• Korean Journal of Remote Sensing
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• v.26 no.5
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• pp.489-495
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• 2010

Hyperspectral imaging obtains information with a wider wavelength range a large number of bands. However, a high correlation between each band, computation cost, and noise causes inaccurate results in cases of no pre-processing. The noises of band extraction and elimination positively necessary in hyperspectral imaging. Since the previous studies have used a characteristic the whole image, a local characteristic of the image is considered for the noise band extraction. In this study, the Quadtree, which is a data structure algorithm. and the fractal dimension are adopted for noise band extraction in Hyperion images. The fractal dimensions of the segments divided by the Quadtree structure are calculated, and variation is used. We focused on the extraction of random noise bands in Hyperion images and compared them with the reference data made by visual decisions. The proposed algorithm extracts the most bands, including random noises. It is possible to eliminate more than 30 noise bands, regardless of images.

• Korean Journal of Remote Sensing
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• v.19 no.6
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• pp.421-430
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• 2003

The extraction technique for Doppler information(Doppler centroid frequency(f$_{dc}$) and it's rate(f$_{r}$) is very important to make an image from the radar echo signal data. Clutterlock and auto-focusing techniques have been widely used to extract accurate Doppler information. But both techniques are not easy to implement in SAR processor and need quite lots of time to calculate accurate f$_{dc}$ and f$_{r}$ because they are generally based on echo signal data only. In this paper we suggest hybrid method for Doppler extraction using both of echo signal data and orbital and attitude information of satellite. In this method CDE(Correlation Doppler Estimation) technique is only used to estimate exact modular f$_{dc}$ using received echo signal data and rest of other algorithms are based on simple mathematical model of geometry between satellite and ground targets as well as the Doppler frequency ambiguity resolving problem. The experimental results using Radarsat-1 signal data shows that the proposed method can be effectively used for the extraction of Doppler information.

• Korean Journal of Remote Sensing
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• v.25 no.4
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• pp.375-381
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• 2009

In this paper, synthetic aperture radar (SAR) clutter images are simulated based on the extensive analyses for radar backscatter characteristics of various earth surfaces, and the simulated images are compared with measured SAR images. At first, the surface parameters including soil moisture content and surface roughness parameters and other parameters for vegetation canopies are measured for various surfaces. The backscattering coefficients for the surfaces are computed using theoretical and empirical models for surface scattering and the radiative transfer for vegetation-canopy scattering. Then, the digital elevation map (DEM) and land cover map (LCM) are used for the SAR image generation. The SAR impulse response (correlation function) is also employed to simulated reliable SAR images. Finally, the appropriate speckle and texture parameters for various earth surfaces are used for generating the SAR clutter images.

• Korean Journal of Remote Sensing
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• v.36 no.3
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• pp.411-423
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• 2020

Localized solar irradiance is normally derived from atmospheric transmission influenced by atmospheric composition and conditions of the target area. Specially, for the area with complex coastal lines such as Taean gun, the accurate estimation of solar irradiance requires for in depth analysis of atmospheric transmission characteristics based on the localized vertical profiles of the key atmospheric parameters. Using MODTRAN (MODerate resolution atmospheric TRANsmission) 6, we report a computational study on clear day atmospheric transmission and direct solar irradiance estimation of Taean gun using the data collected from 3 ground stations and radiosonde measurement over 93 clear days in 2018. The MODTRAN estimated direct solar irradiance is compared with the measurement. The results show that the normalized residual mean (NRM) is 0.28 for the temperature based MODTRAN atmospheric model and 0.32 for the pressure based MODTRAN atmospheric model. These values are larger than 0.1~0.2 of the other study and we understand that such difference represents the local atmospheric characteristics of Taean gun. The results also show that NRM tends to increase noticeably in summer as the temperature increases. Such findings from this study can be very useful for estimation and prediction of the atmospheric condition of the local area with complex coastal lines.

• Korean Journal of Remote Sensing
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• v.27 no.5
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• pp.543-553
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• 2011

Sea ice concentration calculated from the AMSR-E onboard Aqua satellite by using NASA Team2 sea ice algorithm has proven to be very accurate over sea ice in Antarctic Ocean. When glacial ice such as icebergs and ice shelves are dominant in an AMSR-E footprint, the accuracy of the ice concentration calculated from NASA Team2 algorithm is not well maintained due to the different microwave characteristics of the glacial ice from sea ice. We extracted the concentrations of sea ice and glacial ice from two ENVISAT ASAR images of George V coast in southern Antarctica, and compared them with NASA Team2 sea ice concentration. The result showed that the NASA Team2 algorithm underestimates the concentration of glacial ice. To interpret the large deviation of estimation over glacial ice, we analyzed the characteristics of microwave radiation of the glacial ice in PR(polarization ratio), GR(spectral gradient ratio), $PR_R$(rotated PR), and ${\Delta}GR$ domain. We found that glacial ice occupies a unique region in the PR, GR, $PR_R$, and ${\Delta}GR$ domain different from other types of ice such as ice type A, B, and C, and open water. This implies that glacial ice can be added as a new category of ice to the AMSR-E NASA Team2 sea ice algorithm.

• Korean Journal of Remote Sensing
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• v.27 no.4
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• pp.445-455
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• 2011

A probabilistic classification framework is presented that can combine temporal contextual information derived from an existing land-cover map in order to improve the classification accuracy of land-cover classes that can not be discriminated well when using spectral information only. The transition probability is computed by using the existing land-cover map and training data, and considered as a priori probability. By combining the a priori probability with conditional probability computed from spectral information via a Bayesian combination rule, the a posteriori probability is finally computed and then the final land-cover types are determined. The method presented in this paper can be adopted to any probabilistic classification algorithms in a simple way, compared with conventional classification methods that require heavy computational loads to incorporate the temporal contextual information. A case study for crop classification using time-series MODIS data sets is carried out to illustrate the applicability of the presented method. The classification accuracies of the land-cover classes, which showed lower classification accuracies when using only spectral information due to the low resolution MODIS data, were much improved by combining the temporal contextual information. It is expected that the presented probabilistic method would be useful both for updating the existing past land-cover maps, and for improving the classification accuracy.

• Korean Journal of Remote Sensing
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• v.24 no.6
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• pp.535-549
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• 2008

Vicarious calibration for the satellite sensor relies on simulated TOA (Top-of-Atmosphere) radiances over various targets. In this study, TOA visible radiance was calculated over ocean targets which are located in five different regions over the Indian and Pacific ocean, and its possible use for the satellite sensor calibration was examined. TOA radiances are simulated with the 6S radiative transfer model for the comparison with MODIS/Terra and SeaWiFS measurements. Geometric angles and sensor characteristics of the reference satellites were taken into account for the simulation. AOT (Aerosol Optical Thickness) from MODIS/Terra, pigment concentrations from Sea WiFS, and ozone amount from OMI measurements were used as inputs to the model. Other atmospheric input parameters such as surface wind and total column water vapor were taken from NCEP/NCAR reanalysis data. The 5-day averaged radiances over all targets show that the percent differences between simulated and observed radiances are within about ${\pm}5%$ in year 2005, indicating that the calculated radiances are in good agreement with satellite measurements. It has also been shown that the algorithm can produce the SeaWiFS radiances within about ${\pm}5%$ uncertainty range. It has been suggested that the algorithm can be used as a tool for calibrating the VIS bands within about 5% uncertainty range.

• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1425-1434
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• 2021

Continuous and periodic data acquisition must be preceded to maintain and manage the river facilities effectively. Adapting the existing general facilities methods, which include river surveying methods such as terrestrial laser scanners, total stations, and Global Navigation Satellite System (GNSS), has limitation in terms of its costs, manpower, and times to acquire spatial information since the river facilities are distributed across the wide and long area. On the other hand, the Mobile Mapping System (MMS) has comparative advantage in acquiring the data of river facilities since it constructs three-dimensional spatial information while moving. By using the MMS, 184,646,009 points could be attained for Anyang stream with a length of 4 kilometers only in 20 minutes. Levee points were divided at intervals of 10 meters so that about 378 levee cross sections were generated. In addition, the waterside maximum and average slope could be automatically calculated by separating slope plane form levee point cloud, and the accuracy of RMSE was confirmed by comparing with manually calculated slope. The reference slope was calculated manually by plotting point cloud of levee slope plane and selecting two points that use location information when calculating the slope. Also, as a result of comparing the water side slope with slope standard in basic river plan for Anyang stream, it is confirmed that inspecting the river facilities with the MMS point cloud is highly recommended than the existing river survey.

• Korean Journal of Remote Sensing
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• v.38 no.6_4
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• pp.1879-1887
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• 2022

In this study, a method of estimating the velocity and altitude of aircrafts photographed in a KOMPSAT-3 satellite was proposed. In the proposed method, parallax effect, which is a time offset between bands due to the photographing method of the KOMPSAT-3 satellite, the structure of the sensor, and the movement of the satellite's orbit, was calculated, and in this process, trucks running on the highway were used. In addition, the actual direction and the direction by parallax effect of the aircraft were calculated using the coordinates of the aircraft in the image, and the attitude information of the KOMPSAT-3 satellite was calculated using metadata to estimate the velocity and altitude of the aircraft. The estimated value through the proposed method was compared with the actual value, automatic dependent surveillance-broadcast (ADS-B), and the error rate was calculated here. As a result, it was confirmed that the velocity and altitude error rate of large aircraft (I1, I3, S2) were lower than that of light aircraft (I2, S2), and the estimated velocity and altitude were relatively high in large aircraft using the proposed method.

• Journal of The Geomorphological Association of Korea
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• v.19 no.3
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• pp.37-49
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• 2012

The objective of this paper is to propose a methodology for surface sediments classification in tidal flats that can combine ground survey data with high-resolution remote sensing data by multivariate kriging. Unlike conventional methodologies that have classified remote sensing data by using pre-classified sediment components, a new classification methodology presented in this paper first generates sediment component fraction maps and then classifies the sediments on a final stage. For generating sediment component fractions, regression kriging, as one of multivariate kriging algorithms, is applied to integrate ground survey data and remote sensing data. First, trend components of sand, silt, and clay are derived through regression analysis of ground survey data and spectral information from remote sensing data. Then, residuals at sample locations are computed and interpolated to generate residual components in the study area. Finally, the sediment component fractions are computed by adding the residuals to the trend components and are classified on a final stage. A case study at the Baramarae tidal flats with KOMPSAT-2 imagery is carried out to evaluate the classification capability of the proposed classification methodology. Through the case study, the proposed methodology showed the best classification accuracy, compared with the conventional classification methodologies. Especially, much improvement of classification accuracy for fine-grained sediments were also obtained. Therefore, it is expected that the presented classification methodology would be an effective one for surface sediments classification in tidal flats.