• Korean Journal of Remote Sensing
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• v.36 no.3
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• pp.487-501
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• 2020

As a viable option for retrieval of LST (Land Surface Temperature), this paper presents a DNN (Deep Neural Network) based approach using 148 Landsat 8 images for South Korea. Because the brightness temperature and emissivity for the band 10 (approx. 11-㎛ wavelength) of Landsat 8 are derived by combining physics-based equations and empirical coefficients, they include uncertainties according to regional conditions such as meteorology, climate, topography, and vegetation. To overcome this, we used several land surface variables such as NDVI (Normalized Difference Vegetation Index), land cover types, topographic factors (elevation, slope, aspect, and ruggedness) as well as the T₀ calculated from the brightness temperature and emissivity. We optimized four seasonal DNN models using the input variables and in-situ observations from ASOS (Automated Synoptic Observing System) to retrieve the LST, which is an advanced approach when compared with the existing method of the bias correction using a linear equation. The validation statistics from the 1,728 matchups during 2013-2019 showed a good performance of the CC=0.910~0.917 and RMSE=3.245~3.365℃, especially for spring and fall. Also, our DNN models produced a stable LST for all types of land cover. A future work using big data from Landsat 5/7/8 with additional land surface variables will be necessary for a more reliable retrieval of LST for high-resolution satellite images.

• 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.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.2 no.1
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• pp.5-16
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• 1984

This study is about land cover mapping (land use mapping) and change for a period of years in urban area by use of satellite (LANDSAT) data. Definitely, land cover map in 1979 and 1983 of Seoul which has eminant increase of population were produced and change of land cover map for 4 years was considered. The redeveloped software and procedure in this study make it possible to produce land cover maps of urban area in same condition regardless of difference in data acquisition day.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.4
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• pp.291-302
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• 2017

Radiometric calibration is a prerequisite to quantitative remote sensing, and its accuracy has a direct impact on the reliability and accuracy of the quantitative application of remotely sensed data. This paper presents absolute radiometric calibration of the KOMPSAT-3 (KOrea Multi Purpose SATellite-3) and cross calibration using the Landsat-8 OLI (Operational Land Imager). Absolute radiometric calibration was performed using a reflectance-based method. Correlations between TOA (Top Of Atmosphere) radiances and the spectral band responses of the KOMPSAT-3 sensors in Goheung, South Korea, were significant for multispectral bands. A cross calibration method based on the Landsat-8 OLI was also used to assess the two sensors using near simultaneous image pairs over the Libya-4 PICS (Pseudo Invariant Calibration Sites). The spectral profile of the target was obtained from EO-1 (Earth Observing-1) Hyperion data over the Libya-4 PICS to derive the SBAF (Spectral Band Adjustment Factor). The results revealed that the TOA radiance of the KOMPSAT-3 agree with Landsat-8 within 5.14% for all bands after applying the SBAF. The radiometric coefficient presented here appears to be a good standard for maintaining the optical quality of the KOMPSAT-3.

• Korean Journal of Remote Sensing
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• v.29 no.4
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• pp.399-406
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• 2013

The quality of satellite imagery should be improved and stabilized to satisfy numerous users. The radiometric characteristics of an optical sensor can be a measure of data quality. In this study, a band aggregation technique and spectral response function of hyperspectral images are used to simulate multispectral images. EO-1 Hyperion and Landsat-8 OLI images acquired with about 30 minutes difference in overpass time were exploited to evaluate radiometric coefficients of OLI. Radiance values of the OLI and the simulated OLI were compared over three subsets covered by different land types. As a result, the index of agreement shows over 0.99 for all VNIR bands although there are errors caused by space/time and sensors.

• Journal of Korea Water Resources Association
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• v.48 no.2
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• pp.79-90
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• 2015

In this study, the water quality parameters of Geum-river were estimated using Landsat 8 satellite image data which had launched in March 2013. The goal of this research is to predict HAB and to monitor spatial pattern of total nitrogen (TN) and total phosphorus (TP) because both TN and TP are the dominant factors of the growth of harmful algal blooms (HABs). To investigate the relationship between satellite band reflectance and in situ measurement value, Pearson' correlation coefficient analysis was used. The band2, 3, 4 and 5 reflectance values among 11 bands of Landsat 8 were used which was highly associated with detecting TN and TP. The 20 in situ data set with satellite's overpass time were identified. TN showed positive relation with band 2 (0.48), band3 (0.62), band4 (0.57) at a significance level of p<0.05. TP also showed high correlation for band2 (0.59), band3 (0.59), band4 (0.58) at a significance level of p<0.01. The optimal regression equation models were constructed for TN and TP based on multiple regression equations. The estimated concentration based on derived regression equations of TN and TP were compared with in situ measurement data. Finally, the spatial pattern of the two parameters was able be monitored through mapping on November 12, 2013 and April 21, 2014.

• Ecology and Resilient Infrastructure
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• v.5 no.2
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• pp.88-93
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• 2018

In-situ water quality sampling is used for accurate water quality assessment. However, in-situ water quality sampling offers limited samples and requires much time and intensive labors. Remote sensing approach has recently applied for water quality assessment. It has shown the advantage of offering a synoptic view but also more efficient and economical. In this study, we utilized Landsat Imagery to estimate the water quality of the Tamsui River basin, considered as one of the most important rivers located in the north of Taiwan. In order to monitor water quality of Tamsui River basin, a linear regression relation between the value of spectral radiance and four water quality parameters are investigated with 38 water sampling stations. Through the regression model, we could estimate river pollution index (RPI) from the predicted value of four water quality parameters. By using RPI, we can examine the pollution level of Tamsui River. The accuracy of RPI conversion of this study ranged from 32.2% to 68.2%.

• Korean Journal of Remote Sensing
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• v.24 no.5
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• pp.417-425
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• 2008

An image-based atmospheric correction software ATC is implemented using MATLAB and SML (Spatial Modeler Language in ERDAS IMAGINE), and it was tested using Landsat TM/ETM+ data. This ATC has two main functional modules, which are composed of a semiautomatic type and an automatic type. The semi-automatic functional module includes the Julian day (JD), Earth-Sun distance (ESD), solar zenith angle (SZA) and path radiance (PR), which are programmed as individual small functions. For the automatic functional module, these parameters are computed by using the header file of Landsat TM/ETM+. Three atmospheric correction algorithms are included: The apparent reflectance model (AR), one-percent dark object subtraction technique (DOS), and cosine approximation model (COST). The ACT is efficient as well as easy to use in a system with MATLAB and SML.

• Korean Journal of Remote Sensing
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• v.3 no.1
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• pp.1-10
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• 1987

The study was performed to recognize the most preferable spectral chennels for discriminating geological materials using the portable radiometer. The portable radiometer covers the visible and short infrared regions from approximately 0.4 to 2.5 microns which are coincided with Landsat TM, and the rock samples used for the study are pyrophylites, andesites, granite, granodiorite and silicified sedimentary rocks which are collected in Yangsan-Dongrae fault area. The analysis of the rock sample provides a preliminary basis for determining the wavelength regions showing diagnostic spectral features and for discriminating hydrothermal altered rocks from the unaltered rocks. The measurement of spectral of spectral reflectance for the rock samples was carried out in the laboratory which environment condition such as temperature, light sources, and humidity are constant. The analysis of the measured data was based on correlation between the reflectance value of the rock samples, and the follow discriptions are output of the study. 1) Pyrophyllite shows absorption at 0.83 $\mu\textrm{m}$ due to the oxidation of pyrite, and absorption at 2.22 $\mu\textrm{m}$ due to OH. 2) The altered rocks have generally higher reflectance than the unaltered rocks. 3) The ratio mesurement of pyrophyllites shows strong absorption at band 5/6 and band 6/4(in Landsat TM 5/7, 7/4). The ratio 1/5(Landsat TM 1/5) may be useful to discriminate andesite from the granite.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.407-413
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• 2006

To investigate the streamflow impact of land cover changes by a typhoon, HEC-l storm runoff model was applied by using land cover information before and after the typhoon. The model was calibrated with three storm events of 1985 to 1988 based on 1985 land cover condition for a $192.7km^{2}$ watershed in northeast coast of South Korea. After the model was tested, it was run to estimate impacts of land cover change by the typhoon RUSA occurred in 2002 (31 August-1 September) with 897.5 mm rainfall. The land covers before and after the typhoon were prepared using Landsat 7 ETM+ of September 11 of 2000 and Landsat 5 TM of September 29 of 2002 respectively. For the $6.9km^{2}$ damaged area (3.6 % of the watershed), the peak runoff and total runoff by the changed land cover condition increased 12.5 % and 12.7 % for 50 years rainfall frequency and 1.4 % and 1.8 % for 500 years rainfall frequency respectively based on AMC (Antecedent Moisture Condition)-I condition.