectional Reflectance Distribution (BRD) effect is critical to interpret the surface information using remotely sensed data. This effect was caused by geometric relationship between sensor, target and solar that is inevitable effect for data of optical sensor. To remove the BRD effect, semi-empirical BRDF models are widely used. It is faster to calculate than physical models and demanded less observation than empirical models. In this study, Ross-Li kernel and Roujean kernel were used respectively in National Aeronautics and Space Administration (NASA) and European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) that are used to compare each other. The semi-empirical model consists of three parts which are isotropic, geometric and volumetric scattering. Each part contained physical kernel and empirical coefficients that were calculated by statistical method. Red and NIR channel of SPOT/VEGETATION product were used to compute Nadir BRDF Adjusted Reflectance (NBAR) over East Asia area from January 2009 to December 2009. S1 product was provided by VITO that was conducted atmospheric correction using Simplified Method of Atmospheric Correction (SMAC). NBAR was calculated using corrected reflectance of red and NIR. Previous study has revealed that Roujean geometric kernel had unphysical values in large zenith angles. We extracted empirical coefficients in three parts and normalized reflectance to compare both BRDF models. Two points located forest in Korea peninsular and bare land in Gobi desert were selected for comparison. As results of time series analysis, both models showed similar reflectance change pattern and reasonable values. Whereas in case of empirical coefficients comparison, different changes pattern of values were showed in isotropic coefficients.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.237-240
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• 2005

Calibration and Validation are major element of any space borne Earth Observation Mission. These activities are the major objective of the commissioning phases but routine activities shall be maintained during the whole mission in order to maintain the quality of the product delivered to the users or at least to fully characterise the evolution with time of the product quality. With the launch of ERS-l in 1991, the European Space Agency decided to put in place a group dedicated to these activities, along with the daily monitoring of the product quality for anomaly detection and algorithm evolution. These four elements are all strongly linked together. Today this group is fully responsible for the monitoring of two ESA missions, ERS-2 and Envisat, for a total of 12 instruments of various types, preparing itself for the Earth Explorer series of five. other satellites (Cryosat, Goce, SMOS, ADM-Aeolus, Swarm) and at various levels in past and future Third Party Missions such as Landsat, J-ERS, ALOS and KOMPSAT. The Joint proposal by the European Union and the European Space Agency for a 'Global Monitoring for Environment and Security' project (GMES), triggers a review of the scope of these activities in a much wider framework than the handling of single missions with specific tools, methods and activities. Because of the global objective of this proposal, it is necessary to put in place Multi-Mission Calibration and Validation systems and procedures. GMES Calibration and Validation activities will rely on multi source data access, interoperability, long-term data preservation, and definition standards to facilitate the above objectives. The scope of this presentation is to give an overview of the current Calibration and Validation activities at ESA, and the planned evolution in the context of GMES.