• Journal of the Korean Association of Geographic Information Studies
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• v.4 no.1
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• pp.18-26
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• 2001

Landsat TM band ratio algorithms were made by in-water optical measurement data of each sampling points for water quality monitoring of coastal area using Landsat TM satellite data. The algorithm was derived from in-water optical reflectance data which was measuring by the PRR(profiling reflectance radiometer). And, in-water optical reflectance data were applied to Landsat TM bands. Relationship between in-water optical reflectance and pigments proposed by the ratio of TM band 1 and band 2 showed to as follows; $Y=3.8352{\times}(R(band\;1)/R(band\;2))^{-2.1978}$ ($R^2$=0.7069) and, relationship of the ratio of TM band 1 and band 3 as follows; $Y=23.288{\times}(R(band\;1)/R(band\;3))^{-1.5243}$ ($R^2$=0.8062). Calculated the upwelling radiance of water surface and radiance of TM showed the ratio of atmospheric effect. In the coastal area Rayleigh and Mie scattering of atmosphere is to make over 80% of normalized radiance of Landsat TM. In order to apply in-water algorithm obtained by PRR, we had to calculate the atmospheric effects at sampling site. And, the quantitative analysis of in-water components using Landsat TM data need the calibration of in-water algorithm and effective method of atmospheric correction.

• Korean Journal of Remote Sensing
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• v.7 no.1
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• pp.29-43
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• 1991

The study was performed to extraction the ground water potential area using LANDSAT TM data. The image processing techniques developed for the study are contrast transformation, differential filtering and pseudo stereoscopic image methods. These were examined for lineament extraction, lineament interpretation and the integration of vertor data with LANDSAT data. The differential filtering method is much usefull for lineament extraction, and all direction lineaments are clearly shown on the band 5 image of LANDSAT TM. The pseudo stereoscopic image are made in which color differential method is adopted, the pair images are usefull for the lineament interpretation. The results of the analysis are as follows. 1) there is a close correlation between lineament and cased well in the study area, because 33 wells of the developed 45 cased wells coincide with the lineaments. 2) 21 sites in the study area were selected for pumping test, and as a result 11 sites of them produces over than 200 ton/day.

• Korean Journal of Agricultural and Forest Meteorology
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• v.2 no.1
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• pp.9-15
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• 2000

The objective of this study is to evaluate the use of RADARSAT and Landsat TM data for the monitoring of rice growth. The relationships between backscatter coefficients($\sigma$$^{0}$ ) of RADARSAT data and digital numbers (DN) of Landsat TM and rice growth parameters were investigated. Radar backscatter coefficients were calculated by calibration process and then compared with rice growth parameters; plant height, leaf area index (LAI), and fresh and dry biomass. When radar backscatter coefficient ($\sigma$$^{0}$ ) of rice was expressed as a function of time, it is shown that the increasing trend ranged from -22--20dB to -9--8dB as growth advances. The temporal variation of backscatter coefficient was significant to interpret rice growth. According to the relationship between leaf area index and backscatter coefficient, backscatter coefficient underestimated leaf area index at the beginning of life history and overestimated, at the reproductive stage. The same increasing trend between biomass and backscatter coefficient was shown. From these results, RADARSAT data appear positive to the monitoring of rice growth. Each band of time-series Landsat TM data had a significant trend as a rice crop grows during its life cycle. Spectral indices, NDVI[(TM4-TM3)/(TM4+TM3)] and RVI(TM4/TM2), derived from Landsat TM equivalent bands had the same trend as leaf area index.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.2081-2084
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• 2008

본 연구에서는 가용 Landsat TM 위성자료를 이용하여 금호강유역의 수문변수를 산정하였다. 대상 유역인 금호강유역은 대구시를 포함한 하천유역으로 도시화로 인한 유역 환경변화가 매우 심한 지역이다. 대상유역의 수문변수의 변화가 유역 생태 및 수문순환구조에 미치는 영향이 크므로 위성자료를 활용한 광역에 대한 수문변수 산정과 시공간변화 특성의 자연적요인은 물론 인위적인 요인을 분석하는 것은 매우 중요하다. 가용한 Landsat자료는 30-120m의 뛰어난 공간분해능과 다양한 관측 밴드를 가지고 있어, 수문변수 산정 및 유역 환경변화를 파악하기에 적합한 자료이다. 본 연구에서는 1985, 1998, 1999년, 2001년 Landsat TM자료를 이용하여 대상지역에 대한 기하학적 보정 등 전처리과정을 거쳐 정규화 식생지수(NDVI; Normalized Difference Vegetation Index)와 이와 연계한 엽면적지수(LAI; Leaf Area Index)를 산정하였으며 토지피복변화를 분석하였다. Landsat자료를 이용한 광역의 토지피복변화와 수문변수변화 분석을 통하여, 위성관측기법 이용한 유역 수문변수 변화특성 도출 가능성을 제시하였다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.4 no.2
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• pp.27-41
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• 1986

In this study, practical use of TM (Thematic Mapper) data was evaluated by comparison of LANDSAT- 5 TM and MSS (Multispectral Scanner) data. The comparison of TM and MSS data was achieved by analyzing the result of landuse mapping of Incheon area, and in addition, the comparison of accuracy according to image enhancement method was made. From the results of this study, we found that TM data was more accurate by about 20% than MSS data in landuse mapping, and that smoothing was effective in image enhancement processing of TM data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.16 no.2
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• pp.187-194
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• 1998

In this study, effective multispectral Landsat TM band combinations for a merging with the high resolution IRS-1C PAN data using the IHS method to improve landuse accuracy is discussed. From the pre-classified image using the merged images with TM all six band images(with the exception of band 6 image) and PAN image, a sample data which has ten classes was generated. An evaluation of the overall classification accuracy for the representative seven merged images which were merged using each TM three-band images and IRS-1C PAN image by IHS method for the sample area. The increase in classification accuracy is most significant with the inclusion of two of TM4, TM5 and TM7 infrared band images. Especially, the largest increase(11.8 percent) in landuse classification accuracy were investigated when Landsat TM247 bands were merged with IRS-1C PAN data. The classification accuracy when TM three band image and PAN image were used without merging is higher than result of the case of using the merged images.

• Journal of Korean Society for Geospatial Information Science
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• v.7 no.1 s.13
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• pp.87-95
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• 1999

The min object of this study was to prove the effectiveness of PCA(principal component analysis) merged images produced by PCA method using high resolution IRS-1C PAN data and multispectral Landsat TM data A sample data which has ten classes was generated for evaluation of the overall classification accuracy. In result, merged sample image which TM13457 bands with IRS-1C PAN data by PCA method showed best result (95.1%). Especially, the largest improve (6.2%) in classification accuracy was resulted when IRS-1C PAN data was merged with TM123457 or TM13457 images. In addition, landuse classification accuracy of the PCA merged images was improved (5.16%) than original color composite images of Landsat TM data.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.04a
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• pp.167-170
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• 2003

본 연구는 무감독영상해석(Unsupervised Classification)에서 주성분 분석법(Principal Component Analysis)의 응용성을 연구하기 위하여, 주성분 분석법을 K-means, ISODATA 두가지 무감독분류법에 적용하였다. 적용대상지역은 제주도이다. 본 연구에서 주성분 분석 방법중에서 비정규형 주성분 분석방법 (Unstandardized PCA)과 정규형 주성분 분석방법(Standardized PCA) 두가지 경우로 나누어서 각각 연구하였다. 이를 위하여 제주도의 Landsat TM영상과 국토연구원에서 조사한 제주도 식생분류 조사자료와 현장조사 자료 그리고 1/25,000 수치지도를 이용하였다. 그리고 분석된 자료의 정확도를 평가하기 위하여 오차행렬(Error Matrix)을 도입하여 계산하였다. 우선 비정규형 주성분 분석법으로 구한 주성분 영상과 Landsat TM 원래 영상을 오차행렬을 이용하여 제주도의 식생 분류에 각각 적용하였다. 그 결과, K-means 무감독분류법에서는 Landsat TM 자료를 직접 이용한 경우에는 바다와 육상의 분류가 잘 되지 않았으며, 또한 전반적인 영상분류결과가 관측치와 많은 차이를 보였다. 그러나, 주성분 분석법으로 계산된 주성분 영상으로 K-means방법으로 분류 한 결과는 관측치와 잘 일치를 하였다. ISODATA의 경우, Landsat TM 원래영상을 계산하면, K-means으로 분류한 결과보다는 좋은 값을 나타냈으나, 주성분 분석법으로 구한 영상의 계산결과와 비교하면, 주성분 영상으로 구한 분류결과의 정확도가 약 15%정도 높게 나타났다. 정규형 주성분 분석법의 경우를 보면 K-means에서는 Landsat TM원래 자료보다 우수한 결과를 보여주었으나, 비정규형 주성분 분석법으로 계산된 결과보다는 정확도가 다소 떨어지는 단점이 있었고, ISODATA의 경우도 Landsat TM원래 자료보다 약 7%정도의 높은 정확도를 보였으나, 비정규형 영상보다는 약8%정도 낮은 정확도를 보였다. 본 연구에서 주성분 분석법으로 계산된 결과에서 주목되는 것은, 주성분 분석법으로 구한 주성분 영상은 분류방법(K-means, ISODATA, artificial neural networks)에 따라 분류된 결과값이 비슷하게 나타난 반면, Landsat TM원래 자료는 분류방법에 따라 결과값이 많은 차이를 보여 주었다. 그리고 주성분 분석 방법 중에서도 비정규형 주성분 분석법(Unstandardized PCA)이 정규형 주성분 분석법(Standardized PCA)보다 영상분석에서 더 좋은 결과를 보여주는 것으로 나타났다.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.2
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• pp.31-43
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• 2005

Four time points of the fractional area data during the 15 years of the highest group of land surface temperature and the lowest group of NDVl of the Kunsan city Chollabuk_do, Korea located beneath the Yellow sea coast, are observed and analyzed their correlations for the intention to detect the changes of urban land cover. As long as the effective contributions of satellite images in the continuous monitoring of the wide area for wide range of time period, Landsat-5 TM and Landsat-7 ETM+ artificial satellite images, acquisited over the Kunsan city area, are surveyed by the compared calibration after quantization and classification of the deviations between TM and ETM+ images substituted approved error correction thresholds such as gains and biases or offsets. This experiment and research applied Landsat-5 TM and Landsat-7 ETM+ artificial satellite images in change detection of urban land cover in urbanized Kunsan city, then detected strong and proportional correlation relationship between the highest group of land surface temperature and the lowest group of NDVI which exceeded R=(+)0.9478, so the proposed Correlation Analysis Model between the highest group of land surface temperature and the lowest group of NDVI will be able to give proof an effective suitability to the land city change detection monitoring.

• Korean Journal of Remote Sensing
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• v.15 no.1
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• pp.1-8
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• 1999

The estimation technique of surface water temperature by satellite remote sensing has been applied to ocean and large lakes using AVHRR. However, the spatial resolution AVHBR is not abquate for coastal region and small lakes. Landsat 5 TM has 120 m spatial resolution, which suits better. We carried out analysis of surface water temperature in Lake Sihwa and near coastal area using Landsat 5 TM. To relate digital number to the brightness temperature, we applied Empirical, NASA, RESTEC, Quadratic methods. Comparing calculated and observed value, we obtained as follows; NASA method, $R^2=0.9343$, RMSE(Root Mean Square Error)=3.5876$^{\circ}C$; RESTEC method, $R^2=0.8937$, RMSE=3.76$^{\circ}C$; Quadratic method, $R^2=0.8967$, RMSE=2.949$^{\circ}C$. Because Landsat TM has only one band for extracting surface temperature, it was difficult to correct for the atmospheric errors. For improving the accuracy of surface temperature detection using Landsat TM, there is a need for a method to decrease the effect of atmospheric contents.