• Title/Summary/Keyword: Landsat/TM

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Land Cover Change Detection in the Nakdong River Basin Using LiDAR Data and Multi-Temporal Landsat Imagery (LiDAR DEM과 다중시기에 촬영된 Landsat 영상을 이용한 낙동강 유역 내 토지피복 변화 탐지)

  • CHOUNG, Yun-Jae
    • Journal of the Korean Association of Geographic Information Studies
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    • v.18 no.2
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    • pp.135-148
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    • 2015
  • This research is carried out for the land cover change detection in the Nakdong River basin before and after the 4 major rivers restoration project using the LiDAR DEM(Digital Elevation Model) and the multi-temporal Landsat imagery. Firstly the river basin polygon is generated by using the levee boundaries extracted from the LiDAR DEM, and the four river basin imagery are generated from the multi-temporal Landsat-5 TM(Thematic Mapper) and Landsat-8 OLI(Operational Land Imager) imagery by using the generated river basin polygon. Then the main land covers such as river, grass and bare soil are separately generated from the generated river basin imagery by using the image classification method, and the ratio of each land cover in the entire area is calculated. The calculated land cover changes show that the areas of grass and bare soil in the entire area have been significantly changed because of the seasonal change, while the area of the river has been significantly increased because of the increase of the water storage. This paper contributes to proposing an efficient methodology for the land cover change detection in the Nakdong River basin using the LiDAR DEM and the multi-temporal satellite imagery taken before and after the 4 major rivers restoration project.

Detection of Land Cover Change Using Landsat Image Data in Desert Area (Landsat 영상자료를 이용한 사막지역의 토지피복 변화 분석)

  • M, Erdenechimeg;Choi, Byoung-Gil;Na, Young-Woo;Kim, Tae-Hoon
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.28 no.4
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    • pp.471-476
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    • 2010
  • This study aimed at monitoring, mapping, and assessing the land degradation in the desert area. In this research, the Landsat TM and ETM+ imageries to assess the extent of land degradation for study area during the period from 1991 to 2007. Were used to study supervized, unsupervized classfication and NDVI land cover changes in the desert area in Mongolia. The classified map consists of five classes of water, vegetation, slight desertification, middle desertification and sever desertification. It shows that for determination classfication methods and NDVI, desertification map of the study area are prepared. The result showed accounting for a clear deterioration in vegetative cover, an increase of sever desertification and a decrease in middle desertification and slight desertification respectively of the total study area.

The Use of Linearly Transformed LANDSAT Data in Landuse Classification (선형 변환된 LANDSAT 데이타를 이용한 토지이용분류(낙동강 하구역을 중심으로))

  • 안철호;박병욱;김종인
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.7 no.2
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    • pp.85-92
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    • 1989
  • The aim of this study is to find out the combination of effective transformed data, applying Remote Sensing techniques, as to the classification and particular objects by transforming the MSS data and TM data of the satellite LANDSAT into several linearly transformed data. Since one of the problems in the processing of the LANDSAT data is the vastness of the data, the Linear Transformation could be a method to perform analysis of those vast data, more efficiently and economically. This method is carried out as follows : (1) offering the simplicity over complex data, (2) selectional processing over redundant data and removing unnecessary data, (3) emphasizing on the object of the study ; by transforming multispectral data through linear calculation and statistical transformation. In this study, the analysis and transformation of the data have been performed by means of Band Ratioing and Principal Component Analysis. As the classificatory consequence, Infrared/RED Ratioing which expands the characterization of green vegetation, has been useful for a distinctive classification among other classes. For the Principal Component Analysis, band 1,2,7 are efficient in the classification of the green vegetation.

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Vegetation Change Detection in the Sihwa Embankment using Multi-Temporal Satellite Data (다중시기 위성영상을 이용한 시화 방조제 내만 식생변화탐지)

  • Jeong, Jong-Chul;Suh, Young-Sang;Kim, Sang-Wook
    • Journal of Environmental Science International
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    • v.15 no.4
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    • pp.373-378
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    • 2006
  • The western coast of South Korea is famous for its large and broad tidal lands. Nevertheless, land reclamation, which has been conducted on a large scale, such as Sihwa embankment construction project has accelerated coastal environmental changes in the embankment inland. For monitoring of environmental change, vegetation change detecting of the embankment inland were carried out and field survey data compared with Landsat TM, ETM+, IKONOS, and EOC satellite remotely sensed data. In order to utilize multi-temporal remotely sensed images effectively, all data set with pixel size were analyzed by same geometric correction method. To detect the tidal land vegetation change, the spectral characteristics and spatial resolution of Landsat TM and ETM+ images were analyzed by SMA(spectral mixture analysis). We obtained the 78.96% classification accuracy and Kappa index 0.2376 using March 2000 Landsat data. The SMA(spectral mixture analysis) results were considered with comparing of vegetation seasonal change detection method.

A Statistic Correlation Analysis Algorithm Between Land Surface Temperature and Vegetation Index

  • Kim, Hyung-Moo;Kim, Beob-Kyun;You, Kang-Soo
    • Journal of Information Processing Systems
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    • v.1 no.1 s.1
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    • pp.102-106
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    • 2005
  • As long as the effective contributions of satellite images in the continuous monitoring of the wide area and long range of time period, Landsat TM and Landsat ETM+ satellite images are surveyed. After quantization and classification of the deviations between TM and ETM+ images based on approved thresholds such as gains and biases or offsets, a correlation analysis method for the compared calibration is suggested in this paper. Four time points of raster data for 15 years of the highest group of land surface temperature and the lowest group of vegetation of the Kunsan city Chollabuk_do Korea located beneath the Yellow sea coast, are observed and analyzed their correlations for the change detection of urban land cover. This experiment based on proposed algorithm detected strong and proportional correlation relationship between the highest group of land surface temperature and the lowest group of vegetation index which exceeded R=(+)0.9478, so the proposed Correlation Analysis Model between the highest group of land surface temperature and the lowest group of vegetation index will be able to give proof an effective suitability to the land cover change detection and monitoring.

Time Series Analysis of Area of Deltaic Barrier Island in Nakdong River Using Landsat Satellite Image (Landsat 위성영상을 활용한 낙동강 삼각주 연안사주의 면적 시계열 분석)

  • Lee, Seulki;Yang, Mihee;Lee, Changwook
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.34 no.5
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    • pp.457-469
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    • 2016
  • Nakdong river barrage was affected by artificial interference such as construction of port, industrial complex and estuary barrage. This change in Nadong river lead to environmental changes and affected the ability of barrier islands. Therefore, it is decided that the observation of changes in the Nakdong river estuary is very important. In this paper, the topographic change of the Nakdong river barrage observe based on Landsat TM, ETM+ images from 1984 to 2015. In addition, this study tried to conduct a comparative analysis on the area for change of sandy sediment according to tide level. This results could estimate height and volume about sandy sediment accumulated on the lower sand dune. Also, these results are expected to be the basis for prediction of the changing topography of the sand dune. The area of the average change in region 1,2,3 was calculated as 3,015m2, 167,550m2, 14,596m2. This result is expected to be very useful for the continuous observation for sediment changes of Nakdong river.

Prediction of Future Land use Using Times Series Landsat Images Based on CA (Cellular Automata)-Markov Technique (시계열 Landsat 영상과 CA-Markov기법을 이용한 미래 토지이용 변화 예측)

  • Lee, Yong-Jun;Pack, Geun-Ae;Kim, Seong-Joon
    • Proceedings of the KSRS Conference
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    • 2007.03a
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    • pp.55-60
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    • 2007
  • The purpose of this study is to evaluate the temporal land cover change by gradual urbanization of Gyeongan-cheon watershed. This study used the five land use of Landsat TM satellite images(l987, 1991, 2001, 2004) which were classified by maximum likelihood method. The five land use maps examine its accuracy by error matrix and administrative district statistics. This study analyze land use patterns in the past using time.series Landsat satellite images, and predict 2004 year land use using a CA-Markov combined CA(Cellular Automata) and Markov process, and examine its appropriateness. Finally, predict 2030, 2060 year land use maps by CA-Markov model were constructed from the classified images.

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Method Development of Flood Damaged Area Detection by Typhoon RUSA using Landsat Images (Landsat 영상을 이용한 태풍 RUSA 침수피해지역 분석기법 연구)

  • Lee, Mi Seon;Park, Geun Ae;Park, Min Ji;Shin, Hyung Jin;Kim, Seong Joon
    • Proceedings of the Korea Water Resources Association Conference
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    • 2004.05b
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    • pp.1300-1304
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    • 2004
  • This study is to present a method of flood damaged area detection by the typhoon RUSA (August 31 - September 1, 2002) using Landsat 7 ETM+ and Landsat 5 TM images. Two images of Sept. 29, 2000 and Sept. 11, 2002 (path 115, row 34) were prepared for Gangreung, To identify the damaged areas, firstly, the NDVI (Normalized Difference Vegetation Index) of each image was computed, secondly, the NDVI values were reclassified as two categories that the negative index values including zero are the one and the positive index values are the other, thirdly the reclassified image before typhoon is subtracted from the reclassified image after typhoon to get DNDVI (Differential NDVI). Some part of urban and agricultural were classified into damaged area due to typhoon RUSA in Gangreung, $18.8km^2$ and $17.7km^2$ respectively.

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Derivation and Comparison of Narrow and Broadband Algorithms for the Retrieval of Ocean Color Information from Multi-Spectral Camera on Kompsat-2 Satellite

  • Ahn, Yu-Hwan;Shanmugam, Palanisamy;Ryu, Joo-Hyung;Moon, Jeong-Eom
    • Korean Journal of Remote Sensing
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    • v.21 no.3
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    • pp.173-188
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    • 2005
  • The present study aims to derive and compare narrow and broad bandwidths of ocean color sensor’s algorithms for the study of monitoring highly dynamic coastal oceanic environmental parameters using high-resolution imagery acquired from Multi-spectral Camera (MSC) on KOMPSAT-2. These algorithms are derived based on a large data set of remote sensing reflectances ($R_{rs}$) generated by using numerical model that relates $b_b/(a + b_b)$ to $R_{rs}$ as functions of inherent optical properties, such as absorption and backscattering coefficients of six water components including water, phytoplankton (chl), dissolved organic matter (DOM), suspended sediment (SS) concentration, heterotropic organism (he) and an unknown component, possibly represented by bubbles or other particulates unrelated to the first five components. The modeled $R_{rs}$ spectra appear to be consistent with in-situ spectra collected from Korean waters. As Kompsat-2 MSC has similar spectral characteristics with Landsat-5 Thematic Mapper (TM), the model generated $R_{rs}$ values at 2 ㎚ interval are converted to the equivalent remote sensing reflectances at MSC and TM bands. The empirical relationships between the spectral ratios of modeled $R_{rs}$ and chlorophyll concentrations are established in order to derive algorithms for both TM and MSC. Similarly, algorithms are obtained by relating a single band reflectance (band 2) to the suspended sediment concentrations. These algorithms derived by taking into account the narrow and broad spectral bandwidths are compared and assessed. Findings suggest that there was less difference between the broad and narrow band relationships, and the determination coefficient $(r^2)$ for log-transformed data [ N = 500] was interestingly found to be $(r^2)$ = 0.90 for both TM and MSC. Similarly, the determination coefficient for log-transformed data [ N = 500] was 0.93 and 0.92 for TM and MSC respectively. The algorithms presented here are expected to make significant contribution to the enhanced understanding of coastal oceanic environmental parameters using Multi-spectral Camera.

Comparison of Fuzzy Classifiers Based on Fuzzy Membership Functions : Applies to Satellite Landsat TM Image

  • Kim Jin Il;Jeon Young Joan;Choi Young Min
    • Proceedings of the IEEK Conference
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    • 2004.08c
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    • pp.842-845
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    • 2004
  • The aim of this study is to compare the classification results for choosing the fuzzy membership function within fuzzy rules. There are various methods of extracting rules from training data in the process of fuzzy rules generation. Pattern distribution characteristics are considered to produce fuzzy rules. The accuracy of classification results are depended on not only considering the characteristics of fuzzy subspaces but also choosing the fuzzy membership functions. This paper shows how to produce various type of fuzzy rules from the partitioning the pattern spaces and results of land cover classification in satellite remote sensing images by adopting various fuzzy membership functions. The experiments of this study is applied to Landsat TM image and the results of classification are compared by fuzzy membership functions.

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