• 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.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1231-1244
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• 2022

The frequency of exposure of field crops to stress situations is increasing due to abnormal weather conditions. In South Korea, large-scale diseases in representative paddy rice cultivation area were happened. There are limits to field investigation on the crop damage due to large-scale. Satellite-based remote sensing techniques are useful for monitoring crops in cities and counties, but the sensitivity of vegetation index measured from satellite under abnormal growth of crop should be evaluated. The goal is to evaluate satellite-based normalized difference vegetation index (NDVI) retrieved from different spatial scales using drone imagery. In this study, Sentinel-2 and Landsat-8 satellites were used and they have spatial resolution of 10 and 30 m. Drone-based NDVI, which was resampled to the scale of satellite data, had correlation of 0.867-0.940 with Sentinel-2 NDVI and of 0.813-0.934 with Landsat-8 NDVI. When the effects of bias were minimized, Sentinel-2 NDVI had a normalized root mean square error of 0.2 to 2.8% less than that of the drone NDVI compared to Landsat-8 NDVI. In addition, Sentinel-2 NDVI had the constant error values regardless of diseases damage. On the other hand, Landsat-8 NDVI had different error values depending on degree of diseases. Considering the large error at the boundary of agricultural field, high spatial resolution data is more effective in monitoring crops.

• 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.

• Journal of the Korean Association of Geographic Information Studies
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• v.2 no.3
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• pp.71-80
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• 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.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.1
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• pp.98-106
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• 2003

Because satellite images have the advantage of high resolution, multi-spectral, revisit and wide swath characteristics, it is increased to utilize satellite image and get information little by little in nowadays. In order to utilize remote sensed images effectively, it is necessary to process satellite images through many processing steps. Among them, geometric correction is essential step for satellite image processing. In this study, we constructed geometric correction data using LANDSAT satellite images. First, we extracted GCPs from maps and constructed database over the Korean peninsular. Second, LANDSAT satellite images, 165 scenes were corrected geometrically using GCP database. Finally, we made 7 mosaic images by means of geometric correction images over Korean peninsular. We think that constructed geometric correction data will be used for many application fields as basic data.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.4
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• pp.1-9
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• 2014

The interest group and corporation in Korea have cultivated Suaeda grass in the source area every year as a plan to prevent the yellow dust due to Chinese desertification. It needs the afforestation analysis about the research area to plan the greenbelt environment development in the region of yellow dust origin. Thus, this research analyzed the greenbelt environment based on Landsat 5 TM satellite image and Landsat 8 image to grasp and analyze the present of greenbelt environment development. And this research analyzed the inside of the salt desert to understand the detailed greenbelt environment and vegetation index. As a result, it represents that the afforestation was accomplished efficiently between 2009 and 2011, while the greenbelt area was decreased rapidly and bare soil was increased between 2011 and 2013. Through these results, we could recognize that it is in trouble about the greenbelt environment development after 2011 and it needs the project implementation using satellite image when the next afforestation project is planned henceforth.

• Korean Journal of Agricultural Science
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• v.47 no.1
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• pp.59-66
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• 2020

Particulate matter (PM) is regarded as a major threat to public health and safety in urban areas. Despite a variety of efforts to systemically monitor the distribution of PM, the limited amount of sampling sites may not provide sufficient coverage over the areas where the monitoring stations are not located in close proximity. This study examined the capacity of using remotely sensed data to estimate the PM10 and PM2.5 concentrations in Seoul, South Korea. Multiple linear regression models were developed using the multispectral band data from the Moderate-resolution imaging spectro-radiometer equipped on Terra (MODIS) and Operational Land Imager equipped on Landsat 8 (Landsat 8) and meteorological parameters. Compared to MODIS-derived models (r² = 0.25 for PM10, r² = 0.30 for PM2.5), the Landsat 8-derived models showed improved model reliabilities (r² = 0.17 to 0.57 for PM10, r² = 0.47 to 0.71 for PM2.5). Landsat 8 model-derived PM concentration and ground-truth PM measurements were cross-validated to each other to examine the capability of the models for estimating the PM concentration. The modeled PM concentrations showed a stronger correlation to PM10 (r = 0.41 to 0.75) than to PM2.5 (r = 0.14 to 0.82). Overall, the results indicate that Landsat 8-derived models were more suitable in estimating the PM concentrations. Despite the day-to-day fluctuation in the model reliability, several models showed strong correspondences of the modeled PM concentrations to the PM measurements.

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

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.7
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• pp.723-728
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• 2016

This study is analyzed the optical property of red tide pixel by using Landsat-7 ETM+, Landsat-8 OLI and COMS/GOCI image. In order to sample red tide pixel, Landsat-7, 8 true color image were used and obtained coordinate of red tide pixel in the true color image. Normalized water leaving radiance(nLw) and absorption coefficient were obtained from GOCI image in the same coordinate of the true color image. When red tide was not occurred the main absorption range was 412nm and 660nm but when red tide occurred it was 660nm and absorption coefficient in 412nm are drastically reduced. It made no difference of nLw spectrum between red tide pixel and non red tide pixel in nLw, but the absolute value of nLw was low than non red tide pixel, especially 660nm and 680nm wavelength sharply decrease.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.2 s.36
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• pp.63-68
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• 2006

Although it is more recommended to use satellite images for an accurate understanding of the natural environment over a large area, what should proceed obtaining such satellite images is to make basic model equations based firmly upon the on-land experiments and field experiments. It may be more accurate and objective to investigate correlations between satellite images and actual water quality factors obtained for the same area. Thus, this study was conducted in order to determined which band of Landsat ETM+ images is appropriate to estimate the density of chlorophyll-a in a closed laboratory without atmospheric interference, using pure water and sea water. As a result of this study, it was found that the best band that exhibited the highest degree of correlations among the compounded bands rated (B3-B4)/B2 in pure water and (B2+B4)/B3 in sea water. The correlation coefficient here is 0.9747 and 0.9892 respectively. Thus, compounding this band ran be quite useful for estimation density of Chlorophyll-a using Landsat ETM+ image data.