• Journal of Korea Multimedia Society
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• v.25 no.7
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• pp.895-902
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• 2022

Building segmentation using satellite imagery such as EO (Electro-Optical) and SAR (Synthetic-Aperture Radar) images are widely used due to their various uses. EO images have the advantage of having color information, and they are noise-free. In contrast, SAR images can identify the physical characteristics and geometrical information that the EO image cannot capture. This paper proposes a learning framework for efficient building segmentation that consists of a teacher-student-based privileged knowledge distillation and deformable convolution block. The teacher network utilizes EO and SAR images simultaneously to produce richer features and provide them to the student network, while the student network only uses EO images. To do this, we present objective functions that consist of Kullback-Leibler divergence loss and knowledge distillation loss. Furthermore, we introduce deformable convolution to avoid pixel-level noise and efficiently capture hard samples such as small and thin buildings at the global level. Experimental result shows that our method outperforms other methods and efficiently captures complex samples such as a small or narrow building. Moreover, Since our method can be applied to various methods.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.4
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• pp.363-369
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• 2021

Since the Global Navigation Satellite System (GNSS) signal received from the low Earth orbit (LEO) satellite is only affected by the upper ionosphere, the magnitude of the ionospheric delay of Global Positioning System (GPS) signal received from ground user is different. Therefore, the ground-based two-dimensional ionospheric model cannot be applied to LEO satellites. The NeQuick model used in Galileo provides the ionospheric delay according to the user's altitude, so it can be used in the ionospheric model of the LEO satellites. However, the NeQuick model is not suitable for space receivers because of the high computational cost. A simplified NeQuick model with reduced computing time was recently presented. In this study, the computing time of the NeQuick model and the simplified NeQuick model was analyzed based on the GPS Klobuchar model. The NeQuick and simplified NeQuick model were applied to the GNSS data from GRACE-B, Swarm-C, and GOCE satellites to analyze the performance of the ionospheric correction and positioning. The difference in computing time between the NeQuick and simplified NeQuick model was up to 90%, but the difference in ionospheric accuracy was not as large as within 4.5%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.6
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• pp.1116-1132
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• 2010

In this paper, a new forward error correction (FEC) protocol is proposed for point-to-multipoint satellite links. Link-layer error control protocols in point-to-multipoint satellite links impose several problems such as unreliability and receiver-heterogeneity. To resolve the problem of heterogeneous error rates at different receivers, the proposed scheme exploits multiple multicast channels to which each receiver tunes. The more channels a receiver tunes to, the more powerful error correcting capability it achieves. Based on its own channel condition, each receiver tunes to as many channels as it needs, which prevents from receiving unwanted parities. Furthermore, each receiver saves the decoding time, processing overhead, and processing energy. Performance evaluation shows that the proposed scheme guarantees the target PER while saving energy. The proposed technique is highly adaptive to the channel variation with respect to the throughput efficiency, and provides scalable PER and throughput efficiency.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1475-1477
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• 2003

The satellite remote sensing data is good in order to grasp the wide natural environment. The purpose of study is that it examines spectral reflection characteristic and vegetation index by the utilization of the plant energy ( chlorophyll ) for examining the reliability of satellite data and grasps the transition of the natural environment using the result. According to result of analysis, there were NDVI and mutual relationship on chlorophyll, and luminance compensation of NDVI was effective for all area. In vegetation transition, there were no luminance compensation and relation, and there was a decrease of vegetation in area in south and north. The reason was a result by the artificial and natural effect. This analysis is an effective method in order to confirm the change of specific vegetation.

• Korean Journal of Remote Sensing
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• v.33 no.1
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• pp.79-88
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• 2017

The RapidEye satellite sensor has various spectral wavelength bands, and it can capture large areas with high temporal resolution. Therefore, it affords advantages in generating various types of thematic maps, including land cover maps. In this study, we applied a supervised classification scheme to generate high-resolution land cover maps using RapidEye images. To improve the classification accuracy, object-based classification was performed by adding brightness, yellowness, and greenness bands by Tasseled Cap Transformation (TCT) and Normalized Difference Water Index (NDWI) bands. It was experimentally confirmed that the classification results obtained by adding TCT and NDWI bands as input data showed high classification accuracy compared with the land cover map generated using the original RapidEye images.

• Journal of electromagnetic engineering and science
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• v.14 no.3
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• pp.278-283
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• 2014

This paper presents a theoretical approach for a modified turnstile antenna suitable for satellite communication in order to investigate the current distributions of radiators and radiation characteristics with equivalent model analysis. The proposed equivalent model is composed of an ideally horizontal dipole antenna and vertically loaded top-hat radiating elements. The required isoflux pattern with wide beamwidth has been achieved by attaching top-hat elements to the main radiators. In addition to illustrating radiation patterns, electrical performances like current distributions have been analyzed by mathematically manipulating the equations derived from the equivalent horizontal and vertical dipole model.

• The Bulletin of The Korean Astronomical Society
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• v.33 no.2
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• pp.48.1-48.1
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• 2008

• Korean Journal of Remote Sensing
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• v.29 no.6
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• pp.601-610
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• 2013

As a standard water clarity variable, the vertical underwater visibility, called Secchi depth, is estimated with ocean color satellite data. In the present study, Moderate Resolvtion Imaging Spectradiometer (MODIS) data are used to measure the Secchi depth which is a useful indicator of ocean transparency for estimating the water quality and productivity. To estimate the Secchi depth $Z_v$, the empirical regression model is developed based on the satellite optical data and in-situ data. In the previous study, a semi-analytical algorithm for estimating $Z_v$ was developed and validated for Case 1 and 2 waters in both coastal and oceanic waters using extensive sets of satellite and in-situ data. The algorithm uses the vertical diffuse attenuation coefficient, $K_d$($m^{-1}$) and the beam attenuation coefficient, c($m^{-1}$) obtained from satellite ocean color data to estimate $Z_v$. In this study, the semi-analytical algorithm is validated using temporal MODIS data and in-situ data over the Yellow, Southern and East Seas including Case 1 and 2 waters. Using total 156 matching data, MODIS $Z_v$ data showed about 3.6m RMSE value and 1.7m bias value. The $Z_v$ values of the East Sea and Southern Sea showed higher RMSE than the Yellow Sea. Although the semi-analytical algorithm used the fixed coupling constant (= 6.0) transformed from Inherent Optical Properties (IOP) and Apparent Optical Properties (AOP) to Secchi depth, various coupling constants are needed for different sea types and water depth for the optimum estimation of $Z_v$.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.6
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• pp.121-131
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• 2018

Climate change has caused changes in environmental factors that have a direct impact on agriculture such as temperature and precipitation. The meteorological disaster that has the greatest impact on agriculture is drought, and its forecasts are closely related to agricultural production and water supply. In the case of terrestrial data, the accuracy of the spatial map obtained by interpolating the each point data is lowered because it is based on the point observation. Therefore, acquisition of various meteorological data through satellite imagery can complement this terrestrial based drought monitoring. In this study, Evaporative Stress Index (ESI) was used as satellite data for drought determination. The ESI was developed by NASA and USDA, and is calculated through thermal observations of GOES satellites, MODIS, Landsat 5, 7 and 8. We will identify the difference between ESI and other satellite-based drought assessment indices (Vegetation Health Index, VHI, Leaf Area Index, LAI, Enhanced Vegetation Index, EVI), and use it to analyze the drought in South Korea, and examines the applicability of ESI as a new indicator of agricultural drought monitoring.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.1
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• pp.71-79
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• 2014

Most researches have created the impervious surface map by using low-spatial-resolution satellite imagery and are inefficient to generate the object-based impervious map with a broad area. In this study, segment-based impervious surface mapping algorithm is proposed using the RapidEye satellite imagery in order to map impervious area. At first, additional bands are generated by using TOA reflectance conversion RapidEye data. And then, shadow and water class are extracted using training data of converted reflectance image. Object-based impervious surface can be generated by spectral mixture analysis based on land cover map of Ministry of Environment with medium scale, in the case of other classes except shadow and water classes. The experiment shows that result by our method represents high classification accuracy compared to reference data, quantitatively.