• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1009-1029
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• 2023

Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R² of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R² of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.

• Journal of Ecology and Environment
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• v.41 no.3
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• pp.107-113
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• 2017

Background: As the habitat changes in Korea due to climate change, the emergence of disease-mediated vectors is increasing rapidly. Thus for the surveillance of mosquito- and chigger mite-borne disease, their seasonal prevalence and species composition were investigated at seven locations in Daegu, Gunwi and Sangju. Methods: Mosquitoes were collected twice every month from five collection sites using a black light and BG sentinel traps in Daegu and Gunwi from April through November. Chigger mites were investigated twice per month from wild rodents caught with Sherman live traps in Gunwi and Sangju from April through May and September through November. Results: A total of 2,361 female mosquitoes were collected. Cowshed (626 individuals, Trap index (TI) 44.7) and Kyungpook National University campus (846 individuals, TI 60.4) in Daegu had the highest number of mosquitoes in the black light and BG sentinel trap, respectively. The mosquitoes were collected more by BG sentinel trap than the black light trap. Nine mosquito species were trapped, and the Culex pipiens complex was the most commonly mosquito (1,397 individuals, 59.2%), followed by Anopheles sinensis (554 individuals, 23.5%). Anopheles sinensis (531 individuals, 51.9%) and Culex pipiens complex (1,142 individuals, 85.4%) were the most mosquitoes from black light and BG sentinel trap, respectively. In terms of seasonal prevalence, the highest abundance was in July, with 824 individuals collected. In chigger mites, eighty-one wild rodents of five species that are hosts of chigger mites were collected; among them, 53 and 25 individuals of Apodemus agrarius and Crocidura suaveolens, respectively were trapped. Leptotrombidium pallidum was a dominant species, with 2,467 individuals collected (67.8%). Conclusions: The mosquito was the dominant species in Culex pipiens complex and the highest in July and August. Apodemus agrarius was most abundant in wild rats and Leptotrombidium pallidum was dominant in the collected chigger mites.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.807-821
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• 2020

The objective of this study is to evaluate the applicability of representative spatio-temporal fusion models developed for the fusion of mid- and low-resolution satellite images in order to construct a set of time-series high-resolution images for crop monitoring. Particularly, the effects of the characteristics of input image pairs on the prediction performance are investigated by considering the principle of spatio-temporal fusion. An experiment on the fusion of multi-temporal Sentinel-2 and RapidEye images in agricultural fields was conducted to evaluate the prediction performance. Three representative fusion models, including Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), SParse-representation-based SpatioTemporal reflectance Fusion Model (SPSTFM), and Flexible Spatiotemporal DAta Fusion (FSDAF), were applied to this comparative experiment. The three spatio-temporal fusion models exhibited different prediction performance in terms of prediction errors and spatial similarity. However, regardless of the model types, the correlation between coarse resolution images acquired on the pair dates and the prediction date was more significant than the difference between the pair dates and the prediction date to improve the prediction performance. In addition, using vegetation index as input for spatio-temporal fusion showed better prediction performance by alleviating error propagation problems, compared with using fused reflectance values in the calculation of vegetation index. These experimental results can be used as basic information for both the selection of optimal image pairs and input types, and the development of an advanced model in spatio-temporal fusion for crop monitoring.

• Korean journal of applied entomology
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• v.57 no.3
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• pp.177-183
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• 2018

This study examined the seasonal, regional distribution of mosquito vectors related with disease vectors in the Jeju. From March to November, sample were collected from 11 points in four environmentally different sites in Jeju Island. Samples were collected twice a month using a black-light trap and a BG sentinel trap. Overall, five genera and seven species types of 6,042 female mosquitos were collected. Among the collected mosquitos, 4,159 (68.8%) and 1,348 (24.4%) were Culex pipiens and Aedes albopictus, respectively, making them the dominant species. Additionally, collection using the black light trap produced 72.8 entities per trap in Jungang-dong service center in the center of the city, which was the highest value, while the lowest amount of 1.4 per trap was recovered from the airport. When the BG sentinel trap was used, the largest recovery was observed in the port, where there were 71.7 entities per trap, while the lowest amount of 28.3 entities per trap was recovered at Gealmae Eco Park. The overall number of mosquitoes collected started to increase from May, and reached the largest value of 1,156 (19.1%) in August. Trapped mosquitoes are created 364 pools of up to 50 grains per pool, by season, by environmental, and by species. When the pools were used, no flaviviral infection was observed upon real time RT-PCR.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.15
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• pp.6691-6696
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• 2015

Background: Endometrial carcinoma is the most common gynecological cancer and its treatment is still controversial, especially in its early stages. There are conflicting data about the efficacy of retroperitoneal lymphadenectomy during abdominal hysterectomy and bilateral salpingoophrectomy treatment. Lymphadenectomy carries a risk of severe complications, especially in women with co-morbidities. Selective lymphadenectomy has been widely employed for staging evaluation of endometrial carcinoma because it is simple and seems to provide reliable data regarding nodal metastasis. This study was designed to evaluate accuracy of sentinel node sampling in detecting lymph node metastasis in primary endometrial carcinoma during staging laparotomy. Materials and Methods: Ninety-three women with endometrial carcinoma at high-risk for nodal metastasis were studied. During laparotomy, methylene blue dye was injected into sub-serosal myometrium, then retroperitoneal spaces were opened and blue lymph nodes within pelvic and para-aortic regions were removed as separate specimens for histopathological examination (sentinel lymph nodes = SLNs). Hysterectomy and selective lymphadenectomy then performed for all women included in this study. Results: Deposition of methylene dye into at least one lymph node was observed in 73.1% (68/93) of studied cases. 18.3% (17/93) of studied women had positive lymph node metastasis and 94.1% (16/17) of them had positive metastasis in SLNs. In this study, SNLs had 94.4% sensitivity and 100% specificity in prediction of lymph node metastasis. Mean number of lymph nodes removed from each case decreased when SLNs biopsy were taken. Conclusions: SLNs are the key lymph nodes in endometrial tumor metastasis and their involvement could be an indicator for whether or not complete systematic lymphadenectomy is needed during staging laparotomy.

• Journal of Breast Cancer
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• v.21 no.4
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• pp.433-4341
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• 2018

Purpose: This study aimed to evaluate the effects of sentinel lymph node biopsy (SLNB) on recurrence and survival after neoadjuvant chemotherapy (NAC) in breast cancer patients with cytology-proven axillary node metastasis. Methods: We selected patients who were diagnosed with invasive breast cancer and axillary lymph node metastasis and were treated with NAC followed by curative surgery between January 2007 and December 2014. We classified patients into three groups: group A, negative sentinel lymph node (SLN) status and no further dissection; group B, negative SLN status with backup axillary lymph node dissection (ALND); and group C, no residual axillary metastasis on pathology with standard ALND. Results: The median follow-up time was 51 months (range, 3-122 months) and the median number of retrieved SLNs was 5 (range, 2-9). The SLN identification rate was 98.3% (234/238 patients), and the false negative rate of SLNB after NAC was 7.5%. There was no significant difference in axillary recurrence-free survival (p=0.118), disease-free survival (DFS; p=0.578) or overall survival (OS; p=0.149) among groups A, B, and C. In the subgroup analysis of breast pathologic complete response (pCR) status, there was no significant difference in DFS (p=0.271, p=0.892) or OS (p=0.207, p=0.300) in the breast pCR and non-pCR patients. Conclusion: These results suggest that SLNB can be feasible and oncologically safe after NAC for cytology-determined axillary node metastasis patients and could help reduce arm morbidity and lymphedema by avoiding ALND in SLN-negative patients.

• Journal of the Korean Orthopaedic Association
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• v.54 no.6
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• pp.509-518
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• 2019

Purpose: Lymph node metastasis is a very important prognostic factor for all skin cancers and some sarcomas. A sentinel lymph node (SLN) biopsy is the most useful technique for identifying SLNs. Recently, a new generation of diagnostic tools, such as single photon emission computed tomography/computed tomography (SPECT/CT) and positron emission tomography/CT (PET/CT) enabled the detection of SLNs. This study compared the efficacy of PET/CT for detecting lymph node metastases with a SLN biopsy in a single medical center. Materials and Methods: From 2008 to 2018, 72 skin cancers of sarcoma patients diagnosed with some lymph node involvement in a whole body PET/CT reading were assessed. Patients suspected of lymph node metastasis were sent to biopsy and those suspected to be reactive lesions were observed. The analysis was performed retrospectively using the medical records, clinical information, PET/CT readings, and pathology results. Results: The age of patients ranged from 14 to 88 years and the mean follow-up period was 2.4 years. Twenty-two patients were suspected of a lymph node metastasis and confirmed. The sensitivity, specificity, positive predictive value and negative predictive value of PET/CT images in sarcoma and non-sarcoma tumors were increased significantly when the expert's findings were considered together. Conclusion: PET/CT is effective in detecting lymph node metastases.

• Journal of Environmental Impact Assessment
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• v.32 no.6
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• pp.463-472
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• 2023

The amount of damage and the area of damage to forest fires are increasing globally, and the effectiveness analysis of the restoration method after the damage is performed insufficient. This study calculated the area of forest fire damage was calculated using Sentinel-2B satellite images and stack map and the intensity of forest fire damage is analyzed according to the forest type. In addition, the vegetation index was calculated using various wavelength bands. Based on the results, the vegetation resilience by the restoration method was quantitatively. As results, areas with a high proportion of coniferous forests suffered high intensity forest fire damage, and areas with a relatively high ratio of mixed and broad-leaved forests tended to have low forest fire damage. Also, artificial forests showed a recovery of about 92.7% compared to before forest fires and natural forests showed a recovery of about 99.6% from the result of analyzing vegetation resilience in artificial and natural forests after forest fires. Accordingly, it was confirmed that natural forests after forest fire damage had superior vegetation resilience compared to artificial forests. It can be proposed that this study is meaningful in providing important information for efficiently restoring the affected target site and the selection criteria for trees to reduce forest fire damage through the evaluation of vegetation resilience by the intensity of forest fire damage and restoration methods.

• Journal of Korea Water Resources Association
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• v.57 no.5
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• pp.321-332
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• 2024

Understanding the status of surface cover in riparian zones is essential for river management and flood disaster prevention. Traditional survey methods rely on expert interpretation of vegetation through vegetation mapping or indices. However, these methods are limited by their ability to accurately reflect dynamically changing river environments. Against this backdrop, this study utilized satellite imagery to apply the Random Forest method to assess the distribution of vegetation in rivers over multiple years, focusing on the Naeseong Stream as a case study. Remote sensing data from Sentinel-2 imagery were combined with ground truth data from the Naeseong Stream surface cover in 2016. The Random Forest machine learning algorithm was used to extract and train 1,000 samples per surface cover from ten predetermined sampling areas, followed by validation. A sensitivity analysis, annual surface cover analysis, and accuracy assessment were conducted to evaluate their applicability. The results showed an accuracy of 85.1% based on the validation data. Sensitivity analysis indicated the highest efficiency in 30 trees, 800 samples, and the downstream river section. Surface cover analysis accurately reflects the actual river environment. The accuracy analysis identified 14.9% boundary and internal errors, with high accuracy observed in six categories, excluding scattered and herbaceous vegetation. Although this study focused on a single river, applying the surface cover classification method to multiple rivers is necessary to obtain more accurate and comprehensive data.

• Archives of Plastic Surgery
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• v.42 no.4
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• pp.497-499
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• 2015