• Title/Summary/Keyword: ETM method

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Evaluation of a Non-destructive Diagnostic Test for Kudoa septempunctata in Farmed Olive Flounder Paralichthys olivaceus (넙치(Paralichthys olivaceus) 근육 채취 방법에 따른 Kudoa septempunctata 진단 효율 비교)

  • Song, Jun-Young;Jung, Sung Hee;Choi, Hye-Sung
    • Korean Journal of Fisheries and Aquatic Sciences
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    • v.51 no.1
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    • pp.23-30
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    • 2018
  • Kudoa septempunctata, a myxosporean parasite that infects olive flounder Paralichthys olivaceus is known to cause Kudoa food poisoning. Entire trunk muscle (ETM) is used for diagnosis of the parasite in fish and this method demands sacrifice of the host, causing a loss of commercial value. We developed a non-destructive method that uses a plastic syringe-style implanter to draw the sample, called the part-point muscle (PPM) sampling technique. We validated the PPM method in fish infected with K. septempunctata at the level detectable by the ETM method. We confirmed that the PPM method is equally sensitive in comparison to the ETM method for diagnosing K. septempunctata spores in olive flounder muscle. Our study also confirmed that the parasite is uniformly distributed in the dorsal muscle of infected fish. Over a period of 1 month, we observed no mortality of the host fish used for sampling by the PPM method. Thus, our studies demonstrate that the PPM sampling technique is an efficient, non-destructive method for diagnosing K. septempunctata in olive flounder.

Method of Integrating Landsat-5 and Landsat-7 Data to Retrieve Sea Surface Temperature in Coastal Waters on the Basis of Local Empirical Algorithm

  • Xing, Qianguo;Chen, Chu-Qun;Shi, Ping
    • Ocean Science Journal
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    • v.41 no.2
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    • pp.97-104
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    • 2006
  • A useful radiance-converting method was developed to convert the Landsat-7 ETM+thermal-infrared (TIR) band's radiance ($L_{{\lambda},L7/ETM+}$) to that of Landsat-5 TM TIR ($L_{{\lambda},L5/TM+})$ as: $L_{{\lambda},L5/TM}=0.9699{\times}L_{{\lambda},L7/ETM+}+0.1074\;(R^2=1)$. In addition, based on the radiance-converting equation and the linear relation between digital number (DN) and at-satellite radiance, a DN-converting equation can be established to convert DN value of the TIR band between Landsat-5 and Landsat-7. Via this method, it is easy to integrate Landsat-5 and Landsat-7 TIR data to retrieve the sea surface temperature (SST) in coastal waters on the basis of local empirical algorithms in which the radiance or DN of Lansat-5 and 7 TIR band is usually the only input independent variable. The method was employed in a local empirical algorithm in Daya Bay, China, to detect the thermal pollution of cooling water discharge from the Daya Bay nuclear power station (DNPS). This work demonstrates that radiance conversion is an effective approach to integration of Landsat-5 and Landsat-7 data in the process of a SST retrieval which is based on local empirical algorithms.

Burned Area Detection After Wildfire Using Landsat 7 ETM+ SLC-off Images

  • Quoc, Khanh Le;Sy, Tan Nguyen;Nhat, Thanh Nguyen Thi;Thanh, Ha Le
    • IEIE Transactions on Smart Processing and Computing
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    • v.2 no.3
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    • pp.117-129
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    • 2013
  • The increasing demand for monitoring wildfires and their impact on the land surface have prompted studies of burned area extraction and analysis. To differentiate burned and unburned area, the earlier method of the Moderate Resolution Imaging Spectro-radiometer (MODIS) Burned Area Detection Algorithm was proposed to estimate the change in land surface based on the reflectance energy. The energy, whose wavelengths are sensitive to burning, was selected to calculate the change parameter $Z_{score}$. This method was applied using the MODIS images to produce a MODIS Burned Area product. The approach was to simplify this algorithm to make it compatible with the Landsat 7 ETM+ SLC-off images. To extract the refined version of burned regions, post-processing was carried out by applying a median filter, dilation morphology algorithm, and finally a gap filling method. The experimental results showed that the detailed burned areas extracted from the proposed method exhibited more spatial details than those of the MODIS Burned products in the large U.S areas. The results also revealed the discontinuous distribution of burned regions in Vietnam forests.

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The Land Surface Temperature Distributions of Jeju Island using Landsat 7/ETM+ Data

  • Lee Byung-Gul
    • Journal of the Korean earth science society
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    • v.26 no.2
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    • pp.109-113
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    • 2005
  • In this study, the estimation of the temperature distribution of Jeju Island with coastal ocean derived from the thermal band of Landsat 7/ETM+ of January 6, 2003 was carried out. For the computation of the temperature of the island and the coastal ocean based on the thermal band, we used NASA method wiich is the 8 bit Digital Number(DN) converted into spectral radiance. The computed results showed that the land temperature variations were from 0 to 12 Celsius degrees, and a good agreement with the observation ones based on the method. However, the ocean surface temperature was not much changed ground 15 degree since the water was well mixed between the coastal and the offshore ocean. The interesting results were that the temperature distributions of the southern part(Seogwipo City) of Jeju Island were higher than those of the north one(Jeju City) by more than 2 Celsius degree at the same height although the distance between the Jeju and the Seogwipo is only about 35km in winter season. The reason was found that the solar irradiance intensity of the south part was stronger than the north one by Halla mountain in winter season only. From the results, we found that the seasonal variations of solar irradiation and the height of Mt. Halla were an important role of temperature distribution of Jeju Island.

A Machine learning Approach for Knowledge Base Construction Incorporating GIS Data for land Cover Classification of Landsat ETM+ Image (지식 기반 시스템에서 GIS 자료를 활용하기 위한 기계 학습 기법에 관한 연구 - Landsat ETM+ 영상의 토지 피복 분류를 사례로)

  • Kim, Hwa-Hwan;Ku, Cha-Yang
    • Journal of the Korean Geographical Society
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    • v.43 no.5
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    • pp.761-774
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    • 2008
  • Integration of GIS data and human expert knowledge into digital image processing has long been acknowledged as a necessity to improve remote sensing image analysis. We propose inductive machine learning algorithm for GIS data integration and rule-based classification method for land cover classification. Proposed method is tested with a land cover classification of a Landsat ETM+ multispectral image and GIS data layers including elevation, aspect, slope, distance to water bodies, distance to road network, and population density. Decision trees and production rules for land cover classification are generated by C5.0 inductive machine learning algorithm with 350 stratified random point samples. Production rules are used for land cover classification integrated with unsupervised ISODATA classification. Result shows that GIS data layers such as elevation, distance to water bodies and population density can be effectively integrated for rule-based image classification. Intuitive production rules generated by inductive machine learning are easy to understand. Proposed method demonstrates how various GIS data layers can be integrated with remotely sensed imagery in a framework of knowledge base construction to improve land cover classification.

Spatial Distribution Mapping of Cyanobacteria in Daecheong Reservoir Using the Satellite Imagery (위성영상을 이용한 대청호 남조류의 공간 분포 맵핑)

  • Back, Shin Cheol;Park, Jin Ki;Park, Jong Hwa
    • Journal of The Korean Society of Agricultural Engineers
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    • v.58 no.2
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    • pp.53-63
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    • 2016
  • Monitoring of cyanobacteria bloom in reservoir systems is important for water managers responsible of water supply system. Cyanobacteria affect the taste and smell of water and pose considerable filtration problems at water use places. Harmful cyanobacteria bloom in reservoir have significant economic impacts. We develop a new method for estimating the cyanobacteria bloom using Landsat TM and ETM+ data. Developed model was calibrated and cross-validated with existing in situ measurements from Daecheong Reservoir's Water Quality Monitoring Program and Algae Alarm System. Measurements data of three stations taken from 2004 to 2012 were matched with radiometrically converted reflectance data from the Landsat TM and ETM+ sensor. Stepwise multiple linear regression was used to select wavelengths in the Landsat TM and ETM+ bands 1, 2 and 4 that were most significant for predicting cyanobacteria cell number and bio-volume. Based on statistical analysis, the linear models were that included visible band ratios slightly outperformed single band models. The final monitoring models captured the extents of cyanobacteria blooms throughout the 2004-2012 study period. The results serve as an added broad area monitoring tool for water resource managers and present new insight into the initiation and propagation of cyanobacteria blooms in Daecheong reservoir.

Fire Severity Mapping Using a Single Post-Fire Landsat 7 ETM+ Imagery (단일 시기의 Landsat 7 ETM+ 영상을 이용한 산불피해지도 작성)

  • 원강영;임정호
    • Korean Journal of Remote Sensing
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    • v.17 no.1
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    • pp.85-97
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    • 2001
  • The KT(Kauth-Thomas) and IHS(Intensity-Hue-Saturation) transformation techniques were introduced and compared to investigate fire-scarred areas with single post-fire Landsat 7 ETM+ image. This study consists of two parts. First, using only geometrically corrected imagery, it was examined whether or not the different level of fire-damaged areas could be detected by simple slicing method within the image enhanced by the IHS transform. As a result, since the spectral distribution of each class on each IHS component was overlaid, the simple slicing method did not seem appropriate for the delineation of the areas of the different level of fire severity. Second, the image rectified by both radiometrically and topographically was enhanced by the KT transformation and the IHS transformation, respectively. Then, the images were classified by the maximum likelihood method. The cross-validation was performed for the compensation of relatively small set of ground truth data. The results showed that KT transformation produced better accuracy than IHS transformation. In addition, the KT feature spaces and the spectral distribution of IHS components were analyzed on the graph. This study has shown that, as for the detection of the different level of fire severity, the KT transformation reflects the ground physical conditions better than the IHS transformation.

Extended Trigger Modelling for the Workflow Analysis and Design: Case of Telecommunication Company (워크플로 분석/설계를 위한 확장 트리거 모델링: 전화국 사례)

  • Han, Dong-Il;Park, Sei-Kwon
    • IE interfaces
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    • v.9 no.3
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    • pp.236-248
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    • 1996
  • Most of business enterprises today struggle with the coordination of work which is one of the most challenging problems in the business environment. And the situation becomes worse by the increasing complexity and uncertainty. In this paper, suitability of workflow technology for the modelling, optimization, and automation in the complex business structures is discussed. Also, in the abscence of a fully fledged method for analysis and design of workflow systems, this paper proposes a method, ETM(Extended Trigger Modelling), which can solve several problems in other methods. The proposed ETM approach consists of three stages such as situation analysis stage, activity coordination stage and implementation preparation stage. A modelling case of the proposed procedure is also presented.

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Analysis on Urban Sprawl and Landcover Change Using TM, ETM+ and GIS

  • Xiao, Jieying;Ryutaro, Tateishi;Shen, Yanjun;Ge, Jingfeng;Liang, Yanqing;Chang, Chunping
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.978-980
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    • 2003
  • This study explores the temporal and spatial features near 67years (1934 ?2001) and landcover change in last 14 years (1987-2001) in Shijiazhuang, China, based on 67-year time series data edited from historical maps, TM and ETM+ imageries by integrating GIS and remote sensing method. An index named Annual Growth Rate (AGR) is used to analyze the spatial features of urban sprawl, and Maximum Likelihood classification method is utilized to detect the land cover types change. At last, the relationship between urbanization and factors is analyzed.

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Application of the Landsat TM/ETM+, KOMPSAT EOC, and IKONOS to Study the Sedimentary Environments in the Tidal Flats of Kanghwa and Hwang-Do, Korea

  • Ryu Joo-Hyung;Lee Yoon-Kyung;Yoo Hong-Rhyong;Park Chan-Hong
    • Proceedings of the KSRS Conference
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    • 2004.10a
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    • pp.140-143
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    • 2004
  • The west coast of the Korean Peninsula is famous for its large tidal range (up to 9 m) and vast tidal flats. With comparison the sedimentary environments of open and close tidal flat using remote sensing, we select Kanghwa tidal flat and Hwang-Do tidal flat in Cheonsu Bay. Prior to surface sediment discrimination using remote sensing, sedimentary environments including intertidal OEM, hydraulic condition, and relationship between grain size and various tidal condition are investigated. Remote sensing has the potential to provide synoptic information of intertidal environments. The objectives of this study are: (i) to generate an intertidal digital elevation model (OEM) using the waterline method of Lansat TM/ETM+, (ii) to investigate the tidal channel distribution using texture analysis, and (iii) to analyze the relationship between surface grain size by using in-situ data and intertidal OEM and tidal channel density by using high-resolution satellite data such as IKONOS and Kompsat EOC. The results demonstrate that satellite remote sensing is an efficient and effective tool for a surface sediment discrimination and long term morphologic change estimation in tidal flats.

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