• Title/Summary/Keyword: 변화탐지

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Combining Conditional Generative Adversarial Network and Regression-based Calibration for Cloud Removal of Optical Imagery (광학 영상의 구름 제거를 위한 조건부 생성적 적대 신경망과 회귀 기반 보정의 결합)

  • Kwak, Geun-Ho;Park, Soyeon;Park, No-Wook
    • Korean Journal of Remote Sensing
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    • v.38 no.6_1
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    • pp.1357-1369
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    • 2022
  • Cloud removal is an essential image processing step for any task requiring time-series optical images, such as vegetation monitoring and change detection. This paper presents a two-stage cloud removal method that combines conditional generative adversarial networks (cGANs) with regression-based calibration to construct a cloud-free time-series optical image set. In the first stage, the cGANs generate initial prediction results using quantitative relationships between optical and synthetic aperture radar images. In the second stage, the relationships between the predicted results and the actual values in non-cloud areas are first quantified via random forest-based regression modeling and then used to calibrate the cGAN-based prediction results. The potential of the proposed method was evaluated from a cloud removal experiment using Sentinel-2 and COSMO-SkyMed images in the rice field cultivation area of Gimje. The cGAN model could effectively predict the reflectance values in the cloud-contaminated rice fields where severe changes in physical surface conditions happened. Moreover, the regression-based calibration in the second stage could improve the prediction accuracy, compared with a regression-based cloud removal method using a supplementary image that is temporally distant from the target image. These experimental results indicate that the proposed method can be effectively applied to restore cloud-contaminated areas when cloud-free optical images are unavailable for environmental monitoring.

Evaluation on Watershed Natural Habitat Assessment for Conservation of Brachymystax lenok tsinlingensis in Naerin Upstream (내린천 상류 유역 열목어(Brachymystax lenok tslingensis) 서식지 자연성 평가)

  • Jeong Eun Kim;Hwang Goo Lee
    • Ecology and Resilient Infrastructure
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    • v.10 no.3
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    • pp.73-84
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    • 2023
  • The objective of this study was to evaluate biodiversity and natural habitat environment of freshwater ecosystem. Our aim was therefore to produce a set of biodiversity and habitat indicators based on multi-parameters of water quality and biodiversity by analyzing the characteristics of the results by indicators. We selected four indicators a) anthropogenic disturbance, b) habitat diversity, c) biodiversity, d) ecosystem structure. The fishes cohabiting with Brachymystax lenok tsinlingensis were Rhynchocypris kumgangensis and Zacco koreanus. As a result of the anthropogenic disturbance evaluation, it was analyzed that vegetation embankment showed a more stable environment in the tributary than the main stream, and other disturbance was not confirmed As a result of the habitat diversity evaluation, it was analyzed that habitat evaluation index showed a high score of 200 more on average, showing an optimal habitat condition. As a result of the biodiversity evaluation, it was analyzed as a clean habitat condition with a high proportion of sensitive species, abundant dissolved oxygen, and little pollutants. As a results of the ecosystem structure, the ecological health condition metrics and appearance of endangered species showed large score deviation, but it was analyzed that the stream ecosystem health was generally excellent. There was a slight correlation between the habitat environment and the results of the nature habitat evaluation according to the appearance of the B. lenok tsinlingensis.

P-Impedance Inversion in the Shallow Sediment of the Korea Strait by Integrating Core Laboratory Data and the Seismic Section (심부 시추코어 실험실 분석자료와 탄성파 탐사자료 통합 분석을 통한 대한해협 천부 퇴적층 임피던스 도출)

  • Snons Cheong;Gwang Soo Lee;Woohyun Son;Gil Young Kim;Dong Geun Yoo;Yunseok Choi
    • Geophysics and Geophysical Exploration
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    • v.26 no.3
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    • pp.138-149
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    • 2023
  • In geoscience and engineering the geological characteristics of sediment strata is crucial and possible if reliable borehole logging and seismic data are available. To investigate the characteristics of the shallow strata in the Korea Strait, laboratory sonic logs were obtained from deep borehole data and seismic section. In this study, we integrated and analyzed the sonic log data obtained from the drilling core (down to a depth of 200 m below the seabed) and multichannel seismic section. The correlation value was increased from 15% to 45% through time-depth conversion. An initial model of P-wave impedance was set, and the results were compared by performing model-based, band-limited, and sparse-spike inversions. The derived P-impedance distributions exhibited differences between sediment-dominant and unconsolidated layers. The P-impedance inversion process can be used as a framework for an integrated analysis of additional core logs and seismic data in the future. Furthermore, the derived P-impedance can be used to detect shallow gas-saturated regions or faults in the shallow sediment. As domestic deep drilling is being performed continuously for identifying the characteristics of carbon dioxide storage candidates and evaluating resources, the applicability of the integrated inversion will increase in the future.

Study on Establishment of a Monitoring System for Long-term Behavior of Caisson Quay Wall (케이슨 안벽의 장기 거동 모니터링 시스템 구축 연구 )

  • Tae-Min Lee;Sung Tae Kim;Young-Taek Kim;Jiyoung Min
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.27 no.5
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    • pp.40-48
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    • 2023
  • In this paper, a sensor-based monitoring system was established to analyze the long-term behavioral characteristics of the caisson quay wall, a representative structural type in port facilities. Data was collected over a period of approximately 10 months. Based on existing literature, anomalous behaviors of port facilities were classified, and a measurement system was selected to detect them. Monitoring systems were installed on-site to periodically collect data. The collected data was transmitted and stored on a server through LTE network. Considering the site conditions, inclinometers for measuring slope and crack meters for measuring spacing and settlement were installed. They were attached to two caissons for comparison between different caissons. The correlation among measured data, temperature, and tidal level was examined. The temperature dominated the spacing and settlement data. When the temperature changed by approximately 50 degrees, the spacing changed by 10 mm, the settlement by 2 mm, and the slope by 0.1 degrees. On the other hand, there was no clear relationship with tidal level, indicating a need for more in-depth analysis in the future. Based on the characteristics of these collected database, it will be possible to develop algorithms for detecting abnormal states in gravity-type quay walls. The acquisition and analysis of long-term data enable to evaluate the safety and usability of structures in the event of disasters and emergencies.

Trend and future prospect on the development of technology for electronic security system (기계경비시스템의 기술 변화추세와 개발전망)

  • Chung, Tae-Hwang;So, Sung-Young
    • Korean Security Journal
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    • no.19
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    • pp.225-244
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    • 2009
  • Electronic security system is composed mainly of electronic-information-communication device, so system technology, configuration and management of the electronic security system could be affected by the change of information-communication environment. This study is to propose the future prospect on the development of technique for electronic security system through the analysis of the trend and the actual condition on the development of technique. This study is based on literature study and interview with user and provider of electronic security system, also survey was carried out by system provider and members of security integration company to come up with more practical result. Hybrid DVR technology that has multi-function such as motion detection, target tracking and image identification is expected to be developed. And 'Embedded IP camera' technology that internet server and image identification software are built in. Those technologies could change the configuration and management of CCTV system. Fingerprint identification technology and face identification technology are continually developed to get more reliability, but continual development of surveillance and three-dimension identification technology for more efficient face identification system is needed. As radio identification and tracking function of RFID is appreciated as very useful for access control system, hardware and software of RFID technology is expected to be developed, but government's support for market revitalization is necessary. Behavior pattern identification sensor technology is expected to be developed and could replace passive infrared sensor that cause system error, giving security guard firm confidence for response. The principle of behavior pattern identification is similar to image identification, so those two technology could be integrated with tracking technology and radio identification technology of RFID for total monitoring system. For more efficient electronic security system, middle-ware's role is very important to integrate the technology of electronic security system, this could make possible of installing the integrated security system.

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Statistical Characteristics of East Sea Mesoscale Eddies Detected, Tracked, and Grouped Using Satellite Altimeter Data from 1993 to 2017 (인공위성 고도계 자료(1993-2017년)를 이용하여 탐지‧추적‧분류한 동해 중규모 소용돌이의 통계적 특성)

  • LEE, KYUNGJAE;NAM, SUNGHYUN;KIM, YOUNG-GYU
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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    • v.24 no.2
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    • pp.267-281
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    • 2019
  • Energetic mesoscale eddies in the East Sea (ES) associated with strong mesoscale variability impacting circulation and environments were statistically characterized by analyzing satellite altimeter data collected during 1993-2017 and in-situ data obtained from four cruises conducted between 2015 and 2017. A total of 1,008 mesoscale eddies were detected, tracked, and identified and then classified into 27 groups characterized by mean lifetime (L, day), amplitude (H, m), radius (R, km), intensity per unit area (EI, $cm^2/s^2/km^2$), ellipticity (e), eddy kinetic energy (EKE, TJ), available potential energy (APE, TJ), and direction of movement. The center, boundary, and amplitude of mesoscale eddies identified from satellite altimeter data were compared to those from the in-situ observational data for the four cases, yielding uncertainties in the center position of 2-10 km, boundary position of 10-20 km, and amplitude of 0.6-5.9 cm. The mean L, H, R, EI, e, EKE, and APE of the ES mesoscale eddies during the total period are $95{\pm}104$ days, $3.5{\pm}1.5cm$, $39{\pm}6km$, $0.023{\pm}0.017cm^2/s^2/km^2$, $0.72{\pm}0.07$, $23{\pm}21TJ$, and $588{\pm}250TJ$, respectively. The ES mesoscale eddies tend to move following the mean surface current rather than propagating westward. The southern groups (south of the subpolar front) have a longer L, larger H, R, and higher EKE, APE; and stronger EI than those of the northern groups and tend to move a longer distance following surface currents. There are exceptions to the average characteristics, such as the quasi-stationary groups (the Wonsan Warm, Wonsan Cold, Western Japan Basin Warm, and Northern Subpolar Frontal Cold Eddy groups) and short-lived groups with a relatively larger H, higher EKE, and APE and stronger EI (the Yamato Coastal Warm, Central Yamato Warm, and Eastern Japan Basin Coastal Warm eddy groups). Small eddies in the northern ES hardly resolved using the satellite altimetry data only, were not identified here and discussed with potential over-estimations of the mean L, H, R, EI, EKE, and APE. This study suggests that the ES mesoscale eddies 1) include newly identified groups such as the Hokkaido and the Yamato Rise Warm Eddies in addition to relatively well-known groups (e.g., the Ulleung Warm and the Dok Cold Eddies); 2) have a shorter L; smaller H, R, and lower EKE; and stronger EI and higher APE than those of the global ocean, and move following surface currents rather than propagating westward; and 3) show large spatial inhomogeneity among groups.

Wildfire Severity Mapping Using Sentinel Satellite Data Based on Machine Learning Approaches (Sentinel 위성영상과 기계학습을 이용한 국내산불 피해강도 탐지)

  • Sim, Seongmun;Kim, Woohyeok;Lee, Jaese;Kang, Yoojin;Im, Jungho;Kwon, Chunguen;Kim, Sungyong
    • Korean Journal of Remote Sensing
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    • v.36 no.5_3
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    • pp.1109-1123
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    • 2020
  • In South Korea with forest as a major land cover class (over 60% of the country), many wildfires occur every year. Wildfires weaken the shear strength of the soil, forming a layer of soil that is vulnerable to landslides. It is important to identify the severity of a wildfire as well as the burned area to sustainably manage the forest. Although satellite remote sensing has been widely used to map wildfire severity, it is often difficult to determine the severity using only the temporal change of satellite-derived indices such as Normalized Difference Vegetation Index (NDVI) and Normalized Burn Ratio (NBR). In this study, we proposed an approach for determining wildfire severity based on machine learning through the synergistic use of Sentinel-1A Synthetic Aperture Radar-C data and Sentinel-2A Multi Spectral Instrument data. Three wildfire cases-Samcheok in May 2017, Gangreung·Donghae in April 2019, and Gosung·Sokcho in April 2019-were used for developing wildfire severity mapping models with three machine learning algorithms (i.e., Random Forest, Logistic Regression, and Support Vector Machine). The results showed that the random forest model yielded the best performance, resulting in an overall accuracy of 82.3%. The cross-site validation to examine the spatiotemporal transferability of the machine learning models showed that the models were highly sensitive to temporal differences between the training and validation sites, especially in the early growing season. This implies that a more robust model with high spatiotemporal transferability can be developed when more wildfire cases with different seasons and areas are added in the future.

Automatic Detection of Stage 1 Sleep (자동 분석을 이용한 1단계 수면탐지)

  • 신홍범;한종희;정도언;박광석
    • Journal of Biomedical Engineering Research
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    • v.25 no.1
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    • pp.11-19
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    • 2004
  • Stage 1 sleep provides important information regarding interpretation of nocturnal polysomnography, particularly sleep onset. It is a short transition period from wakeful consciousness to sleep. Lack of prominent sleep events characterizing stage 1 sleep is a major obstacle in automatic sleep stage scoring. In this study, we attempted to utilize simultaneous EEC and EOG processing and analyses to detect stage 1 sleep automatically. Relative powers of the alpha waves and the theta waves were calculated from spectral estimation. Either the relative power of alpha waves less than 50% or the relative power of theta waves more than 23% was regarded as stage 1 sleep. SEM (slow eye movement) was defined as the duration of both eye movement ranging from 1.5 to 4 seconds and regarded also as stage 1 sleep. If one of these three criteria was met, the epoch was regarded as stage 1 sleep. Results f ere compared to the manual rating results done by two polysomnography experts. Total of 169 epochs was analyzed. Agreement rate for stage 1 sleep between automatic detection and manual scoring was 79.3% and Cohen's Kappa was 0.586 (p<0.01). A significant portion (32%) of automatically detected stage 1 sleep included SEM. Generally, digitally-scored sleep s1aging shows the accuracy up to 70%. Considering potential difficulties in stage 1 sleep scoring, the accuracy of 79.3% in this study seems to be robust enough. Simultaneous analysis of EOG provides differential value to the present study from previous oneswhich mainly depended on EEG analysis. The issue of close relationship between SEM and stage 1 sleep raised by Kinnariet at. remains to be a valid one in this study.

An Analysis on the Usability of Unmanned Aerial Vehicle(UAV) Image to Identify Water Quality Characteristics in Agricultural Streams (농업지역 소하천의 수질 특성 파악을 위한 UAV 영상 활용 가능성 분석)

  • Kim, Seoung-Hyeon;Moon, Byung-Hyun;Song, Bong-Geun;Park, Kyung-Hun
    • Journal of the Korean Association of Geographic Information Studies
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    • v.22 no.3
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    • pp.10-20
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    • 2019
  • Irregular rainfall caused by climate change, in combination with non-point pollution, can cause water systems worldwide to suffer from frequent eutrophication and algal blooms. This type of water pollution is more common in agricultural prone to water system inflow of non-point pollution. Therefore, in this study, the correlation between Unmanned Aerial Vehicle(UAV) multi-spectral images and total phosphorus, total nitrogen, and chlorophyll-a with indirect association of algal blooms, was analyzed to identify the usability of UAV image to identify water quality characteristics in agricultural streams. The analysis the vegetation index Normalized Differences Index (NDVI), the Normalized Differences Red Edge(NDRE), and the Chlorophyll Index Red Edge(CIRE) for the detection of multi-spectral images and algal blooms collected from the target regions Yang cheon and Hamyang Wicheon. The analysis of the correlation between image values and water quality analysis values for the water sampling points, total phosphorus at a significance level of 0.05 was correlated with the CIRE(0.66), and chlorophyll-a showed correlation with Blue(-0.67), Green(-0.66), NDVI(0.75), NDRE (0.67), CIRE(0.74). Total nitrogen was correlated with the Red(-0.64), Red edge (-0.64) and Near-Infrared Ray(NIR)(-0.72) wavelength at the significance level of 0.05. The results of this study confirmed a significant correlations between multi-spectral images collected through UAV and the factors responsible for water pollution, In the case of the vegetation index used for the detection of algal bloom, the possibility of identification of not only chlorophyll-a but also total phosphorus was confirmed. This data will be used as a meaningful data for counterplan such as selecting non-point pollution apprehensive area in agricultural area.

Convergence of Remote Sensing and Digital Geospatial Information for Monitoring Unmeasured Reservoirs (미계측 저수지 수체 모니터링을 위한 원격탐사 및 디지털 공간정보 융합)

  • Hee-Jin Lee;Chanyang Sur;Jeongho Cho;Won-Ho Nam
    • Korean Journal of Remote Sensing
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    • v.39 no.5_4
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    • pp.1135-1144
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    • 2023
  • Many agricultural reservoirs in South Korea, constructed before 1970, have become aging facilities. The majority of small-scale reservoirs lack measurement systems to ascertain basic specifications and water levels, classifying them as unmeasured reservoirs. Furthermore, continuous sedimentation within the reservoirs and industrial development-induced water quality deterioration lead to reduced water supply capacity and changes in reservoir morphology. This study utilized Light Detection And Ranging (LiDAR) sensors, which provide elevation information and allow for the characterization of surface features, to construct high-resolution Digital Surface Model (DSM) and Digital Elevation Model (DEM) data of reservoir facilities. Additionally, bathymetric measurements based on multibeam echosounders were conducted to propose an updated approach for determining reservoir capacity. Drone-based LiDAR was employed to generate DSM and DEM data with a spatial resolution of 50 cm, enabling the display of elevations of hydraulic structures, such as embankments, spillways, and intake channels. Furthermore, using drone-based hyperspectral imagery, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) were calculated to detect water bodies and verify differences from existing reservoir boundaries. The constructed high-resolution DEM data were integrated with bathymetric measurements to create underwater contour maps, which were used to generate a Triangulated Irregular Network (TIN). The TIN was utilized to calculate the inundation area and volume of the reservoir, yielding results highly consistent with basic specifications. Considering areas that were not surveyed due to underwater vegetation, it is anticipated that this data will be valuable for future updates of reservoir capacity information.