• Korean Journal of Remote Sensing
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• v.38 no.1
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• pp.103-110
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• 2022

Since satellite images generally include clouds in the atmosphere, it is essential to detect or mask clouds before satellite image processing. Clouds were detected using physical characteristics of clouds in previous research. Cloud detection methods using deep learning techniques such as CNN or the modified U-Net in image segmentation field have been studied recently. Since image segmentation is the process of assigning a label to every pixel in an image, precise pixel-based dataset is required for cloud detection. Obtaining accurate training datasets is more important than a network configuration in image segmentation for cloud detection. Existing deep learning techniques used different training datasets. And test datasets were extracted from intra-dataset which were acquired by same sensor and procedure as training dataset. Different datasets make it difficult to determine which network shows a better overall performance. To verify the effectiveness of the cloud detection network such as Cloud-Net, two types of networks were trained using the cloud dataset from KOMPSAT-3 images provided by the AIHUB site and the L8-Cloud dataset from Landsat8 images which was publicly opened by a Cloud-Net author. Test data from intra-dataset of KOMPSAT-3 cloud dataset were used for validating the network. The simulation results show that the network trained with KOMPSAT-3 cloud dataset shows good performance on the network trained with L8-Cloud dataset. Because Landsat8 and KOMPSAT-3 satellite images have different GSDs, making it difficult to achieve good results from cross-sensor validation. The network could be superior for intra-dataset, but it could be inferior for cross-sensor data. It is necessary to study techniques that show good results in cross-senor validation dataset in the future.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.3
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• pp.73-82
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• 2021

Rural roads are the significant infrastructure for developing and managing the rural areas, hence the utilization of the remote sensing datasets for managing the rural roads is necessary for expanding the rural transportation infrastructure and improving the life quality of the rural residents. In this research, the two different methods such as image classification and image segmentation were compared for mapping the rural road based on the given high-resolution satellite image acquired in the rural areas. In the image classification method, the deep learning with the multiple neural networks was employed to the given high-resolution satellite image for generating the object classification map, then the rural roads were mapped by extracting the road objects from the generated object classification map. In the image segmentation method, the multiresolution segmentation was employed to the same satellite image for generating the segment image, then the rural roads were mapped by merging the road objects located on the rural roads on the satellite image. We used the 100 checkpoints for assessing the accuracy of the two rural roads mapped by the different methods and drew the following conclusions. The image segmentation method had the better performance than the image classification method for mapping the rural roads using the give satellite image, because some of the rural roads mapped by the image classification method were not identified due to the miclassification errors occurred in the object classification map, while all of the rural roads mapped by the image segmentation method were identified. However some of the rural roads mapped by the image segmentation method also had the miclassfication errors due to some rural road segments including the non-rural road objects. In future research the object-oriented classification or the convolutional neural networks widely used for detecting the precise objects from the image sources would be used for improving the accuracy of the rural roads using the high-resolution satellite image.

• Journal of Korea Spatial Information System Society
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• v.6 no.2 s.12
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• pp.77-84
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• 2004

The purpose of this study is to suggest an effective guideline for reducing communication costs and improving qualities of Intelligent Transport Systems (ITS) by totally or partially integrating wireless communication networks between equipments of ITS Centers and Roadside in the National ITS Physical Architecture. We analyzed wire and wireless communication networks such as wireless LAN and satellite communications in the National Highway Traffic Management System (NHTMS) for receiving and transmitting transportation data. Also, we analyzed operation and communication costs to find out right communication networks for ITS. The results of this study will be used to build and operate many other ITS systems including Korea Highway Corporation.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.2
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• pp.127-135
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• 2022

Compared to the continuous increase of domestic nano-satellite development cases, the initial communication success rate is relatively low. In a situation where communication cases of LEO satellites using commercial satellite communication networks are increasing recently. In this situation, the SNIPE project developed by the KASI(Korea Astronomy and Space Science Institute), KARI(Korea Aerospace Research Institute), and Yonsei University apply an Iridium module for communication test to the SNIPE nano-satellites. Therefore, in this paper, the visibility analysis of the iridium module on the SNIPE satellite was analyzed under considering the orbital and communication environment of the iridium satellite constellation and the attitude control mode. In the case of LEO satellites, the communication possibility was limited due to the relatively small iridium communication coverage for high altitude and the high doppler shift considered in the iridium communication network. For this reason, in this paper, it could be simulated that there was a more performance difference according to the difference in relative RAAN(Right Ascension of Ascending Node) angle with the Iridium constellation. Finally, by checking the visibility of communication module under the tumbling situation that occurred during the initial deployment of the nano-satellite, the possibility of using the iridium communication technology was analyzed.

• Journal of Korea Water Resources Association
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• v.52 no.4
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• pp.279-289
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• 2019

Unlike other natural disasters, drought is a reoccurring and region-wide phenomenon after being triggered by a prolonged precipitation deficiency. Considering that remote sensing products provide consistent temporal and spatial measurements of precipitation, this study developed a remote sensing data-based drought outlook model. The meteorological drought was defined by the Standardized Precipitation Index (SPI) achieved from PERSIANN_CDR, TRMM 3B42 and GPM IMERG images. Bayesian networks were employed in this study to combine the historical drought information and dynamical prediction products in advance of drought outlook. Drought outlook was determined through a decision-making model considering the current drought condition and forecasted condition from the Bayesian networks. Drought outlook condition was classified by four states such as no drought, drought occurrence, drought persistence, and drought removal. The receiver operating characteristics (ROC) curve analysis were employed to measure the relative outlook performance with the dynamical prediction production, Multi-Model Ensemble (MME). The ROC analysis indicated that the proposed outlook model showed better performance than the MME, especially for drought occurrence and persistence of 2- and 3-month outlook.

• Journal of Satellite, Information and Communications
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• v.12 no.3
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• pp.98-102
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• 2017

In this paper, we study RF-powered backscatter cognitive radio networks to improve the performance for the secondary user which is backscatter radio based wireless sensors. In our proposed model, we consider an avoiding the doubly round-trip attenuation to add a carrier emitter and utilization of spectrum sensing information. When the primary channel is busy, the secondary user is able to harvest RF energy from the channel through a hybrid-access point (H-AP) and a carrier emitter. When the channel becomes idle, the secondary user will be use the harvested energy to operate wireless sensors, to use the sensing and to backscatter through the carrier emitter. We model mathematically the deterministic and multisource elements of a number of tagged channels. In the proposed communication environment, we show the BER performance of the backscatter communication using WiFi signal.

• Journal of Satellite, Information and Communications
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• v.9 no.3
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• pp.98-103
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• 2014

In this paper, we propose and analyze a novel interference cancellation scheme in cooperation communication environment in which a large number of users exist. In cooperative communication system consisting a source, destination, and relay, ad-hoc groups undergo a rapid degradation because of interference data form adjacent ad-hoc groups. To solve these problems, we propose Zero Forcing (FC) and Minimum Mean Square Error (MMSE) and make a dent in the magnitude of interference. Finally, we can obtain orignal data using Successive Interference Cancellation (SIC). The performance of proposed scheme is analyzed in terms of a bit error probability. The results of the paper can be applied to design of various ad-hoc networks for cooperation communication systems.

• Journal of Satellite, Information and Communications
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• v.12 no.4
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• pp.131-140
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• 2017

Multipath TCP (MPTCP) is a transport layer protocol that simultaneously transmits data using multiple interfaces. MPTCP is superior to existing TCP in network environment with homogeneous subflows, but it shows worse performance compared to existing TCP in network environment with bufferbloat. If a bufferbloat occurs in one of the MPTCP multipaths, the packet will not arrive at the MPTCP receive buffer due to a sudden increase in delay time, resulting in a HoL blocking phenomenon. It makes the receive window of the other path to be zero. In this paper, we apply Adaptive Random Early Detection (ARED), Controlled Delay (CoDel) and Proportional Integral Controller Enhanced (PIE) among the proposed Active Queue Management (AQM) to limit the delay of bufferbloat path. Experiments were conducted to improve the performance of MPTCP in heterogeneous networks. In order to carry out the experiment, we constructed a Linux-based testbed and compared the MPTCP performance with that of the existing droptail.

• Journal of Satellite, Information and Communications
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• v.8 no.4
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• pp.53-57
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• 2013

The quality of service for the voice and data communication is one of the most important elements in the mobile cellular networks. This quality has the time varying characteristics depending on the wireless network environments. In order to guarantee the quality of service at the predefined level, the mobile service provider needs to collect all the information about the level of quality served by the local base stations. In the conventional method the information on the service quality is measured and collected by the moving vehicle adopting the global positioning device. However this method requires relatively high cost and does not cover all the service areas. In this paper a new method is proposed utilizing a measurement node with local area communication transceiver and the mobile user equipment. In the proposed method the node communicates with the user equipment periodically to monitor the information on the service quality. The resulting information is reported to the measurement server in the mobile network. This method could be applied to either the circuit or the packet based networks. It also has an advantage in terms of the cost efficiency compared to the conventional method considering the required the equipment and the human resources.

• Journal of Satellite, Information and Communications
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• v.10 no.2
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• pp.24-29
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• 2015

Recently, with developments of various networks, devices and various services, energy efficiency has become one of the most crucial issues with respect to sustainability of mobile devices. For connecting to networks seamlessly to offer services, a scenario of RF energy harvesting which supplies energy to wireless devices with RF signals is assumed. To increase the efficiency of RF energy harvesting, this paper proposes a RF energy harvesting algorithm which is based upon a frequency selective fading map. Through the algorithm, a receiver of mobile device can get fading information at each frequency and select a frequency which has the best quality. At the end, the simulation result demonstrates its superiority by showing a 4.45dB improvement in comparison to a deep fading frequency point.