• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.1
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• pp.115-127
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• 2024

This research aimed to construct models with various structures based on the Transformer module and to perform land cover classification, thereby examining the applicability of the Transformer module. For the classification of land cover, the Unet model, which has a CNN structure, was selected as the base model, and a total of four deep learning models were constructed by combining both the encoder and decoder parts with the Transformer module. During the training process of the deep learning models, the training was repeated 10 times under the same conditions to evaluate the generalization performance. The evaluation of the classification accuracy of the deep learning models showed that the Model D, which utilized the Transformer module in both the encoder and decoder structures, achieved the highest overall accuracy with an average of approximately 89.4% and a Kappa coefficient average of about 73.2%. In terms of training time, models based on CNN were the most efficient. however, the use of Transformer-based models resulted in an average improvement of 0.5% in classification accuracy based on the Kappa coefficient. It is considered necessary to refine the model by considering various variables such as adjusting hyperparameters and image patch sizes during the integration process with CNN models. A common issue identified in all models during the land cover classification process was the difficulty in detecting small-scale objects. To improve this misclassification phenomenon, it is deemed necessary to explore the use of high-resolution input data and integrate multidimensional data that includes terrain and texture information.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.325-338
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• 2023

Korean fir (Abies koreana Wilson) is one of the most important environmental indicator tree species for assessing climate change impacts on coniferous forests in the Korean Peninsula. However, due to the nature of alpine and subalpine regions, it is difficult to conduct regular field surveys of Korean fir, which is mainly distributed in regions with altitudes greater than 1,000 m. Therefore, this study analyzed the vegetation change trend of Korean fir using regularly observed remote sensing data. Specifically, normalized difference vegetation index (NDVI) from Moderate Resolution Imaging Spectroradiometer (MODIS), land surface temperature (LST), and precipitation data from Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievalsfor GPM from September 2003 to 2020 for Hallasan and Jirisan were used to analyze vegetation changes and their association with environmental variables. We identified a decrease in NDVI in 2020 compared to 2003 for both sites. Based on the NDVI difference maps, areas for healthy vegetation and high mortality of Korean fir were selected. Long-term NDVI time-series analysis demonstrated that both Hallasan and Jirisan had a decrease in NDVI at the high mortality areas (Hallasan: -0.46, Jirisan: -0.43). Furthermore, when analyzing the long-term fluctuations of Korean fir vegetation through the Hodrick-Prescott filter-applied NDVI, LST, and precipitation, the NDVI difference between the Korean fir healthy vegetation and high mortality sitesincreased with the increasing LST and decreasing precipitation in Hallasan. Thissuggests that the increase in LST and the decrease in precipitation contribute to the decline of Korean fir in Hallasan. In contrast, Jirisan confirmed a long-term trend of declining NDVI in the areas of Korean fir mortality but did not find a significant correlation between the changes in NDVI and environmental variables (LST and precipitation). Further analyses of environmental factors, such as soil moisture, insolation, and wind that have been identified to be related to Korean fir habitats in previous studies should be conducted. This study demonstrated the feasibility of using satellite data for long-term monitoring of Korean fir ecosystems and investigating their changes in conjunction with environmental conditions. Thisstudy provided the potential forsatellite-based monitoring to improve our understanding of the ecology of Korean fir.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.363-368
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• 2003

We have successfully developed a more effective algorithm to extract the lineament in the area covered by wide alluvial deposits characterized by a relatively narrow range of brightness in the Landsat TM image, while the currently used algorithm is limited to the mountainous areas. In the new algorithm, flat areas mainly consisting of alluvial deposits were selected using the Local Enhancement from the Digital Elevation Model (DEM). The aspect values were obtained by 3${\times}$3 moving windowing of Zevenbergen & Thorno's Method, and then the slopes of the study area were determined using the aspect values. After the lineament factors in the alluvial deposits were revealed by comparing the threshold values, the first rank lineament under the alluvial deposits were extracted using the Hough transform In order to extract the final lineament, the lowest points under the alluvial deposits in a given topographic section perpendicular to the first rank lineament were determined through the spline interpolation, and then the final lineament were chosen through Hough transform using the lowest points. The algorithm developed in this study enables us to observe a clearer lineament in the areas covered by much larger alluvial deposits compared with the results extracted using the conventional existing algorithm. There exists, however, some differences between the first rank lineament, obtained using the aspect and the slope, and the final lineament. This study shows that the new algorithm more effectively extracts the lineament in the area covered with wide alluvlal deposits than in the areas of converging slope, areas with narrow alluvial deposits or valleys.

• Journal of the Korean earth science society
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• v.40 no.5
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• pp.447-463
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• 2019

Sea surface wind is a fundamental element for understanding the oceanic phenomena and for analyzing changes of the Earth environment caused by global warming. Global research institutes have developed and operated scatterometers to accurately and continuously observe the sea surface wind, with the accuracy of approximately ${\pm}20^{\circ}$ for wind direction and ${\pm}2m\;s^{-1}$ for wind speed. Given that the spatial resolution of the scatterometer is 12.5-25.0 km, the applicability of the data to the coastal area is limited due to complicated coastal lines and many islands around the Korean Peninsula. In contrast, Synthetic Aperture Radar (SAR), one of microwave sensors, is an all-weather instrument, which enables us to retrieve sea surface wind with high resolution (<1 km) and compensate the sparse resolution of the scatterometer. In this study, we investigated the Geophysical Model Functions (GMF), which are the algorithms for retrieval of sea surface wind speed from the SAR data depending on each band such as C-, L-, or X-band radar. We reviewed in the simulation of the backscattering coefficients for relative wind direction, incidence angle, and wind speed by applying LMOD, CMOD, and XMOD model functions, and analyzed the characteristics of each GMF. We investigated previous studies about the validation of wind speed from the SAR data using these GMFs. The accuracy of sea surface wind from SAR data changed with respect to observation mode, GMF type, reference data for validation, preprocessing method, and the method for calculation of relative wind direction. It is expected that this study contributes to the potential users of SAR images who retrieve wind speeds from SAR data at the coastal region around the Korean Peninsula.

• Journal of the Korea Society of Computer and Information
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• v.19 no.9
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• pp.1-10
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• 2014

In this paper, we propose MPI gridding algorithm of LiDAR data that minimizes the communication between the cores. The LiDAR data collected from aircraft is a 3D spatial information which is used in various applications. Since there are many cases where the LiDAR data has too high resolution than actually required or non-surface information is included in the data, filtering the raw LiDAR data is required. In order to use the filtered data, the interpolation using the data structure to search adjacent locations is conducted to reconstruct the data. Since the processing time of LiDAR data is directly proportional to the size of it, there have been many studies on the high performance parallel processing system using MPI. However, previously proposed methods in parallel approach possess possible performance degradations such as imbalanced data size among cores or communication overhead for resolving boundary condition inconsistency. We conduct empirical experiments to verify the effectiveness of our proposed algorithm. The results show that the total execution time of the proposed method decreased up to 4.2 times than that of the conventional method on heterogeneous clusters.

• Korean Journal of Remote Sensing
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• v.36 no.3
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• pp.401-410
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• 2020

Recently, many studies have been conducted on the changing phenology on the Korean Peninsula due to global warming. However, because of the geographical characteristics, research on plant season in autumn, which is difficult to measure compared to spring season, is insufficient. In this study, all leaves that maple and fallen leaves were defined as 'Decay leaves' and decay leaf detection was performed based on the Landsat-8 satellite image. The first threshold value of decay leaves was calculated by using NDVI and the secondary threshold value of decay leaves was calculated using by NDWI and the difference of spectral characteristics with green leaves. POD, FAR values were used to verify accuracy of the dry leaf detection algorithm in this study, and the results showed high accuracy with POD of 98.619 and FAR of 1.203.

• Journal of Preventive Medicine and Public Health
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• v.42 no.5
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• pp.298-304
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• 2009

Objectives : The aim of this study was to investigate the association of blood pressure levels with the common carotid artery intima-media thickness (CCA-IMT) and carotid plaques. Methods : Data were obtained from 2,635 subjects, aged 50 years and over, who participated in the Community Health Survey (a population-based, cross-sectional study) in Dong-gu, Gwangju city between 2007 and 2008. Participants were categorized into three groups according to blood pressure levels; normotensives (<120/80 mmHg), prehypertensives (120-139/80-89 mmHg), and hypertensives ($\geq$140/90 mmHg). Prehypertensives were further categorized as low prehypertensives (120-129/80-84 mmHg) and high prehypertensives (130-139/85-89 mmHg). Carotid intima-media thickness and plaques were evaluated with a high-resolution B-mode ultrasound. Statistical analyses were performed using chi-square test, ANOVA, and multiple logistic regression. Results : Prehypertensives had significantly greater maximal CCA-IMT values than normotensives, with a multivariate adjusted odds ratio of 1.78 (95% CI=1.36-2.32) for abnormal CCA-IMT (maximal CCA-IMT$\geq$1.0 mm), and 1.45 (95% CI=1.19-1.77) for carotid plaques. The multivariate adjusted odds ratio of low prehypertensives was 1.64 (95% CI=1.21-2.21) for abnormal CCA-IMT, and 1.30 (95% CI=1.04-1.63) for carotid plaques compared with normotensives. Subject with hypertension had higher frequency of abnormal CCA-IMT (odds ratio, 2.18; 95% CI=1.49-3.18), and carotid plaques (odds ratio, 1.98; 95% CI=1.46-2.67) compared with normotensives after adjustment for other cardiovascular risk factors. Conclusions : Our results indicate that there is a significant increase in the prevalence of carotid atherosclerosis in subjects with prehypertension (even in low prehypertensives) compared with normotensive subjects. Further studies are required to confirm the benefits and role of carotid ultrasonography in persons with prehypertension.

• Korean Journal of Remote Sensing
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• v.36 no.2_2
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• pp.309-323
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• 2020

Estimation of chlorophyll a concentration (CHL) on coastal areas using remote sensing has been mostly performed through multi-spectral satellite image analysis. Recently, various studies using hyperspectral imagery have been attempted. In particular, airborne hyperspectral imagery is composed of hundreds of bands with a narrow band width and high spatial resolution, and thus may be more effective in coastal areas than estimation of CHL through conventional satellite image. In this study, comparative analysis of hyperspectral and satellite-based CHL images was performed to estimate CHL in coastal areas. As a result of analyzing CHL and seawater spectrum data obtained by field survey conducted on the south coast of Korea, the seawater spectrum with high CHL peaked near the wavelength bands of 570 and 680 nm. Using this spectral feature, a new band ratio of 570 / 490 nm for estimating CHL was proposed. Through regression analysis between band ratio and the measured CHL were generated new CHL empirical formula. Validation of new empirical formula using the measured CHL showed valid results, with R² of 0.70, RMSE of 2.43 mg m^-3, and mean bias of 3.46 mg m^-3. As a result of applying the new empirical formula to hyperspectral and satellite images, the average RMSE between hyperspectral imagery and the measured CHL was 0.12 mg m^-3, making it possible to estimate CHL with higher accuracy than multi-spectral satellite images. Through these results, it is expected that it is possible to provide more accurate and precise spatial distribution information of CHL in coastal areas by utilizing hyperspectral imagery.

• Korean Journal of Remote Sensing
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• v.36 no.5_2
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• pp.881-891
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• 2020

Recently, the Ministry of Land, Infrastructure and Transport and the Ministry of Science and ICT are developing the Land Observation Satellite (CAS-500) to meet increased demand for high-resolution satellite images. Expected image products of CAS-500 includes precision orthoimage, Digital Surface Model (DSM), change detection map, etc. The quality of these products is determined based on the geometric accuracy of satellite images. Therefore, it is important to make precision geometric corrections of CAS-500 images to produce high-quality products. Geometric correction requires the Ground Control Point (GCP), which is usually extracted manually using orthoimages and digital map. This requires a lot of time to acquire GCPs. Therefore, it is necessary to automatically extract GCPs and reduce the time required for GCP extraction and orthoimage generation. To this end, the Precision Image Processing (PIP) System was developed for CAS-500 images to minimize user intervention in GCP extraction. This paper explains the products, processing steps and the function modules and Database of the PIP System. The performance of the System in terms of processing speed, is also presented. It is expected that through the developed System, precise orthoimages can be generated from all CAS-500 images over the Korean peninsula promptly. As future studies, we need to extend the System to handle automated orthoimage generation for overseas regions.

• Journal of Korean Society for Atmospheric Environment
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• v.22 no.2
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• pp.259-266
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• 2006

A dual-channel glass coil sampling technique was used to measure hourly formaldehyde concentration in the ambient air. The dual-channel coil sampling assembly consists of three parts; an all-pyrex 28-turn coil made of 0.2-cm internal diameter glass tubing for gas-liquid contact and scrubbing of soluble gases, an inlet section upstream of the coil for introducing sample air and scrubbing solution, and a widened glass section downstream of the coil for gas-liquid separation. The scrubbing solution used was a dilute aqueous DNPH (dinitrophenylhydrazine) solution. Hourly concentration of formaldehyde was determined at a Gwangju semi-urban site during two intensive studies between September and October using the dual channel glass-coil/DNPH sampling technique and HPLC (High Performance Liquid Chromatography) analysis. The mean concentration was 1.7($0.4{\sim}4.7$) and 3.0($0.5{\sim}19.1$) ppbv for the September and October intensives, respectively, which are considerably low, compared to those measured in polluted urban areas around the world including several urban areas of Korea. The diurnal variation showed significant increase of formaldehyde in the daytime suggesting the dominance of formation of formaldehyde due to photochemical oxidation of methane and other hydrocarbons. An increase in the formaldehyde sometimes in the night might be due to an increase in primary source, i.e. traffic emissions. It was also found that rapid increase in formaldehyde levels from 3.0 to 19.1 ppbv in the afternoon on October 20 was due to plumes from burning of agricultural wastes such as rice straw and stubble. It is expected from the measurement data that the constructed dual-channel glass coil sampling system can be utilized for measuring atmospheric concentration of the formaldehyde with high time resolution.