• Title/Summary/Keyword: Sensing Region

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Detection of low frequency tonal signal of underwater radiated noise via compressive sensing (압축센싱 기법을 적용한 선박 수중 방사 소음 신호의 저주파 토널 탐지)

  • Kim, Jinhong;Shim, Byonghyo;Ahn, Jae-Kyun;Kim, Seongil;Hong, Wooyoung
    • The Journal of the Acoustical Society of Korea
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    • v.37 no.1
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    • pp.39-45
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    • 2018
  • Compressive sensing allows recovering an original signal which has a small dimension of the signal compared to the dimension of the entire signal in a short period of time through a small number of observations. In this paper, we proposed a method for detecting tonal signal which caused by the machinery component of a vessel such as an engine, gearbox, and support elements. The tonal signal can be modeled as the sparse signal in the frequency domain when it compares to whole spectrum range. Thus, the target tonal signal can be estimated by S-OMP (Simultaneous-Orthogonal Matching Pursuit) which is one of the sparse signal recovery algorithms. In simulation section, we showed that S-OMP algorithm estimated more precise frequencies than the conventional FFT (Fast Fourier Transform) thresholding algorithm in low SNR (Signal to Noise Ratio) region.

STATUS OF GOCI DATA PROCESSING SYSTEM(GDPS) DEVELOPMENT

  • Han, Hee-Jeong;Ahn, Yu-Hwan;Ryu, Joo-Hyung
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.159-161
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    • 2007
  • Geostationary Ocean Color Imager (GOCI), the world-first ocean remote sensing instrument on geostationary Communication, Ocean, Meteorological Satellite (COMS), will be able to take a picture of a large region several times a day (almost with every one hour interval). We, KORDI, are in charge for developing the GOCI data processing system (GDPS) which is the basic software for processing the data from GOCI. The GDPS will be based on windows operating system to produce the GOCI level 2 data products (useful for oceanographic environmental analysis) automatically in real-time mode. Also, the GDPS will be a user-interactive program by well-organized graphical user interfaces for data processing and visualization. Its products will be the chlorophyll concentration, amount of total suspended sediments (TSS), colored dissolved organic matters (CDOM) and red tide from water leaving radiance or remote sensing reflectance. In addition, the GDPS will be able to produce daily products such as water current vector, primary productivity, water quality categorization, vegetation index, using individual observation data composed from several subscenes provided by GOCI for each slit within the target area. The resulting GOCI level 2 data will be disseminated through LRIT using satellite dissemination system and through online request and download systems. This software is carefully designed and implemented, and will be tested by sub-contractual company until the end of this year. It will need to be updated in effect with respect to new/improved algorithms and the calibration/validation activities.

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Application of Linear Spectral Mixture Analysis to Geological Thematic Mapping using LANDSAT 7 ETM+ and ASTER Satellite Imageries (LANDSAT 7 ETM+와 ASTER영상정보를 이용한 선형분광혼합분석 기법의 지질주제도 작성 응용)

  • Kim Seung Tae;Lee Kiwon
    • Korean Journal of Remote Sensing
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    • v.20 no.6
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    • pp.369-382
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    • 2004
  • The purpose of this study is the investigation of applicability of LSMA(Linear Spectral Mixture Analysis) on the geological uses with different radiometric and spatial types of sensor images such as Terra ASTER and LANDSAT 7 ETM+. As for the actual application case, geologic mapping for mineral exploration using ASTER and ETM+ at the Mongolian plateau region was carried out. After the pre-processing such as the geometric corrections and calibration of radiance, 7 endmembers, as spectral classes for geologic rock types, related to spectral signature deviation for the given application was determined by the pre-surveyed geological mapping information and the correlation matrix analysis, and total 20 images of ASTER and ETM+ were used to LSMA processing. As the results, fraction maps showing individual mineral types in the study area are presented. It concluded that this approach based on LSMA using ETM+ and ASTER is regarded as one of the effective schemes for geologic remote sensing.

Long-term shape sensing of bridge girders using automated ROI extraction of LiDAR point clouds

  • Ganesh Kolappan Geetha;Sahyeon Lee;Junhwa Lee;Sung-Han Sim
    • Smart Structures and Systems
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    • v.33 no.6
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    • pp.399-414
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    • 2024
  • This study discusses the long-term deformation monitoring and shape sensing of bridge girder surfaces with an automated extraction scheme for point clouds in the Region Of Interest (ROI), invariant to the position of a Light Detection And Ranging system (LiDAR). Advanced smart construction necessitates continuous monitoring of the deformation and shape of bridge girders during the construction phase. An automated scheme is proposed for reconstructing geometric model of ROI in the presence of noisy non-stationary background. The proposed scheme involves (i) denoising irrelevant background point clouds using dimensions from the design model, (ii) extracting the outer boundaries of the bridge girder by transforming and processing the point cloud data in a two-dimensional image space, (iii) extracting topology of pre-defined targets using the modified Otsu method, (iv) registering the point clouds to a common reference frame or design coordinate using extracted predefined targets placed outside ROI, and (v) defining the bounding box in the point clouds using corresponding dimensional information of the bridge girder and abutments from the design model. The surface-fitted reconstructed geometric model in the ROI is superposed consistently over a long period to monitor bridge shape and derive deflection during the construction phase, which is highly correlated. The proposed scheme of combining 2D-3D with the design model overcomes the sensitivity of 3D point cloud registration to initial match, which often leads to a local extremum.

A Feasibility Study on the Application of TVDI on Accessing Wildfire Danger in the Korean Peninsula (한반도 지역 산불 발생 위험도 예측에 TVDI 적용 가능성 고찰)

  • Kim, Kwang Nyun;Kim, Seung Hee;Won, Myoung Soo;Jang, Keun Chang;Choi, Won Jun;Lee, Yun Gon
    • Korean Journal of Remote Sensing
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    • v.35 no.6_3
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    • pp.1197-1208
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    • 2019
  • Wildfire is a major natural disaster affecting socioeconomics and ecology. Remote sensing data have been widely used to estimate the wildfire danger with an advantage of higher spatial resolution. Among the several wildfire related indices using remote sensing data, Temperature Vegetation Dryness Index (TVDI) assesses wildfire danger based on both Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST). Although TVDI has physical advantages by considering both weather and vegetation condition, previous studies have shown TVDI does not performed well compare to other wildfire related indices over the Korean Peninsula. In this study we have attempted multiple modification to improve TVDI performance over the study region. In-situ measured air temperature was employed to increase accuracy, regression line was generated using monthly data to include seasonal effect, and TVDI was calculated at each province level to consider vegetation type and local climate. The modified TVDI calculation method was evaluated in wildfire cases and showed significant improvement in wildfire danger estimation.

Change Detection of Land Cover Environment using Fuzzy Logic Operation : A Case Study of Anmyeon-do (퍼지논리연산을 이용한 토지피복환경 변화분석: 안면도 사례연구)

  • 장동호;지광훈;이현영
    • Korean Journal of Remote Sensing
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    • v.18 no.6
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    • pp.305-317
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    • 2002
  • The purpose of this study is to analyze the land cover environmental changes in the Anmyeon-do. Especially, it centers on the changes in the land cover environment through methods of GIS and remote sensing. The land cover environmental change areas were detected from remote sensing data, and geographic data sets related to land cover environment change were built as a spatial database in GIS. Fuzzy logic was applied for data representation and integration of thematic maps. In the natural, social, and economic environment variables, the altitude, population density, and the national land use planning showed higher fuzzy membership values, respectively. After integrating all thematic maps using fuzzy logic operation, it is possible to predict the change quantitatively. In the study area, a region where land cover change will be likely to occur is the one on a plain near the shoreline. In particular, the hills of less than 5% slope and less than 15m altitude, adjacent to the ocean, were quite vulnerable to the aggravation of coastal environment on account of current, large-scale development. In conclusions, it is expected that the generalized scheme used in this study is regarded as one of effective methodologies for land cover environmental change detection from geographic data.

Cloud-cell Tracking Analysis using Satellite Image of Extreme Heavy Snowfall in the Yeongdong Region (영동지역의 극한 대설에 대한 위성관측으로부터 구름 추적)

  • Cho, Young-Jun;Kwon, Tae-Yong
    • Korean Journal of Remote Sensing
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    • v.30 no.1
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    • pp.83-107
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    • 2014
  • This study presents spatial characteristics of cloud using satellite image in the extreme heavy snowfall of the Yeongdong region. 3 extreme heavy snowfall events in the Yeongdong region during the recent 12 years (2001 ~ 2012) are selected for which the fresh snow cover exceed 50 cm/day. Spatial characteristics (minimum brightness temperature; Tmin, cloud size, center of cloud-cell) of cloud are analyzed by tracking main cloud-cell related with these events. These characteristics are compared with radar precipitation in the Yeongdong region to investigate relationship between cloud and precipitation. The results are summarized as follows, selected extreme heavy snowfall events are associated with the isolated, well-developed, and small-scale convective cloud which is developing over the Yeongdong region or moving from over East Korea Bay to the Yeongdong region. During the period of main precipitation, cloud-cell Tmin is low ($-40{\sim}-50^{\circ}C$) and cloud area is small (17,000 ~ 40,000 $km^2$). Precipitation area (${\geq}$ 0.5 mm/hr) from radar also shows small and isolated shape (4,000 ~ 8,000 $km^2$). The locations of the cloud and precipitation are similar, but in there centers are located closely to the coast of the Yeongdong region. In all events the extreme heavy snowfall occur in the period a developed cloud-cell was moving into the coastal waters of the Yeongdong. However, it was found that developing stage of cloud and precipitation are not well matched each other in one of 3 events. Water vapor image shows that cloud-cell is developed on the northern edge of the dry(dark) region. Therefore, at the result analyzed from cloud and precipitation, selected extreme heavy snowfall events are associated with small-scale secondary cyclone or vortex, not explosive polar low. Detection and tracking small-scale cloud-cell in the real-time forecasting of the Yeongdong extreme heavy snowfall is important.

Improvement of MODIS land cover classification over the Asia-Oceania region (아시아-오세아니아 지역의 MODIS 지면피복분류 개선)

  • Park, Ji-Yeol;Suh, Myoung-Seok
    • Korean Journal of Remote Sensing
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    • v.31 no.2
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    • pp.51-64
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    • 2015
  • We improved the MODerate resolution Imaging Spectroradiometer (MODIS) land cover map over the Asia-Oceania region through the reclassification of the misclassified pixels. The misclassified pixels are defined where the number of land cover types are greater than 3 from the 12 years of MODIS land cover map. The ratio of misclassified pixels in this region amounts to 17.53%. The MODIS Normalized Difference Vegetation Index (NDVI) time series over the correctly classified pixels showed that continuous variation with time without noises. However, there are so many unreasonable fluctuations in the NDVI time series for the misclassified pixels. To improve the quality of input data for the reclassification, we corrected the MODIS NDVI using Correction based on Spatial and Temporal Continuity (CSaTC) developed by Cho and Suh (2013). Iterative Self-Organizing Data Analysis (ISODATA) was used for the clustering of NDVI data over the misclassified pixels and land cover types was determined based on the seasonal variation pattern of NDVI. The final land cover map was generated through the merging of correctly classified MODIS land cover map and reclassified land cover map. The validation results using the 138 ground truth data showed that the overall accuracy of classification is improved from 68% of original MODIS land cover map to 74% of reclassified land cover map.

A LuxR-type Transcriptional Regulator, PsyR, Coordinates Regulation of Pathogenesis-related Genes in Pseudomonas syringae pv. tabaci (Pseudomonas syringae pv. tabaci 에서 LuxR-type 전사조절자인 PsyR에 의한 병원성 유전자들의 조절)

  • Choi, Yeon Hee;Lee, Jun Seung;Yun, Sora;Baik, Hyung Suk
    • Journal of Life Science
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    • v.25 no.2
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    • pp.136-150
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    • 2015
  • Pseudomonas syringae pathovar tabaci is a plant pathogenic bacterium that causes wildfire disease in tobacco plants. In P. syringae pv. tabaci, PsyI, a LuxI-type protein, acts as an AHL synthase, while primary and secondary sequence analysis of PsyR has revealed that it is a homolog of the LuxR-type transcriptional regulator that responds to AHL molecules. In this study, using phenotypic and genetic analyses in P. syringae pv. tabaci, we show the effect of PsyR protein as a quorum-sensing (QS) transcriptional regulator. Regulatory effects of PsyR on swarming motility and production of siderophores, tabtoxin, and N-acyl homoserine lactones were examined via phenotypic assays, and confirmed by quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR). Further qRT-PCR showed that PsyR regulates expression of these virulence genes in response to environmental signals. However, an upstream region of the gene was not bound with purified MBP-PsyR protein; rather, PsyR was only able to shift the upstream region of psyI. These results suggested that PsyR may be indirectly controlled via intermediate-regulatory systems and that auto-regulation by PsyR does not occur.

Speckle Noise Removal by Rank-ordered Differences Diffusion Filter (순위 차 확산 필터를 이용한 스페클 잡음 제거)

  • Ye, Chul-Soo
    • Korean Journal of Remote Sensing
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    • v.25 no.1
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    • pp.21-30
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    • 2009
  • The purposes of this paper are to present a selection method of neighboring pixels whose local statistics are similar to the center pixel and combine the selection result with mean curvature diffusion filter to reduce noises in remote sensed imagery. The order of selection of neighboring pixels is critical, especially for finding a pixel belonging to the homogeneous region, since the statistics of the homogeneous region vary according to the selection order. An effective strategy for selecting neighboring pixels, which uses rank-order differences vector obtained by computing the intensity differences between the center pixel and neighboring pixels and arranging them in ascending order, is proposed in this paper. By using region growing method, we divide the elements of the rank-ordered differences vector into two groups, homogeneous rank-ordered differences vector and outlier rank-ordered differences vector. The mean curvature diffusion filter is combined with a line process, which chooses selectively diffusion coefficient of the neighboring pixels belonging into homogeneous rank-ordered differences vector. Experimental results using an aerial image and a TerraSAR-X satellite image showed that the proposed method reduced more efficiently noises than some conventional adaptive filters using all neighboring pixels in updating the center pixel.