• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.2
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• pp.123-131
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• 2011

Characteristics of sea surface temperature(SST) difference around Gwang-Yang steel Mill where can affect marine ecosystem in Gwang-Yang bay using 25 collected Landsat-7 ETM+ thermal infrared band data from 2000 to 2010. To analyze accuracy of SST from the Landsat-7 ETM+ thermal infrared image， satellite-induced SST was verfied by compared Yeo-Su tide station and Landsat thermal image. As a result, SST from Landsat-7 ETM+ is $1.22^{\circ}C$ lower than sea temperature from Yeo-Su tide station and correlation coefficient resulted in above 0.991 which means that correlation coefficient between Landsat image temperature and field sea temperature is relatively high. Five regions were selected to analyze sea surface temperature between near Gwang-Yang steel mill and the open sea and analyzed timeseries of sea surface temperature seasonally and regionally. Moreover, the additional analysis has been carried out by comparing the averaged temperatures of Gwang-Yang and Soon-Cheon bays using the dataset over a year.

• Korean Journal of Remote Sensing
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• v.27 no.4
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• pp.435-444
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• 2011

The land cover map derived from spectral features of high resolution optical images has low spectral resolution and heterogeneity in the same land cover class. For this reason, despite the same land cover class, the land cover can be classified into various land cover classes especially in vegetation area. In order to overcome these problems, detailed vegetation classification is applied to optical satellite image and SAR(Synthetic Aperture Radar) integrated data in vegetation area which is the result of pre-classification from optical image. The pre-classification and vegetation classification were performed with MLC(Maximum Likelihood Classification) method. The hierarchical land cover classification was proposed from fusion of detailed vegetation classes and non-vegetation classes of pre-classification. We can verify the facts that the proposed method has higher accuracy than not only general SAR data and GLCM(Gray Level Co-occurrence Matrix) texture integrated methods but also hierarchical GLCM integrated method. Especially the proposed method has high accuracy with respect to both vegetation and non-vegetation classification.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.158-174
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• 2018

The leaf area index (LAI) is a major factor explaining the photosynthesis of vegetation, evapotranspiration, and energy exchange between the earth surface and atmosphere, and there have been studies on accurate and applicable LAI estimation methods. This study aimed to investigate the relationship between the actual LAI data, UAV image-based vegetation index, canopy height and satellite image (Sentinel-2) LAI and to present an effective LAI estimation method using UAV. As a result, among the six vegetation indices in this study, NDRE ($R^2=0.496$) and CIRE ($R^2=0.443$), which contained red-edge band, showed a high correlation. The application of the canopy height model data to the vegetation index improved the explanatory power of the LAI. In addition, in the case of NDVI, the saturation problem caused by the linear relationship with LAI was addressed. In this study, it was possible to estimate high resolution LAI using UAV images. It is expected that the applicability of such data will be improved if calibration and correction steps are carried out for various vegetation and seasonal images.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1015-1023
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• 2022

The Entry-Descent-Landing process of a lander involves many environmental and technical challenges. To solve these problems, recently, terrestrial relative navigation (TRN) technology has been essential for landers. TRN is a technology for estimating the position and attitude of a lander by comparing Inertial Measurement Unit (IMU) data and image data collected from a descending lander with pre-built reference data. In this paper, we present a method for generating descent dataset and extracting landmarks, which are key elements for developing TRN technologies to be used on Mars. The proposed method generates IMU data of a descending lander using a simulated Mars landing trajectory and generates descent images from high-resolution ortho-map and digital elevation map through a ray tracing technique. Landmark extraction is performed by an area-based extraction method due to the low-textured surfaces on Mars. In addition, search area reduction is carried out to improve matching accuracy and speed. The performance evaluation result for the descent dataset generation method showed that the proposed method can generate images that satisfy the imaging geometry. The performance evaluation result for the landmark extraction method showed that the proposed method ensures several meters of positioning accuracy while ensuring processing speed as fast as the feature-based methods.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.979-995
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• 2023

As wildfires are difficult to predict, real-time monitoring is crucial for a timely response. Geostationary satellite images are very useful for active fire detection because they can monitor a vast area with high temporal resolution (e.g., 2 min). Existing satellite-based active fire detection algorithms detect thermal outliers using threshold values based on the statistical analysis of brightness temperature. However, the difficulty in establishing suitable thresholds for such threshold-based methods hinders their ability to detect fires with low intensity and achieve generalized performance. In light of these challenges, machine learning has emerged as a potential-solution. Until now, relatively simple techniques such as random forest, Vanilla convolutional neural network (CNN), and U-net have been applied for active fire detection. Therefore, this study proposed an active fire detection algorithm using state-of-the-art (SOTA) deep learning techniques using data from the Advanced Himawari Imager and evaluated it over East Asia and Australia. The SOTA model was developed by applying EfficientNet and lion optimizer, and the results were compared with the model using the Vanilla CNN structure. EfficientNet outperformed CNN with F1-scores of 0.88 and 0.83 in East Asia and Australia, respectively. The performance was better after using weighted loss, equal sampling, and image augmentation techniques to fix data imbalance issues compared to before the techniques were used, resulting in F1-scores of 0.92 in East Asia and 0.84 in Australia. It is anticipated that timely responses facilitated by the SOTA deep learning-based approach for active fire detection will effectively mitigate the damage caused by wildfires.

• Korean Journal of Remote Sensing
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• v.18 no.4
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• pp.209-220
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• 2002

We carried out studies on SAR image intensity and interferometric phase over oyster sea farms. Strong backscattering was observed in amplitude images, and that was considered as a radar signal double bouncing from horizontal bars. These sea farming structures are not visible in satellite optical images except IKONOS image, so that it demonstrates the value of radar remote sensing as an effective tool in support of sea farm detection. The intensity of the image is sensitive to system parameters including wavelength, polarization, and look direction, but does not correlate to tide height. We found that the strongest backscattering can be obtained by L-band HH-polarization with a look direction perpendicular to the horizontal bar. We also succeeded in generating 21 coherent JERS-1 SAR interferometric pairs over the oyster farms. The general trend of the fringe rate of the interferometric phases appeared to be governed by altitude of ambiguity. The general trend was modeled by an inverse function and removed to have a residual phase. The residual phase showed a linear relation with the tide height. The results demonstrate for the first time that SAR can possibly be used to estimate sea level. However, the r.m.s. error of a regression line is 11.7 cm, and that is so far too large to make reliable assessments of sea level in practical applications. Further studies is required to improve the accuracy specifically using multi-polarization SAR data.

• Journal of the Korean Society of Marine Environment & Safety
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• v.22 no.5
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• pp.508-520
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• 2016

In this study, variations in water temperature after the passage of typhoons in Korean waters from 2009-2015 were analyzed. Sea surface temperature (SST) images derived from satellite remote sensing data were used, and water temperature information came from real-time mooring buoys at Yangyang, Gangneung, Samcheok and Yeoungdeok, while wind data was supplied by the Korea Meteorological Administration. Differences in SST observed before and after the passage of a typhoon using the SST images were found to be affected by wind direction as well as hot and cool seasonal tendencies. Coastal water temperatures of the eastern part of the Korean peninsula, located to the right of a typhoon, as in the case of typhoons Muifa, Chanhom, Nakri and Tembin, were lowered by a coastal upwelling system from southerly winds across the water's surface at depths of 15m and 25m. In particular, typhoons Chanhom and Tembin decreased water temperatures by about $8-11^{\circ}C$ and $16^{\circ}C$, respectively. However, temperatures to the left of the typhoons were increased by a downwelling of offshore seawater with a high temperature through the mid and lower seawater layers. After the passage of the typhoons, further mixing of seawater at a higher or lower temperature due to southerly or northerly winds, according to the context, lasted for 1-2 or 4 days, respectively.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.11a
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• pp.393-398
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• 2004

It is transformed map data of different coordinate system into unique system and We triedto make topographic map on non-accessible area. We transformed Russian map coordinates(Krassovsky, G-K projection) intoWGS-84, TM projection and assessed accuracy. The RMSE(in East and West bearings : ${\pm}$13.67m, in North and South bearings ： ${\pm}$14.67m) using only SCP(Survey Control Point) is more accurate than that(in East and West bearings ： ${\pm}$24.26m, in North and South bearings : ${\pm}$25.32m) using SCP, intersection of road, bridge. Exterior orientation parameters are estimated using rigorous modelling and GCPs are classified with SCP, intersection of road, bridge. Rigorous modelling is performed with each classified GCP. The modelling result usingonly SCP(in East and West bearings : ${\pm}$13.53m, in North and South bearings ： ${\pm}$14.22m) is more accurate than that using intersection of road(in East and West bearings ： ${\pm}$16.l1m, in North and South bearings： ${\pm}$23.85m), bridge(in East and West bearings : ${\pm}$17.21m, in North and South bearings : ${\pm}$21.82m). The results means that SCP is more accurate than intersection of road, bridge because of edit to generate map. therefore, SCP is suitable for object of GCP in paper map(1:50,000). Geographic information on non-accessible area and analysis is performed. The results of stereoscopic plotting is well matched old map data on road, railroad but, many objects are generally editted. It is possible to update on new objects(building, tributary ‥‥etc). Ability of description using SPOT-5(stereo) is more than features and items included in 1:50,000 topographic map. Therefore, it is possible to make large scale map than 1:50,000 topographic map using SPOT-5 imagery. But, there are many problems(accurate GCPs, obtain of high resolution stereoscopic satellite imagery in a period ‥‥ etc) to make topographic map on non-accessible area. It is actually difficult to solve these problems. therefore, it is possible to update 1:50,000 topographic map in part of topographic map generation.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.1
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• pp.65-71
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• 2015

Red Tide phenomenon which happens in the southern coast of Korea gives massive damage to the fishermen who run fish farms and thereby a lot of efforts to prevent damage are made from various angles. In particular, red tide monitoring with satellite imagery can make it possible to obtain the occurrence data of red tide throughout the whole areas of the sea, which helps provide important information for establishing the preventive plans of disasters. In this regard, this study selected the South Sea of Gyeongnam Province with a view to suggesting the monitoring results with regard to the spread and reduction of the Red Tide in the middle of the day by using the GOCI Images of COMS. With this intention, it selected the region in the South Sea of Gyeongnam Province. The study results of analysis on the GOCI image data for the years of 2013(Aug. 12) and 2014 (Sep. 11) are as follows: the pattern of the Red Tide in the region of the South Sea occurred in the southern sea area of Geoje-do in the morning. It gradually spread and showed a gradual decline after reaching the top at 1 PM. In addition, in terms of the tide movement in the middle of the day, Red Tide began in the southern sea area and moved to the west, and moved to the east again at noon. It is judged that additional study on many factors such as the characteristics of the future Red-tide organisms, tidal currents, amount of sunshine, and water temperature is needed, but it is estimated that Red Tide movement monitoring with GOCI images would provide very crucial information for predicting the spread and movement of the Red Tide to protect and manage the Red Tide disasters.

• Korean Journal of Remote Sensing
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• v.33 no.3
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• pp.287-299
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• 2017

The Southern Volcanic Zone (SVZ) of Chile consists of many volcanoes, including the Mt.Villarrica and Mt.Llaima, and the two volcanoes are covered with snow at the top of Mountain. The purpose of this study is to analyze the relationship between the ice caps and the volcanic activity of the two volcanoes for 25 years by using the satellite image data are available in a time series. A total of 60 Landsat-5 TM and Landsat-7 ETM + data were used for the study from September 1986 to February 2011. Using NDSI (Normalized Difference Snow Index) algorithm and SRTM DEM, snow cover and snowline were extracted. Finally, the snow cover area, lower-snowline, and upper-snowline, which are quantitative indicators of snow cover change, were directly or indirectly affected by volcanic activity, were extracted from the satellite images. The results show that the volcanic activity of Villarrica volcano is more than 55% when the snow cover is less than 20 and the lower-snowline is 1,880 m in Llaima volcano. In addition, when the upper-snowline of the two volcanoes is below -170m, it can be confirmed that the volcano is differentiated with a probability of about 90%. Therefore, the changes in volcanic snowfall are closely correlated with volcanic activity, and it is possible to indirectly deduce volcanic activity by monitoring the snow.