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

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.4 no.2
• /
• pp.27-41
• /
• 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 Association of Geographic Information Studies
• /
• v.4 no.1
• /
• pp.18-26
• /
• 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.

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

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

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.2 no.1
• /
• pp.9-15
• /
• 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
• /
• 2008.05a
• /
• pp.2081-2084
• /
• 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 Association of Geographic Information Studies
• /
• v.2 no.3
• /
• pp.71-80
• /
• 1999

The aim of the present study is to define and tentatively to interpret the distribution of polluted water released from Lake Sihwa into the Yellow Sea using Landsat TM. Since the region is an extreme Case 2 water, empirical algorithms for detecting concentration of chlorophyll-a and suspended sediments have limitations. This work focuses on the use of multi-temporal Landsat TM data. We applied PCA to detect evolution of spatial feature of polluted water after release from the lake Sihwa. The PCA results were compared with in situ data, such as chlorophyll-a, suspended sediments, Secchi disk depth(SDD), surface temperature, remote sensing reflectance at six channel of SeaWiFS. Also, the in situ remote sensing reflectance obtained by PRR-600(Profiling Reflectance Radiometer) was compared with PCA results of Landsat TM data sets to find 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. Therefore, Problems in applying PCA techniques to multi-spectral remotely sensed data were also discussed in this paper.

• Economic and Environmental Geology
• /
• v.28 no.4
• /
• pp.405-414
• /
• 1995

An algorithm for monitoring geomorphological change using remote sensing data is investigated and tested using two LANDSAT TM data sets acquired over the Kyunggi Bay on April 15 1986 and September 22 1992, respectively. The algorithm exploits change vector analysis and tasseled cap transform. Although change vector analysis is effective for change detection, efficiency is decreased as the number of variables are increased. In this algorithm, we overcome the problem by utilizing the tasseled cap transform which can reduce six bands of LANDSAT TM data into only two components called Brightness and Greenness. The test results demonstrate that the algorithm is very effective in monitoring small-scaled changes over coastal area as well as significant changes in geomorphology. The resulting change vector image, however, is more sensitive to the changes occurred by human activities than by pure geological processes mainly because of relatively short time interval between two LANDSAT TM data sets.

• Ocean Science Journal
• /
• v.41 no.2
• /
• pp.97-104
• /
• 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.