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Korean Journal of Remote Sensing

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수록정보
수록범위 : 1권1호(1985)~37권1호(2021) |수록논문 수 : 1,592
대한원격탐사학회지
37권1호(2021년 02월) 수록논문
최근 권호 논문
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KCI등재

1Flow Velocity Change of David Glacier, East Antarctica, from 2016 to 2020 Observed by Sentinel-1A SAR Offset Tracking Method

저자 : Jihyun Moon , Yuri Cho , Hoonyol Lee

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 37권 1호 발행 연도 : 2021 페이지 : pp. 1-11 (11 pages)

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This study measures the change of ice flow velocity of David Glacier, one of the fast-moving glaciers in East Antarctica that drains through Drygalski Ice Tongue. In order to effectively observe the rapid flow velocity, we applied the offset tracking technique to Sentinel-1A SAR images obtained from 2016 to 2020 with 36-day temporal baseline. The resulting velocity maps were averaged and the two relatively fast points (A1 and A2) were selected for further time-series analysis. The flow velocity increased during the Antarctic summer (around December to March) over the four years' observation period probably due to the ice surface melting and reduced friction on the ice bottom. Bedmap2 showed that the fast flow velocities at A1 and A2 are associated with a sharp decrease in the ice surface and bottom elevation so that ice volumetric cross-section narrows down and the crevasses are being created on the ice surface. The local maxima in standard deviation of ice velocity, S1 and S2, showed random temporal fluctuation due to the rotational ice swirls causing error in offset tracking method. It is suggested that more robust offset tracking method is necessary to incorporate rotational motion.

KCI등재

2Damage Proxy Map (DPM) of the 2016 Gyeongju and 2017 Pohang Earthquakes Using Sentinel-1 Imagery

저자 : Arip Syaripudin Nur , Chang-wook Lee

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 37권 1호 발행 연도 : 2021 페이지 : pp. 13-22 (10 pages)

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The ML 5.8 earthquake shocked Gyeongju, Korea, at 11:32:55 UTC on September 12, 2016. One year later, on the afternoon of November 15, 2017, the ML 5.4 earthquake occurred in Pohang, South Korea. The earthquakes injured many residents, damaged buildings, and affected the economy of Gyeongju and Pohang. The damage proxy maps (DPMs) were generated from Sentinel-1 synthetic aperture radar (SAR) imagery by comparing pre- and co-events interferometric coherences to identify anomalous changes that indicate damaged by the earthquakes. DPMs manage to detect coherence loss in residential and commercial areas in both Gyeongju and Pohang earthquakes. We found that our results show a good correlation with the Korea Meteorological Administration (KMA) report with Modified Mercalli Intensity (MMI) scale values of more than VII (seven). The color scale of Sentinel-1 DPMs indicates an increasingly significant change in the area covered by the pixel, delineating collapsed walls and roofs from the official report. The resulting maps can be used to assess the distribution of seismic damage after the Gyeongju and Pohang earthquakes and can also be used as inventory data of damaged buildings to map seismic vulnerability using machine learning in Gyeongju or Pohang.

KCI등재

3Design of LEO Constellations with Inter-satellite Connects Based on the Performance Evaluation of the Three Constellations SpaceX, OneWeb and Telesat

저자 : Peng Zong , Saeid Kohani

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 37권 1호 발행 연도 : 2021 페이지 : pp. 23-40 (18 pages)

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The idea of designing LEO's satellite constellations has become very important for internet access. Several LEO satellite constellations have been designed and used for global communications. In this paper, by examining three LEO satellite constellations, namely SpaceX's 4425 satellites Ku-Kaband system, OneWeb's 720 satellites Ku-Ka-band system, Telesat's 117 satellites Ka-band system. And evaluating the power of data transmission and their telecommunications, we come close to a conceptual design area. First with the mathematical modeling and formulation and the design of inter-orbital communications for satellites, intersatellite communications, inter-orbital communications, we get a complete design based on the genetic algorithm for LEO satellite constellation design. And then, using simulations and design software, the final results of the designed model are obtained. Finally, we compare the results of the designed model with other existing LEO satellite constellations.

KCI등재

4Improvement of Thunderstorm Detection Method Using GK2A/AMI, RADAR, Lightning, and Numerical Model Data

저자 : Ha-yeong Yu , Myoung-seok Suh , Seoung-oh Ryu

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 37권 1호 발행 연도 : 2021 페이지 : pp. 41-55 (15 pages)

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To detect thunderstorms occurring in Korea, National Meteorological Satellite Center (NMSC) also introduced the rapid-development thunderstorm (RDT) algorithm developed by EUMETSAT. At NMCS, the H-RDT (HR) based on the Himawari-8 satellite and the K-RDT (KR) which combines the GK2A convection initiation output with the RDT were developed. In this study, we optimized the KR (KU) to improve the detection level of thunderstorms occurring in Korea. For this, we used all available data, such as GK2A/AMI, RADAR, lightning, and numerical model data from the recent two years (2019-2020). The machine learning of logistic regression and stepwise variable selection was used to optimize the KU algorithms. For considering the developing stages and duration time of thunderstorms, and data availability of GK2A/AMI, a total of 72 types of detection algorithms were developed. The level of detection of the KR, HR, and KU was evaluated qualitatively and quantitatively using lightning and RADAR data. Visual inspection using the lightning and RADAR data showed that all three algorithms detect thunderstorms that occurred in Korea well. However, the level of detection differs according to the lightning frequency and day/night, and the higher the frequency of lightning, the higher the detection level is. And the level of detection is generally higher at night than day. The quantitative verification of KU using lightning (RADAR) data showed that POD and FAR are 0.70 (0.34) and 0.57 (0.04), respectively. The verification results showed that the detection level of KU is slightly better than that of KR and HR.

KCI등재

5The Estimated Source of 2017 Pohang Earthquake Using Surface Deformation Modeling Based on Multi-Frequency InSAR Data

저자 : Muhammad Fulki Fadhillah , Chang-wook Lee

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 37권 1호 발행 연도 : 2021 페이지 : pp. 57-67 (11 pages)

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An earthquake occurred on 17 November 2017 in Pohang, South Korea with a strength of 5.4 Mw. This is the second strongest earthquake recorded by local authorities since the equipment was first installed. In order to improve understanding of earthquakes and surface deformation, many studies have been conducted according to these phenomena. In this research, we will estimate the surface deformation using the Okada model equation. The SAR images of three satellites with different wavelengths (ALOS-2, Cosmo SkyMed and Sentinel-1) were used to produce the interferogram pairs. The interferogram is used as a reference for surface deformation changes by using Okada to determine the source of surface deformation that occurs during an earthquake. The Non-linear optimization (Levemberg-Marquadrt algorithm) and Monte Carlo restart was applied to optimize the fault parameter on modeling process. Based on the modeling results of each satellite data, the fault geometry is ~6 km length, ~2 km width and ~5 km depth. The root mean square error values in the surface deformation model results for Sentinel, CSK and ALOS are 0.37 cm, 0.79 cm and 1.47 cm, respectively. Furthermore, the results of this modeling can be used as learning material in understanding about seismic activity to minimize the impacts that arise in the future.

KCI등재

6Moon Phase based Threshold Determination for VIIRS Boat Detection

저자 : Euihyun Kim , Sang-wan Kim , Hahn Chul Jung , Joo-hyung Ryu

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 37권 1호 발행 연도 : 2021 페이지 : pp. 69-84 (16 pages)

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Awareness of boats is a main issue in areas of fishery management, illegal fishing, and maritime traffic, etc. For the awareness, Automatic Identification System (AIS) and Vessel-Pass System (V-PASS) have been widely used to collect the boat-related information. However, only using these systems makes it difficult to collect the accurate information. Recently, satellite-based data has been increasingly used as a cooperative system. In 2015, U.S. National Oceanic and Atmospheric Administration (NOAA) developed a boat detection algorithm using Visible Infrared Imaging Radiometer Suite (VIIRS) Day & Night Band (DNB) data. Although the detections have been widely utilized in many publications, it is difficult to estimate the night-time fishing boats immediately. Particularly, it is difficult to estimate the threshold due to the lunar irradiation effect. This effect must be corrected to apply a single specific threshold. In this study, the moon phase was considered as the main frequency of this effect. Considering the moon phase, relational expressions are derived and then used as offsets for relative correction. After the correction, it shows a significant reduction in the standard deviation of the threshold compared to the threshold of NOAA. Through the correction, this study can set a constant threshold every day without determination of different thresholds. In conclusion, this study can achieve the detection applying the single specific threshold regardless of the moon phase.

KCI등재

7Study on Dimensionality Reduction for Sea-level Variations by Using Altimetry Data around the East Asia Coasts

저자 : Do-hyun Hwang , Suho Bak , Min-ji Jeong , Na-kyeong Kim , Mi-so Park , Bo-ram Kim , Hong-joo Yoon

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 37권 1호 발행 연도 : 2021 페이지 : pp. 85-95 (11 pages)

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Recently, as data mining and artificial neural network techniques are developed, analyzing large amounts of data is proposed to reduce the dimension of the data. In general, empirical orthogonal function (EOF) used to reduce the dimension in the ocean data and recently, Self-organizing maps (SOM) algorithm have been investigated to apply to the ocean field. In this study, both algorithms used the monthly Sea level anomaly (SLA) data from 1993 to 2018 around the East Asia Coasts. There was dominated by the influence of the Kuroshio Extension and eddy kinetic energy. It was able to find the maximum amount of variance of EOF modes. SOM algorithm summarized the characteristic of spatial distributions and periods in EOF mode 1 and 2. It was useful to find the change of SLA variable through the movement of nodes. Node 1 and 5 appeared in the early 2000s and the early 2010s when the sea level was high. On the other hand, node 2 and 6 appeared in the late 1990s and the late 2000s, when the sea level was relatively low. Therefore, it is considered that the application of the SOM algorithm around the East Asia Coasts is well distinguished. In addition, SOM results processed by SLA data, it is able to apply the other climate data to explain more clearly SLA variation mechanisms.

KCI등재

8Retrieval of High-Resolution Grid Type Visibility Data in South Korea Using Inverse Distance Weighting and Kriging

저자 : Taeho Kang , Myoung-seok Suh

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 37권 1호 발행 연도 : 2021 페이지 : pp. 97-110 (14 pages)

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Fog can cause large-scale human and economic damages, including traffic systems and agriculture. So, Korea Meteorological Administration is operating about 290 visibility meters to improve the observation level of fog. However, it is still insufficient to detect very localized fog. In this study, high-resolution grid-type visibility data were retrieved from irregularly distributed visibility data across the country. To this end, three objective analysis techniques (Inverse Distance Weighting (IDW), Ordinary Kriging (OK) and Universal Kriging (UK)) were used. To find the best method and parameters, sensitivity test was performed for the effective radius, power parameter and variogram model that affect the level of objective analysis. Also, the effect of data distribution characteristics (level of normality) on the performance level of objective analysis was evaluated. IDW showed a relatively high level of objective analysis in terms of bias, RMSE and correlation, and the performance is inversely proportional to the effective radius and power parameter. However, the two Krigings showed relatively low level of objective analysis, in particular, greatly weakened the variability of the variables, although the level of output was different depending on the variogram model used. As the level of objective analysis is greatly influenced by the distribution characteristics of data, power, and models used, care should be taken when selecting objective analysis techniques and parameters.

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9Keypoint-based Deep Learning Approach for Building Footprint Extraction Using Aerial Images

저자 : Doyoung Jeong , Yongil Kim

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 37권 1호 발행 연도 : 2021 페이지 : pp. 111-122 (12 pages)

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Building footprint extraction is an active topic in the domain of remote sensing, since buildings are a fundamental unit of urban areas. Deep convolutional neural networks successfully perform footprint extraction from optical satellite images. However, semantic segmentation produces coarse results in the output, such as blurred and rounded boundaries, which are caused by the use of convolutional layers with large receptive fields and pooling layers. The objective of this study is to generate visually enhanced building objects by directly extracting the vertices of individual buildings by combining instance segmentation and keypoint detection. The target keypoints in building extraction are defined as points of interest based on the local image gradient direction, that is, the vertices of a building polygon. The proposed framework follows a two-stage, top-down approach that is divided into object detection and keypoint estimation. Keypoints between instances are distinguished by merging the rough segmentation masks and the local features of regions of interest. A building polygon is created by grouping the predicted keypoints through a simple geometric method. Our model achieved an F1-score of 0.650 with an mIoU of 62.6 for building footprint extraction using the OpenCitesAI dataset. The results demonstrated that the proposed framework using keypoint estimation exhibited better segmentation performance when compared with Mask R-CNN in terms of both qualitative and quantitative results.

KCI등재

10The Assessment of Cross Calibration/Validation Accuracy for KOMPSAT-3 Using Landsat 8 and 6S

저자 : Cheonggil Jin , Chuluong Choi

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 37권 1호 발행 연도 : 2021 페이지 : pp. 123-137 (15 pages)

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In this study, we performed cross calibration of KOMPSAT-3 AEISS imaging sensor with reference to normalized pixels in the Landsat 8 OLI scenes of homogenous ROI recorded by both sensors between January 2014 and December 2019 at the Libya 4 PICS. Cross calibration is using images from a stable and well-calibrated satellite sensor as references to harmonize measurements from other sensors and/or characterize other sensors. But cross calibration has two problems; RSR and temporal difference. The RSR of KOMPSAT-3 and Landsat 8 are similar at the blue and green bands. But the red and NIR bands have a large difference. So we calculate SBAF of each sensor. We compared the SBAF estimated from the TOA Radiance simulation with KOMPSAT-3 and Landsat 8, the results displayed a difference of about 2.07~2.92% and 0.96~1.21% in the VIS and NIR bands. Before SBAF, Reflectance and Radiance difference was 0.42~23.23%. Case of difference temporal, we simulated by 6S and Landsat 8 for alignment the same acquisition time. The SBAF-corrected cross calibration coefficients using KOMPSAT-3, 6S and simulated Landsat 8 compared to the initial cross calibration without correction demonstrated a percentage difference in the spectral bands of about 0.866~1.192%. KOMPSAT-3 maximum uncertainty was estimated at 3.26~3.89%; errors due to atmospheric condition minimized to less than 1% (via 6S); Maximum deviation of KOMPSAT-3 DN was less than 1%. As the result, the results affirm that SBAF and 6s simulation enhanced cross-calibration accuracy.

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