• Title/Summary/Keyword: Landsat TM data

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Detection of Thermal Plume Signature in and around the Younggwang coastal waters of Korea using LANDSAT & NOAA Thermal Infrared Data

  • Ahn, Yu-Hwan;Shanmugam, P.;Lee, Jae-Hak;Kang, Yong Q.
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.869-872
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    • 2003
  • The thermal contamination of the Younggwang coastal marine ecosystem has been investigated using space borne thermal infrared data acquired over the period 1985-2003 by the Landsat and NOAA satellites. The analysis of AVHRR data brought out the general pattern and extension of thermal plume while TM data yielded more accurate information about the plume shape, dimension, dispersion direction etc. The examination of sea surface temperature (SST) computed from these images clearly indicates that the thermal plume extends 70 to100km southward during summer and 50 to70km northwestward during winter monsoons. The maximum plume temperature was 29$^{\circ}C$ in summer and 12$^{\circ}C$ in winter. The comparative analysis shows that the temperature retrieved from TM is slightly higher (1.8$^{\circ}C$, 3$^{\circ}C$ and 2.2$^{\circ}C$ for the images of 98/11/10, 99/05/05 and 99/05/21 respectively) than those derived from AVHRR data. The correlation coefficient between the TM-derived SST and AVHRR-derived SST was 0.72.

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Estimation of Rice-Planted Area using Landsat TM Imagery in Dangjin-gun area (Landsat TM 화상을 이용한 당진군 일원의 논면적 추정)

  • 홍석영;임상규;이규성;조인상;김길웅
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.3 no.1
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    • pp.5-15
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    • 2001
  • For estimating paddy field area with Landsat TM images, two dates, May 31, 1991 (transplanting stage) and August 19, 1991 (heading stage) were selected by the data analysis of digital numbers considering rice cropping calendar. Four different estimating methods (1) rule-based classification method, (2) supervised classification(maximum likelihood), (3) unsupervised classification (ISODATA, No. of class:15), (4) unsupervised classification (ISODATA, No. of class:20) were examined. Paddy field area was estimated to 7291.19 ha by non-classification method. In comparison with topographical map (1:25,000), accuracy far paddy field area was 92%. A new image stacked by 10 layers, Landsat TM band 3,4,5, RVI, and wetness in May 31,1991 and August 19,1991 was made to estimate paddy field area by both supervised and unsupervised classification method. Paddy field was classified to 9100.98 ha by supervised classification. Error matrix showed 97.2% overall accuracy far training samples. Accuracy compared with topographical map was 95%. Unsupervised classifications by ISODATA using principal axis. Paddy field area by two different classification number of criteria were 6663.60 ha and 5704.56 ha and accuracy compared with topographical map was 87% and 82%. Irrespective of the estimating methods, paddy fields were discriminated very well by using two-date Landsat TM images in May 31,1991 (transplanting stage) and August 19,1991 (heading stage). Among estimation methods, rule-based classification method was the easiest to analyze and fast to process.

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A Study on Chlorophyll Estimating Algorithm in Kwangyang bay Using Satellite Images

  • Jo, Myung-Hee;Suh, Young-Sang;Kim, Byoung-Suk
    • Proceedings of the KSRS Conference
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    • 1999.11a
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    • pp.249-255
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    • 1999
  • Water pollution is becoming a serious problem in the populous cities and coastal areas near industrial complex. Sometimes, phytoplankton is considered as the most important element in the coastal environment. Phytoplankton is easily estimated by measuring chlorophyll content in the laboratory. In this study, to build up estimating algorithm of the chlorophyll amount related to the monitoring of coastal environments in Kwangyang bay, the correlationship the respective in situ observed data with Landsat TM and SeaWiFS satellite Image was analyzed. It showed that Landsat TM band 3 image has the highest correlationship with observed data, and based upon this result the monitoring algorithm of chlorophyll in coastal area was extracted. This algorithm will be an important for extracting and controlling environment elements in coastal areas in the future. And it has a significant meaning that it has established a spatial data construction in which satellite image alone could monitor the coastal environment.

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Water quality observation using Principal Component Analysis

  • Jeong, Jong-Chul;Yoo, Sing-Jae
    • Proceedings of the KSRS Conference
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    • 1998.09a
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    • pp.58-63
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    • 1998
  • The aim of the present study is to define and tentatively to interpret the distribution of polluted water released from Lake Sihwa into Yellow Sea using Landsat TM. Since the region is an extreme case 2 water, empirical algorithms for chlorophyll-a and suspended sediments have limitations. This work focuses on the use of multi-temporal Landsat TM. We applied PCA to detect evolution of spatial feature of polluted water after release from the lake. The PCA results were compared with in situ data, such as chlorophyll-a, suspended sediments, Secchi disk depth (SDD), surface temperature, radiance reflectance at six bands. The in situ remote sensing reflectance was analysed with PCA. On the basis of these In situ data we found good correlation between first Principal Component and Secchi disk depth ($R^2$=0.7631), although other variables did not result in such a good correlation. The problems in applying PCA techniques to multi-spectral remote sensed data are also discussed.

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Potential Use of Airborne Synthetic Aperture Radar to Monitor Agricultural Land Uses: A Case Study in Thailand

  • Wanpiyarat, V.;Buapradubkul, D.;Chutirattanaphan, S.
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.44-46
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    • 2003
  • In 1996, Thailand's participation in the Pacific Rim as a part of NASA's Mission to Planet Earth (MTPE) Program, was titled 'AIRSAR Thailand Project'. In this project the Department of Land Development utilized Topographic SAR (TOPSAR) which had multi-frequencies: C band, L band, and P band with multi-polarization: HH, VV, and HV as well as C band VV DEM. Satellite data such as LANDSAT TM was also utilized for optimal use. Results of AIRSAR image processing including data fusion among difference wavelength bands and polarization revealed the quality of AIRSAR that best suit for detection of agricultural land uses. The HH-L band AIRSAR was proven to be useful to distinguish among crop types when combined with appropriate data. The HH, VV, and HV-P band enhanced surface characteristics of swamp forest and wetland. In addition, TOPSAR has its great advantage for identification of salt farms and shrimp ponds.

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Detection of Red Tide Patches using AVHRR and Landsat TM data (AVHRR과 Landsat TM 자료를 이용한 적조 패취 관측)

  • Jeong, Jong-Chul
    • Journal of Environmental Impact Assessment
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    • v.10 no.1
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    • pp.1-8
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    • 2001
  • Detection of red tides by satellite remote sensing can be done either by detecting enhanced level of chlorophyll pigment or by detecting changes in the spectral composition of pixels. Using chlorophyll concentration, however, is not effective currently due to the facts: 1) Chlorophyll-a is a universal pigment of phytoplankton, and 2) no accurate algorithm for chlorophyll in case 2 water is available yet. Here, red band algorithm, classification and PCA (Principal Component Analysis) techniques were applied for detecting patches of Cochlodinium polykrikoides red tides which occurred in Korean waters in 1995. This dinoflagellate species appears dark red due to the characteristic pigments absorbing lights in the blue and green wavelength most effectively. In the satellite image, the brightness of red tide pixels in all the three visible bands were low making the detection difficult. Red band algorithm is not good for detecting the red tide because of reflectance of suspended sediments. For supervised classification, selecting training area was difficult, while unsupervised classification was not effective in delineating the patches from surrounding pixels. On the other hand, PCA gave a good qualitative discrimination on the distribution compared with actual observation.

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A Design of Clustering Classification Systems using Satellite Remote Sensing Images Based on Design Patterns (디자인 패턴을 적용한 위성영상처리를 위한 군집화 분류시스템의 설계)

  • Kim, Dong-Yeon;Kim, Jin-Il
    • The KIPS Transactions:PartB
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    • v.9B no.3
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    • pp.319-326
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    • 2002
  • In this paper, we have designed and implemented cluttering classification systems- unsupervised classifiers-for the processing of satellite remote sensing images. Implemented systems adopt various design patterns which include a factory pattern and a strategy pattern to support various satellite images'formats and to design compatible systems. The clustering systems consist of sequential clustering, K-Means clustering, ISODATA clustering and Fuzzy C-Means clustering classifiers. The systems are tested by using a Landsat TM satellite image for the classification input. As results, these clustering systems are well designed to extract sample data for the classification of satellite images of which there is no previous knowledge. The systems can be provided with real-time base clustering tools, compatibilities and components' reusabilities as well.

Extraction of Land Surface Change Information by Using Landsat TM Images (Landsat TM 영상을 이용한 지표변화정보 추출)

  • 최승필;양인태
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.21 no.3
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    • pp.261-267
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    • 2003
  • We are able to simultaneously extract the land surface change information, as we input each information extracted from images classified during the two periods, as the attribute information of geographic information, and then use it a parameter of GIS. Hence, this research sought to present basic data far efficient management and development of land surface, together with land use trends, by using the remote-sensing technique enabling the acquisition of the land surface covering information, as well as the benefits of GIS. The research conducted a study on the extraction of land surface change information, and made it possible to treat image information easily compared to the existing image classification methods, thereby making it easy to know the land surface change process for each pixel.

Spectral Reflectivity on Geological Materials in Yangsan-Dongrae Fault Area (양산-동래 단층 지역의 암석에 대한 분광학적 연구)

  • 姜必鍾;智光薰
    • Korean Journal of Remote Sensing
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    • v.3 no.1
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    • pp.1-10
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    • 1987
  • The study was performed to recognize the most preferable spectral chennels for discriminating geological materials using the portable radiometer. The portable radiometer covers the visible and short infrared regions from approximately 0.4 to 2.5 microns which are coincided with Landsat TM, and the rock samples used for the study are pyrophylites, andesites, granite, granodiorite and silicified sedimentary rocks which are collected in Yangsan-Dongrae fault area. The analysis of the rock sample provides a preliminary basis for determining the wavelength regions showing diagnostic spectral features and for discriminating hydrothermal altered rocks from the unaltered rocks. The measurement of spectral of spectral reflectance for the rock samples was carried out in the laboratory which environment condition such as temperature, light sources, and humidity are constant. The analysis of the measured data was based on correlation between the reflectance value of the rock samples, and the follow discriptions are output of the study. 1) Pyrophyllite shows absorption at 0.83 $\mu\textrm{m}$ due to the oxidation of pyrite, and absorption at 2.22 $\mu\textrm{m}$ due to OH. 2) The altered rocks have generally higher reflectance than the unaltered rocks. 3) The ratio mesurement of pyrophyllites shows strong absorption at band 5/6 and band 6/4(in Landsat TM 5/7, 7/4). The ratio 1/5(Landsat TM 1/5) may be useful to discriminate andesite from the granite.

A Study on the Preparation Method of Fruit Cropping Distribution Map using Satellite Images and GIS (위성영상과 GIS를 이용한 과수재배 분포도 작성 기법에 관한 연구)

  • Jo, Myung-Hee;Bu, Ki-Dong;Lee, Jung-Hyoup;Lee, Kwang-Jae
    • Journal of the Korean Association of Geographic Information Studies
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    • v.3 no.4
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    • pp.73-86
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    • 2000
  • This study focused on extracting an efficient method in the fruit cropping distribution mapping with various classification methods using multi-temporal satellite images and Geographic Information Systems(GIS). For this study, multi-temporal Landsat TM images, in observation data and existing fruit cropping area statistics were used to compare and analyze the properties of fruit cropping and seasonal distribution per classification method. As a result, this study concludes that Maximum Likelihood Method with earlier autumn satellite image was most efficient for the fruit cropping mapping using Landsat TM image. In addition, it was clarified that cropping area per administrative boundary was prepared and distribution pattern was identified efficiently using GIS spatial analysis.

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