• Title/Summary/Keyword: 인공위성 영상

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Comparison and Analysis of Matching DEM Using KOMPSAT-3 In/Cross-track Stereo Pair (KOMPSAT-3 In/Cross-track 입체영상을 이용한 매칭 DEM 비교 분석)

  • Oh, Kwan-Young;Jeong, Eui-Cheon;Lee, Kwang-Jae;Kim, Youn-Soo;Lee, Won-Jin
    • Korean Journal of Remote Sensing
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    • v.34 no.6_3
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    • pp.1445-1456
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    • 2018
  • The purpose of this study is to compare the quality and characteristics of matching DEMs by using KOMPSAT-3 stereo pair capture in in-track and cross-track. For this purpose, two stereo pairs of KOMPSAT-3 were collected that were taken in the same area. The two stereo pairs have similar stereo geometry elements such as B/H, convergence angle. Sensor modeling for DEM production was performed with RFM affine calibration using multiple GCPs. The GCPs used in the study were extracted from the 0.25 m ortho-image and 5 meter DEM provided by NGII. In addition, matching DEMs were produced at the same resolution as the reference DEMs for a comparison analysis. As a result of the experiment, the horizontal and vertical errors at the CPs indicated an accuracy of 1 to 3 pixels. In addition, the shapes and accuracy of two DEMs produced in areas where the effects of natural or artificial surface land were low were almost similar.

Analysis of Coastline Changes in Yeongdong Region Using Aerial Photos and CORONA Satellite Images (항공사진과 CORONA 위성영상을 이용한 영동지역 해안선 변화 분석)

  • Ahn, Seunghyo;Kim, Gihong;Lee, Hanna
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.40 no.3
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    • pp.187-193
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    • 2022
  • In the Yeongdong region of Gangwon-do, coastal areas are important resources in terms of cultural, social and economic aspects. However, the coast of Gangwon-do is experiencing severe erosion, and it is concerned that its adverse effects will gradually increase. In this study, coastline changes of Yangyang and Gangneung in Gangwon-do were tracked and analyzed over a long period of time. In order to build time series image data, aerial photos from the 1940s to the present were mainly used, and data from CORONA satellite, which operated from the 1960s to the early 1970s, were collected and used together. Using 51cm resolution ortho image and 2m resolution Digital Elevation Model(DEM) as reference, ground control points were selected to perform geometric correction on the aerial photos and CORONA images. Subsequently, Canny edge detector applied to these images to extract the coastlines. As a result of analyzing the extracted and vectorized coastlines by overlaying them in chronological order, erosion and deposition occurring around the artificial structures and on the nearby beaches were observed. In this study, the effect of seasonal variation, tide, and various coastal management including the beach filling were not considered. Because coastal erosion is greatly affected by geographic factors, each local government must find its own solution. Continuous research and local data accumulation are required.

Hyperspectral Image Analysis Technology Based on Machine Learning for Marine Object Detection (해상 객체 탐지를 위한 머신러닝 기반의 초분광 영상 분석 기술)

  • Sangwoo Oh;Dongmin Seo
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.28 no.7
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    • pp.1120-1128
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    • 2022
  • In the event of a marine accident, the longer the exposure time to the sea increases, the faster the chance of survival decreases. However, because the search area of the sea is extremely wide compared to that of land, marine object detection technology based on the sensor mounted on a satellite or an aircraft must be applied rather than ship for an efficient search. The purpose of this study was to rapidly detect an object in the ocean using a hyperspectral image sensor mounted on an aircraft. The image captured by this sensor has a spatial resolution of 8,241 × 1,024, and is a large-capacity data comprising 127 spectra and a resolution of 0.7 m per pixel. In this study, a marine object detection model was developed that combines a seawater identification algorithm using DBSCAN and a density-based land removal algorithm to rapidly analyze large data. When the developed detection model was applied to the hyperspectral image, the performance of analyzing a sea area of about 5 km2 within 100 s was confirmed. In addition, to evaluate the detection accuracy of the developed model, hyperspectral images of the Mokpo, Gunsan, and Yeosu regions were taken using an aircraft. As a result, ships in the experimental image could be detected with an accuracy of 90 %. The technology developed in this study is expected to be utilized as important information to support the search and rescue activities of small ships and human life.

Investigation of Dice Artificial Reef Stability Installed (1981-2004 years) on Pohang Coast of the East Sea (경상북도 포항시 해역에 시설된(1981-2004년) 사각형 어초의 상태조사)

  • Cho, Yong-Chul;Kim, Wan-Ki;Lee, Chae-Sung;Kim, Nam-Il
    • Journal of Advanced Marine Engineering and Technology
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    • v.34 no.1
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    • pp.177-182
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    • 2010
  • Sediment transport around artificial habitat which is induced by the change of flow due to installation of the structure plays a role not only as a defect function of subsidence and burial but also bottom-environment control function. Using Side Scan Sonar (SSS), Differential Global Positioning System (DGPS) and Scuba diving equipment, we investigated a facility condition of a dice reef installed on Pohang coast of the East Sea. Investigation result, at total 139 place, 10,526 dice reef was discovered. As the level which affects function of the above 0.5m, the case 4 place of burial (0.5~1.2m, 2.9%), scour appeared with 3 place (0.5m, 2.2%) and broken was appeared with 183 artificial reefs (1.74%). As a result, dice reef installed Pohang coast appeared to mostly stable.

Extracting Roof Edges of Small Buildings from Digital Aerial Photographs (수치항공사진으로부터 소형건물의 지붕 경계 추출)

  • Lee, Jin-Duk;Bhang, Kon-Joon;Kim, Sung-Hoon;Lee, Kyu-Dal
    • The Journal of the Korea Contents Association
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    • v.14 no.5
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    • pp.425-435
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    • 2014
  • The research for extracting man-made features such as building and road from the aerial photograph or satellite imagery has been performed actively. As lately the resolution of digital aerial photographs was improved, unwanted features(noise) would be often detected. An edge detection algorithm is developed to make up for such a noise problem, make boundaries of wanted objects clear and extract only needed features. The algorithm developed in this research performs separating RGB channels, differencing between channels, transforming in to binary images, excluding noises and restoring shapes, and edge extraction in order. The images to be used for edge detection are prepared through bundle adjustment, DTM extraction, orthorectification and mosaicking. The roof edges of small building on preprocessed digital aerial orthophotos were extracted using the algorithm developed in this study. The validity of the algorithms was proved by comparing edge results of small building extracted in this study with those of conventional methods.

Evaluation of Space-based Wetland InSAR Observations with ALOS-2 ScanSAR Mode (습지대 변화 관측을 위한 ALOS-2 광대역 모드 적용 연구)

  • Hong, Sang-Hoon;Wdowinski, Shimon
    • Korean Journal of Remote Sensing
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    • v.38 no.5_1
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    • pp.447-460
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    • 2022
  • It is well known that satellite synthetic aperture radar interferometry (InSAR) has been widely used for the observation of surface displacement owing to earthquakes, volcanoes, and subsidence very precisely. In wetlands where vegetation exists on the surface of the water, it is possible to create a water level change map with high spatial resolution over a wide area using the InSAR technique. Currently, a number of imaging radar satellites are in operation, and most of them support a ScanSAR mode observation to gather information over a large area at once. The Cienaga Grande de Santa Marta (CGSM) wetland, located in northern Colombia, is a vast wetland developed along the Caribbean coast. The CGSM wetlands face serious environmental threats from human activities such as reclamation for agricultural uses and residential purposes as well as natural causes such as sea level rise owing to climate change. Various restoration and protection plans have been conducted to conserve these invaluable environments in recognition of the ecological importance of the CGSM wetlands. Monitoring of water level changes in wetland is very important resources to understand the hydrologic characteristics and the in-situ water level gauge stations are usually utilized to measure the water level. Although it can provide very good temporal resolution of water level information, it is limited to fully understand flow pattern owing to its very coarse spatial resolution. In this study, we evaluate the L-band ALOS-2 PALSAR-2 ScanSAR mode to observe the water level change over the wide wetland area using the radar interferometric technique. In order to assess the quality of the interferometric product in the aspect of spatial resolution and coherence, we also utilized ALOS-2 PALSAR-2 stripmap high-resolution mode observations.

Construction and Application of 3D Image Model for GIS Spatial Analysis (GIS 공간분석을 위한 3D 영상모형의 구축과 활용)

  • Jung, Sung-Heuk;Lee, Kae-Dong;Lee, Jae-Kee
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.26 no.6
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    • pp.561-569
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    • 2008
  • Currently, satellite image, aerial image and airborne laser scanning data are mostly used to build 3D image models. However, we are in need of quality 3D image models as current models cannot express topographic and features most elaborately and realistically. When making 3D image models, the model is first built and textures from terrestrial photos are applied to add realistic features to the model. This study analyzed techniques to use photogrammetry and laser scanning data to create a 3D image models with topography, building and statue that emphasize spatial accuracy, delicate depiction and photo-realistic imaging. 3D image models with spatial accuracy and photographic texture were built to be served via 3D image map services systems on the internet. The 3D image models can be used for various purposes, such as daylight and view right analysis, landscape analysis, facility management system.

Application and Analysis of Remote Sensing Data for Disaster Management in Korea - Focused on Managing Drought of Reservoir Based on Remote Sensing - (국가 재난 관리를 위한 원격탐사 자료 분석 및 활용 - 원격탐사기반 저수지 가뭄 관리를 중심으로 -)

  • Kim, Seongsam;Lee, Junwoo;Koo, Seul;Kim, Yongmin
    • Korean Journal of Remote Sensing
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    • v.38 no.6_3
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    • pp.1749-1760
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    • 2022
  • In modern society, human and social damages caused by natural disasters and frequent disaster accidents have been increased year by year. Prompt access to dangerous disaster sites that are inaccessible or inaccessible using state-of-the-art Earth observation equipment such as satellites, drones, and survey robots, and timely collection and analysis of meaningful disaster information. It can play an important role in protecting people's property and life throughout the entire disaster management cycle, such as responding to disaster sites and establishing mid-to long-term recovery plans. This special issue introduces the National Disaster Management Research Institute (NDMI)'s disaster management technology that utilizes various Earth observation platforms, such as mobile survey vehicles equipped with close-range disaster site survey sensors, drones, and survey robots, as well as satellite technology, which is a tool of remote earth observation. Major research achievements include detection of damage from water disasters using Google Earth Engine, mid- and long-term time series observation, detection of reservoir water bodies using Sentinel-1 Synthetic Aperture Radar (SAR) images and artificial intelligence, analysis of resident movement patterns in case of forest fire disasters, and data analysis of disaster safety research. Efficient integrated management and utilization plan research results are summarized. In addition, research results on scientific investigation activities on the causes of disasters using drones and survey robots during the investigation of inaccessible and dangerous disaster sites were described.

Preliminary Research of the Sedimentary Environment in Bupyeng Reservoir Region, Soyang Lake in Chuncheon - Focus on Sentinel-2 Satellite Images and in-situ data - (춘천시 소양호 상류 부평지구의 퇴적환경에 대한 선행연구 - 현장조사와 위성영상자료를 중심으로 -)

  • Kim, GeonYoung;Kim, Dain;Kim, TaeHun;Lee, JinHo;Jang, YoSep;Choi, HyunJin;Shim, WonJae;Park, SungJae;Lee, Chang-Wook
    • Korean Journal of Remote Sensing
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    • v.34 no.6_1
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    • pp.1119-1130
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    • 2018
  • Soyang Lake has been contributing to economic growth by preventing flood damage in the metropolitan area, the water level in the middle to upper flow of lake has been greatly decreased due to the drought in 2015. In order to restore the existing flow rate, Bupyungbo has been built in Bupyeong-ri, Shin Nam-myeon, Inje-gun to cause artificial changes on the sedimentary environment of Bupyeong freshwater region. Therefore, this study intends to confirm the changes of sedimentary environment since Bupyeongbo has been utilized. For this study, we used the Sentinel-2 satellite image data periodically to measure the dimension of water according to the volume of water kept near Bupyung district and analyzed the particle size and the percentage of water content of the sediments through field study. The Sentnel-2 satellite images showed us how the water surface has been changed and that during the period from September 2017 to October 2018, the minimum and maximum area of water surface was observed in June 2018 and in January 2018, respectively. In addition, we find that the smaller being the particle size, the higher having the water content and that there is higher the correlation between the water content and the grain size of the sediment layer. Hereafter, if we will acquire the drone images at Bupyung district, we expect that we will be able to measure the distribution of sediments in the same area according to different time periods and observe various kinds of sediment through field work.

A Study on Evaluating the Possibility of Monitoring Ships of CAS500-1 Images Based on YOLO Algorithm: A Case Study of a Busan New Port and an Oakland Port in California (YOLO 알고리즘 기반 국토위성영상의 선박 모니터링 가능성 평가 연구: 부산 신항과 캘리포니아 오클랜드항을 대상으로)

  • Park, Sangchul;Park, Yeongbin;Jang, Soyeong;Kim, Tae-Ho
    • Korean Journal of Remote Sensing
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    • v.38 no.6_1
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    • pp.1463-1478
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    • 2022
  • Maritime transport accounts for 99.7% of the exports and imports of the Republic of Korea; therefore, developing a vessel monitoring system for efficient operation is of significant interest. Several studies have focused on tracking and monitoring vessel movements based on automatic identification system (AIS) data; however, ships without AIS have limited monitoring and tracking ability. High-resolution optical satellite images can provide the missing layer of information in AIS-based monitoring systems because they can identify non-AIS vessels and small ships over a wide range. Therefore, it is necessary to investigate vessel monitoring and small vessel classification systems using high-resolution optical satellite images. This study examined the possibility of developing ship monitoring systems using Compact Advanced Satellite 500-1 (CAS500-1) satellite images by first training a deep learning model using satellite image data and then performing detection in other images. To determine the effectiveness of the proposed method, the learning data was acquired from ships in the Yellow Sea and its major ports, and the detection model was established using the You Only Look Once (YOLO) algorithm. The ship detection performance was evaluated for a domestic and an international port. The results obtained using the detection model in ships in the anchorage and berth areas were compared with the ship classification information obtained using AIS, and an accuracy of 85.5% and 70% was achieved using domestic and international classification models, respectively. The results indicate that high-resolution satellite images can be used in mooring ships for vessel monitoring. The developed approach can potentially be used in vessel tracking and monitoring systems at major ports around the world if the accuracy of the detection model is improved through continuous learning data construction.