• Title/Summary/Keyword: 모니터링 탐사

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GOCI-II Based Low Sea Surface Salinity and Hourly Variation by Typhoon Hinnamnor (GOCI-II 기반 저염분수 산출과 태풍 힌남노에 의한 시간별 염분 변화)

  • So-Hyun Kim;Dae-Won Kim;Young-Heon Jo
    • Korean Journal of Remote Sensing
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    • v.39 no.6_2
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    • pp.1605-1613
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    • 2023
  • The physical properties of the ocean interior are determined by temperature and salinity. To observe them, we rely on satellite observations for broad regions of oceans. However, the satellite for salinity measurement, Soil Moisture Active Passive (SMAP), has low temporal and spatial resolutions; thus, more is needed to resolve the fast-changing coastal environment. To overcome these limitations, the algorithm to use the Geostationary Ocean Color Imager-II (GOCI-II) of the Geo-Kompsat-2B (GK-2B) was developed as the inputs for a Multi-layer Perceptron Neural Network (MPNN). The result shows that coefficient of determination (R2), root mean square error (RMSE), and relative root mean square error (RRMSE) between GOCI-II based sea surface salinity (SSS) (GOCI-II SSS) and SMAP was 0.94, 0.58 psu, and 1.87%, respectively. Furthermore, the spatial variation of GOCI-II SSS was also very uniform, with over 0.8 of R2 and less than 1 psu of RMSE. In addition, GOCI-II SSS was also compared with SSS of Ieodo Ocean Research Station (I-ORS), suggesting that the result was slightly low, which was further analyzed for the following reasons. We further illustrated the valuable information of high spatial and temporal variation of GOCI-II SSS to analyze SSS variation by the 11th typhoon, Hinnamnor, in 2022. We used the mean and standard deviation (STD) of one day of GOCI-II SSS, revealing the high spatial and temporal changes. Thus, this study will shed light on the research for monitoring the highly changing marine environment.

Retrieval of Hourly Aerosol Optical Depth Using Top-of-Atmosphere Reflectance from GOCI-II and Machine Learning over South Korea (GOCI-II 대기상한 반사도와 기계학습을 이용한 남한 지역 시간별 에어로졸 광학 두께 산출)

  • Seyoung Yang;Hyunyoung Choi;Jungho Im
    • Korean Journal of Remote Sensing
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    • v.39 no.5_3
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    • pp.933-948
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    • 2023
  • Atmospheric aerosols not only have adverse effects on human health but also exert direct and indirect impacts on the climate system. Consequently, it is imperative to comprehend the characteristics and spatiotemporal distribution of aerosols. Numerous research endeavors have been undertaken to monitor aerosols, predominantly through the retrieval of aerosol optical depth (AOD) via satellite-based observations. Nonetheless, this approach primarily relies on a look-up table-based inversion algorithm, characterized by computationally intensive operations and associated uncertainties. In this study, a novel high-resolution AOD direct retrieval algorithm, leveraging machine learning, was developed using top-of-atmosphere reflectance data derived from the Geostationary Ocean Color Imager-II (GOCI-II), in conjunction with their differences from the past 30-day minimum reflectance, and meteorological variables from numerical models. The Light Gradient Boosting Machine (LGBM) technique was harnessed, and the resultant estimates underwent rigorous validation encompassing random, temporal, and spatial N-fold cross-validation (CV) using ground-based observation data from Aerosol Robotic Network (AERONET) AOD. The three CV results consistently demonstrated robust performance, yielding R2=0.70-0.80, RMSE=0.08-0.09, and within the expected error (EE) of 75.2-85.1%. The Shapley Additive exPlanations(SHAP) analysis confirmed the substantial influence of reflectance-related variables on AOD estimation. A comprehensive examination of the spatiotemporal distribution of AOD in Seoul and Ulsan revealed that the developed LGBM model yielded results that are in close concordance with AERONET AOD over time, thereby confirming its suitability for AOD retrieval at high spatiotemporal resolution (i.e., hourly, 250 m). Furthermore, upon comparing data coverage, it was ascertained that the LGBM model enhanced data retrieval frequency by approximately 8.8% in comparison to the GOCI-II L2 AOD products, ameliorating issues associated with excessive masking over very illuminated surfaces that are often encountered in physics-based AOD retrieval processes.

Analysis of Micro-Sedimentary Structure Characteristics Using Ultra-High Resolution UAV Imagery: Hwangdo Tidal Flat, South Korea (초고해상도 무인항공기 영상을 이용한 한국 황도 갯벌의 미세 퇴적 구조 특성 분석)

  • Minju Kim;Won-Kyung Baek;Hoi Soo Jung;Joo-Hyung Ryu
    • Korean Journal of Remote Sensing
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    • v.40 no.3
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    • pp.295-305
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    • 2024
  • This study aims to analyze the micro-sedimentary structures of the Hwangdo tidal flats using ultra-high resolution unmanned aerial vehicle (UAV) data. Tidal flats, located in the transitional area between land and sea, constantly change due to tidal activities and provide a unique environment important for understanding sedimentary processes and environmental conditions. Traditional field observation methods are limited in spatial and temporal coverage, and existing satellite imagery does not provide sufficient resolution to study micro-sedimentary structures. To overcome these limitations, high-resolution images of the Hwangdo tidal flats in Chungcheongnam-do were acquired using UAVs. This area has experienced significant changes in its sedimentary environment due to coastal development projects such as sea wall construction. From May 17 to 18, 2022, sediment samples were collected from 91 points during field surveys and 25 in-situ points were intensively analyzed. UAV data with a spatial resolution of approximately 0.9 mm allowed identifying and extracting parameters related to micro-sedimentary structures. For mud cracks, the length of the major axis of the polygons was extracted, and the wavelength and ripple symmetry index were extracted for ripple marks. The results of the study showed that in areas with mud content above 80%, mud cracks formed at an average major axis length of 37.3 cm. In regions with sand content above 60%, ripples with an average wavelength of 8 cm and a ripple symmetry index of 2.0 were formed. This study demonstrated that micro-sedimentary structures of tidal flats can be effectively analyzed using ultra-high resolution UAV data without field surveys. This highlights the potential of UAV technology as an important tool in environmental monitoring and coastal management and shows its usefulness in the study of sedimentary structures. In addition, the results of this study are expected to serve as baseline data for more accurate sedimentary facies classification.

Introduction of Satellite Remote Sensing Technologies to Korea Coast Guard (해양경찰청 위성활용 방안)

  • Yang, Chan-Su;Oh, Jeong-Hwan
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2011.11a
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    • pp.154-155
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    • 2011
  • 2010년 천리안위성의 성공적인 발사에 따라 인공위성의 활용에 대한 기대가 커지고 있다. 천리안 해양관측위성(GOCI)이외에 아리랑 2호가 현재 운용중인 우리나라 위성들이다. 가까운 시기에 아리랑 5호(2011년 말), 아리랑 3호(2012년), 아리랑 3A호(2013년)가 발사될 예정이다. 즉, 해양적용을 위한 위성환경은 이제부터 준비되고 있다고 볼 수 있다. 대외적으로 보면, 인공위성 자원은 아주 많다. 문제는 이와 같은 자원을 어떻게 활용할 것인가 인데 이의 활용 기술 개발적 측면에서는 많이 소홀한 것이 사실이다. 전세계적으로 이 시스템 개발을 위한 치열한 경쟁이 진행 중에 있다. 이미 소말리아 주변 감시체계는 많은 부분을 위성에 의지하고 있다. 우리나라에서 최초로 위성활용 가능성을 보여준 사건이 허베이스피리트호 원유유출 사고이다. 이 사고는 2007년 12월7일 아침 7시6분경 서해안 만리포 북서쪽 10km 해상에서 크레인을 적재한 1만1800t급 바지선이 정박 중인 홍콩 선적 유조선 허베이 스피리트호(14만6000t급)와 부딪치면서 발생했다. 이와 같은 기름 유출 사고의 경우, 유출 범위를 정확하게 이해하는 것이 중요하다. 거의 준비된 상태가 아님에도 불구하고 12월 8일 아침 최초로 유출된 기름을 모습을 보여주는 위성이미지(광학위성)가 얻어졌다. 하지만 이와 같은 자료가 관련 전문가가 이용할 수 있기까지 많은 시간이 소용되었고, 이 정보를 전달할 수 있는 방법도 없었다. 사실 단순한 이미지가 아니라 지리정보체계를 가진 오염정보를 제공할 방법도 준비도 되어 있지 못한 상황이었다. 본 발표를 통하여, 허베이스피리트호 사고뿐만 아니라, 2011년 6월부터 수개월간 지속된 발해만 오염사고 적용 등 다양한 사례 소개를 하고, 이를 기반으로 해양경찰청에서 업무활용을 위한 방안을 제시한다. 먼저, 해경청의 주요 임무인, 경비, 수색구조, 오염대응 분야별로 현황 분석을 수행하였다. 또한 국외사례에 대한 조사를 한 후, 최종 인공위성 원격탐사기술의 해경청 도입방안에 대한 설계를 실시하였다. 국제적으로 인공위성을 이용한 해양 경비, 수색구조, 오염 모니터링기술 개발이 이루어지고 있으며, 유럽 국가는 시범도입을 진행 중에 있다. 유럽해사안전국(EMSA)은 해양경비 및 수색구조를 위한 선박통항 및 보고 서비스와 오염대비대응(Pollution Preparedness and Response, PPR) 위성 서비스를 회원국에 제공하고 있다. 해양경찰청 임무 수행뿐만 아니라, 해양영토 관리적 측면에서 첨단 위성장비 활용, 선진국형 해상경비 패러다임의 전환 필요성이 크다고 할 수 있다.

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Seasonal Effects Removal of Unsupervised Change Detection based Multitemporal Imagery (다시기 원격탐사자료 기반 무감독 변화탐지의 계절적 영향 제거)

  • Park, Hong Lyun;Choi, Jae Wan;Oh, Jae Hong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.36 no.2
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    • pp.51-58
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    • 2018
  • Recently, various satellite sensors have been developed and it is becoming more convenient to acquire multitemporal satellite images. Therefore, various researches are being actively carried out in the field of utilizing change detection techniques such as disaster and land monitoring using multitemporal satellite images. In particular, researches related to the development of unsupervised change detection techniques capable of extracting rapidly change regions have been conducted. However, there is a disadvantage that false detection occurs due to a spectral difference such as a seasonal change. In order to overcome the disadvantages, this study aimed to reduce the false alarm detection due to seasonal effects using the direction vector generated by applying the $S^2CVA$ (Sequential Spectral Change Vector Analysis) technique, which is one of the unsupervised change detection methods. $S^2CVA$ technique was applied to RapidEye images of the same and different seasons. We analyzed whether the change direction vector of $S^2CVA$ can remove false positives due to seasonal effects. For the quantitative evaluation, the ROC (Receiver Operating Characteristic) curve and the AUC (Area Under Curve) value were calculated for the change detection results and it was confirmed that the change detection performance was improved compared with the change detection method using only the change magnitude vector.

Unsupervised Change Detection for Very High-spatial Resolution Satellite Imagery by Using Object-based IR-MAD Algorithm (객체 기반의 IR-MAD 기법을 활용한 고해상도 위성영상의 무감독 변화탐지)

  • Jaewan, Choi
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.33 no.4
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    • pp.297-304
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    • 2015
  • The change detection algorithms, based on remotely sensed satellite imagery, can be applied to various applications, such as the hazard/disaster analysis and the land monitoring. However, unchanged areas sometimes detected as the changed areas due to various errors in relief displacements and noise pixels, included in the original multi-temporal dataset at the application of unsupervised change detection algorithm. In this research, the object-based changed detection for the high-spatial resolution satellite images is applied by using the IR-MAD (Iteratively Reweighted- Multivariate Alteration Detection), which is one of those representative change detection algorithms. In additionally, we tried to increase the accuracy of change detection results with using the additional information, based on the cross-sharpening method. In the experiment, we used the KOMPSAT-2 satellite sensor, and resulted in the object-based IR-MAD algorithm, representing higher changed detection accuracy than that by the pixel-based IR-MAD. Also, the object-based IR-MAD, focused on cross-sharpened images, increased in accuracy of changed detection, compared to the original object-based IR-MAD. Through these experiments, we could conclude that the land monitoring and the change detection with the high-spatial-resolution satellite imagery can be accomplished efficiency by using the object-based IR-MAD algorithm.

Sensitivity Experiment of Surface Reflectance to Error-inducing Variables Based on the GEMS Satellite Observations (GEMS 위성관측에 기반한 지면반사도 산출 시에 오차 유발 변수에 대한 민감도 실험)

  • Shin, Hee-Woo;Yoo, Jung-Moon
    • Journal of the Korean earth science society
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    • v.39 no.1
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    • pp.53-66
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    • 2018
  • The information of surface reflectance ($R_{sfc}$) is important for the heat balance and the environmental/climate monitoring. The $R_{sfc}$ sensitivity to error-induced variables for the Geostationary Environment Monitoring Spectrometer (GEMS) retrieval from geostationary-orbit satellite observations at 300-500 nm was investigated, utilizing polar-orbit satellite data of the MODerate resolution Imaging Spectroradiometer (MODIS) and Ozone Mapping Instrument (OMI), and the radiative transfer model (RTM) experiment. The variables in this study can be cloud, Rayleigh-scattering, aerosol, ozone and surface type. The cloud detection in high-resolution MODIS pixels ($1km{\times}1km$) was compared with that in GEMS-scale pixels ($8km{\times}7km$). The GEMS detection was consistent (~79%) with the MODIS result. However, the detection probability in partially-cloudy (${\leq}40%$) GEMS pixels decreased due to other effects (i.e., aerosol and surface type). The Rayleigh-scattering effect in RGB images was noticeable over ocean, based on the RTM calculation. The reflectance at top of atmosphere ($R_{toa}$) increased with aerosol amounts in case of $R_{sfc}$<0.2, but decreased in $R_{sfc}{\geq}0.2$. The $R_{sfc}$ errors due to the aerosol increased with wavelength in the UV, but were constant or slightly decreased in the visible. The ozone absorption was most sensitive at 328 nm in the UV region (328-354 nm). The $R_{sfc}$ error was +0.1 because of negative total ozone anomaly (-100 DU) under the condition of $R_{sfc}=0.15$. This study can be useful to estimate $R_{sfc}$ uncertainties in the GEMS retrieval.

Validation of Extreme Rainfall Estimation in an Urban Area derived from Satellite Data : A Case Study on the Heavy Rainfall Event in July, 2011 (위성 자료를 이용한 도시지역 극치강우 모니터링: 2011년 7월 집중호우를 중심으로)

  • Yoon, Sun-Kwon;Park, Kyung-Won;Kim, Jong Pil;Jung, Il-Won
    • Journal of Korea Water Resources Association
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    • v.47 no.4
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    • pp.371-384
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    • 2014
  • This study developed a new algorithm of extreme rainfall extraction based on the Communication, Ocean and Meteorological Satellite (COMS) and the Tropical Rainfall Measurement Mission (TRMM) Satellite image data and evaluated its applicability for the heavy rainfall event in July-2011 in Seoul, South Korea. The power-series-regression-based Z-R relationship was employed for taking into account for empirical relationships between TRMM/PR, TRMM/VIRS, COMS, and Automatic Weather System(AWS) at each elevation. The estimated Z-R relationship ($Z=303R^{0.72}$) agreed well with observation from AWS (correlation coefficient=0.57). The estimated 10-minute rainfall intensities from the COMS satellite using the Z-R relationship generated underestimated rainfall intensities. For a small rainfall event the Z-R relationship tended to overestimated rainfall intensities. However, the overall patterns of estimated rainfall were very comparable with the observed data. The correlation coefficients and the Root Mean Square Error (RMSE) of 10-minute rainfall series from COMS and AWS gave 0.517, and 3.146, respectively. In addition, the averaged error value of the spatial correlation matrix ranged from -0.530 to -0.228, indicating negative correlation. To reduce the error by extreme rainfall estimation using satellite datasets it is required to take into more extreme factors and improve the algorithm through further study. This study showed the potential utility of multi-geostationary satellite data for building up sub-daily rainfall and establishing the real-time flood alert system in ungauged watersheds.

Deterioration Characteristic Analysis for Stone Properties in the Taereung Royal Tomb of the Joseon Dynasty using Nondestructive Analysis (비파괴 분석을 활용한 조선왕릉 태릉 석조물의 손상특성 분석)

  • Lee, Myeonseong;Choie, Myoungju;Lee, Taejong;Chun, Yungun
    • Korean Journal of Heritage: History & Science
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    • v.53 no.2
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    • pp.222-241
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    • 2020
  • The Taereung Royal Tomb from the Joseon Dynasty is the tomb of Empress Munjeong, the second queen of King Jungjong, and it contains various types of stone artifacts. All of these stone artifacts were constructed using coarse- to medium-grained biotite granite. The major types of deterioration of the stone artifacts are identified as surface weathering and biological contaminants. Exfoliation (145 sculptures), granular decomposition (138 sculptures), and repair materials (156 sculptures), along with biological contaminant algae (154 sculptures), lichen (165 sculptures) and moss (97 sculptures), have a high occurrence frequency. In particular, it is deemed that immediate conservation treatment is required, as biological deterioration (algae) represents the most serious condition (grade 3 or higher in 94% of all stones), and it is thought that exfoliation and granulation decomposition are required for long-term conservation management. As a result of equo -tip hardness and ultrasonic measurement, more than 70% of stones were found to have very weak physical properties. Through hyperspectral analysis, organisms were shown to inhabit more than 80% of the surface of burial mound stone artifacts, and P (phosphorus), S (sulfur), Cl (chlorine), and Ca (calcium) were detected in this area. This is because Taereung Royal Tomb has been exposed to the outdoors for hundreds of years and has been weathered by physical, chemical, and biological factors. Therefore, among the stone artifacts in the Taereung Royal Tomb, those with high physical weathering grades are considered to require consolidation to reinforce them physically. Since organisms are highly likely to cause stone damage, they must be removed via dry and wet cleaning. In addition, in order to delay the reoccurrence of organisms following conservation treatment, it is necessary to regularly clean up the soil that has flowed into the burial mound, and to monitor conservation conditions over the long term.

Overview and Prospective of Satellite Chlorophyll-a Concentration Retrieval Algorithms Suitable for Coastal Turbid Sea Waters (연안 혼탁 해수에 적합한 위성 클로로필-a 농도 산출 알고리즘 개관과 전망)

  • Park, Ji-Eun;Park, Kyung-Ae;Lee, Ji-Hyun
    • Journal of the Korean earth science society
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    • v.42 no.3
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    • pp.247-263
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    • 2021
  • Climate change has been accelerating in coastal waters recently; therefore, the importance of coastal environmental monitoring is also increasing. Chlorophyll-a concentration, an important marine variable, in the surface layer of the global ocean has been retrieved for decades through various ocean color satellites and utilized in various research fields. However, the commonly used chlorophyll-a concentration algorithm is only suitable for application in clear water and cannot be applied to turbid waters because significant errors are caused by differences in their distinct components and optical properties. In addition, designing a standard algorithm for coastal waters is difficult because of differences in various optical characteristics depending on the coastal area. To overcome this problem, various algorithms have been developed and used considering the components and the variations in the optical properties of coastal waters with high turbidity. Chlorophyll-a concentration retrieval algorithms can be categorized into empirical algorithms, semi-analytic algorithms, and machine learning algorithms. These algorithms mainly use the blue-green band ratio based on the reflective spectrum of sea water as the basic form. In constrast, algorithms developed for turbid water utilizes the green-red band ratio, the red-near-infrared band ratio, and the inherent optical properties to compensate for the effect of dissolved organisms and suspended sediments in coastal area. Reliable retrieval of satellite chlorophyll-a concentration from turbid waters is essential for monitoring the coastal environment and understanding changes in the marine ecosystem. Therefore, this study summarizes the pre-existing algorithms that have been utilized for monitoring turbid Case 2 water and presents the problems associated with the mornitoring and study of seas around the Korean Peninsula. We also summarize the prospective for future ocean color satellites, which can yield more accurate and diverse results regarding the ecological environment with the development of multi-spectral and hyperspectral sensors.