• Title/Summary/Keyword: Landsat Thematic Mapper

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Unsupervised Classification of Forest Vegetation in the Mt. Wolak Experimental Forest Using Landsat Thematic Mapper Data (Landsat Thematic Mapper 화상자료를 이용한 월악산 지역 산림식생의 무감독분류)

  • Lee, Sang Hee;Park, Jae Hyeon;Lee, Joon Woo;Kim, Je Su
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.4 no.2
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    • pp.36-44
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    • 2001
  • The main purpose of this study was to classify forest vegetation effectively using Landsat Thematic Mapper data(June, 1994) in mountainous region. The research area was the Mt. Wolak Experimental Forest of Chungbuk National University, near Chungju and Jecheon city, Chungcheongbuk-do. To classify forest vegetation effectively, Normalized Difference Vegetation Index(NDVI) was used to reduce topographic effects. This NDVI was modified and transformed to the value of 0 to 255, and then the modified values were combined with other Landsat Thematic Mapper bands. To classify forest and land cover types, unsupervised classification method was used. The results of this study are summarized as follows. 1. Combinations of band "3, 5, NDVI" in Landsat Thematic Mapper data showed a good separation with high accuracy. The expected classification accuracy was 95.1% in Landsat Thematic Mapper data. 2. The Land Cover types were classified into six groups : coniferous forest, deciduous forest, mixed forest, paddy and grass, non-forest, and other undetectable areas. As these classified results were compared with the reconnaissance survey and aerial black and white infrared photographs, the overall classification accuracy was 76.5% in Landsat Thematic Mapper data. 3. The portion of non-forest in Mt. Wolak area was 1.9%. The percentages of coniferous, deciduous and mixed forests were 30.9%, 35.7% and 26.4%, respectively. 4. As these classified results were compared with other reference data, the percentages of coniferous, deciduous and mixed forests increased, but the portion of non-forest was exceedingly diminished. These differences are thought to be from the different research method and the different season of received Landsat Thematic Mapper data.

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Estimating Sea Surface Temperature Change after Tide Embankment Construction using Landsat Data (방조제 건설에 의한 해수면 온도 변화 추정)

  • Shin, Dong-Hoon;Lee, Kyoo-Seock
    • Journal of the Korean Association of Geographic Information Studies
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    • v.9 no.4
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    • pp.224-232
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    • 2006
  • This study investigates to detect Sea Surface Temperature (SST) and land cover change after tide embankment construction using Landsat Thematic Mapper (TM) Thermal Infrared (TIR) band data at Shihwa Lake and surrounding area. SST measurement is important for studies of both the structure of the ocean and as the thermal boundary between the ocean and the atmosphere. Since 1970s, the derivation of SST by satellite remote sensing (RS) has been applied to earth surface using Advanced Very High Resolution Radiometer (AVHRR) and Landsat TM. However, AVHRR has restriction in deriving SST in the area whose shoreline is complicated like western coast in South Korea because of coarse spatial resolution. The TIR band of TM images can be used to detect SST change whose shoreline is complicated and narrow like the study site. Thus, multi-temporal TM images were used for SST change detection in this study.

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Landuse classifications from Thematic Mapper Images Using a Maximum Likelihood Method (위성영상을 이용한 토지이용분류에 관한 연구)

  • 박희성;박승우
    • Proceedings of the Korean Society of Agricultural Engineers Conference
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    • 1998.10a
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    • pp.366-369
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    • 1998
  • To get the knowledge of land uses for watersheds, Thematic Mapper image from Landsat 5 satellite was used. The image was classified into land covers/uses by maximum likelihood classification technique. Land uses from the satellite image in this study was compared with those from the topographical map in previous. It was found that Land uses from the satellite image had a good reflection of real situations and more advantage in the reduction of time and cost.

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Study on the Image Information Analysis for Inaccessible Area (비접근 지역에 대한 영상정보 분석 연구)

  • 함영국;김영환;신석철
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1998.10a
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    • pp.343-348
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    • 1998
  • In this study, we extracted several terrain information using satellite and aerial images. We detected change of terrain using Landsat Thematic Mapper(TM) and aerial images which are multitemporal data. In change detection processing, we first classified satellite images by ISODATA algorithm which is an unsupervised learning algorithm, then performed change detection. By this method, we could obtain good result. Also we introduce sub-pixel concept to classify road and agriculture area in inaccessible area. In summary, in chang detection processing, we can find that the used method is efficient.

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Change of Coastal Ocean According to Kwang Yang Bay Development based on Landsat TM Images

  • Lee, Byung-Gul;Choo, Hyo-Sang;Lee, Gyu-Hyung
    • Environmental Sciences Bulletin of The Korean Environmental Sciences Society
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    • v.4 no.3
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    • pp.149-156
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    • 2000
  • This study presents an investigation of the changes that have occurred in the coastal ocean area of Kwangyang Bay located in the South Coastal region of Korea using remote sensing data based on Landsat Thematic Mapper (TM) multispectral digital data from 1988 and 1996. The coastal changes were detected using the digital histogram method and vector trace method. All the images were preprocessed, i.e. geometrically corrected, before the training set selection. when comparing the histograms of 7-band TM data, it was found that the band 5 image exhibited two critical Digital Number(DN) peaks, thereby indicating new coastal water and coastal land data. Based on this information, the coastal ocean area of the band 5 image was calculated using the vector tracing method supported by a CAD program. The result shows that the coastal ocean area decreased by about 5 % between 1988 to 1994. Accordingly, this gives a strong indication that the continuing land development will have a serious impact on the ecosystem of Kwangyang Bay.

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An Analysis of Spatiotemporal Change of Southwestern Coastal Wetlands Using Landsat Thematic Mapper Data (Landsat TM 자료를 이용한 서남해 연안 습지의 시공간 변화 분석에 관하여)

  • Yi, Gi-Chul;Im, Byung-Sun;Woo, Chang-Ho;Cho, Young-Hwan
    • Journal of Environmental Impact Assessment
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    • v.6 no.1
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    • pp.55-66
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    • 1997
  • This study summarizes the use of satellite data to detect the change of southwestern coastal wetlands in Korea. The images used for this study were two Landsat Thematic Mapper(TM) images (June 12, 1984 & June 2, 1992). TM images were used to classify such different types of wetlands as aquatic bed, nonaquatic bed and other land use in the region. Then it, was possible to a) determine the status of wetlands using image classification products, and b) detect the changes of various types of wetlands influenced by both human and nature. The results from spatiotemporal analysis showed that approximately 120 lad of coastal wetlands were lost from the year of 1984 to 1992. 71 % of the lost wetlands were converted to the reclaimed land. This loss of wetlands has been causing the profound environmental impacts. It has been successfully proved that satellite data are very effective for spatiatemporal change analysis, especially for that of coastal wetlands.

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The Expectation of the Land Use and Land Cover Using CLUE-S Model and Landsat Images (CLUE-S 모델과 시계열 Landsat 자료를 이용한 토지피복 변화 예측)

  • Kim, Woo-Sun;Yun, Kong-Hyun;Heo, Joon;Jayakumar, S.
    • Journal of Korean Society for Geospatial Information Science
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    • v.16 no.1
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    • pp.33-41
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    • 2008
  • Land use/land cover is very important to understand the change in the land cover between specific periods. But as there are number of factors which are responsible for the change in the land cover, it is very difficult to identify the specific factors. Therefore in the study we made an attempt to use the land use strategies quantitatively and conducted simulation study. The input data using the CLUE-S model are the satellite data of 1987 and 2001 from Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+) and we conducted simulations for 23 years from 1987 to 2010. As a result, the accuracy between the land use map derived from original satellite data and simulation for 2001 was 93.69% and in this reason we could expect land use and land cover in the future.

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A Study on the Land-Use Changes on the Balan Water sheds Using the Multi-temperature Landsat TM Images (다시기 Landsat TM 영상을 이용한 소유역의 토지이용변화분석)

  • 강문성;박승우
    • Proceedings of the Korean Society of Agricultural Engineers Conference
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    • 1999.10c
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    • pp.473-478
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    • 1999
  • The purpose of the study were to detect and evaluate the land use and changes on the Balan Watersheds, located southwest of Suwon, using the Thematic Mapper(TM) data. Three sests of TM taken in 1985 , 1993 and 1996 were used and the changes in the land use analyzed and compared. The suupervised and unsuperivised classification methods were adoppted to classify five land-cover categories ; Paddy , upland , forest , residential , and water. Future ladn use patterns were simulated using a Markow chain method, and the change ratios presented.

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Evaluation of Land Cover Classification of Pyeong-Taeg Area by Landsat Thematic Mapper Data (Landsat TM 영상자료를 이용한 평택지역의 토지피복 현황 및 분류정확도 평가)

  • 윤성탁;김선오;임상규
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.3 no.3
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    • pp.163-170
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    • 2001
  • The objective of this study was to evaluate land cover classification of PyeongTaeg area by Landsat Thematic Mapper Data June, 1997. This study was also to make more correct reference data using DGPS, aerophoto, and topographical chart etc.. The result of the area of paddy and upland were estimated 4,949 $\textrm{km}^2$ and 16,157 $\textrm{km}^2$, respectively. Correctness of estimation by using DGPS, aerophoto, topographical chart were shown over 90% correct in case of rice paddy field, water, and sea, while upland, vinyl house, forest, grassland, village were shown low correctness. Total average accuracy was shown to be 85.8%. Correctness of paddy field showed high value of 92%, showing that use of remote sensing data was proved to be effective methods to estimate spatial distribution and cultivation status of paddy field. Classification result of sea, water area, downtown had higher correctness, while upland, vinyl-house, grassland were proved to be relatively low correctness because of it's small area and mixed distribution.

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