• Title/Summary/Keyword: 원격계산

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Uncertainties of SO2 Vertical Column Density Retrieval from Ground-based Hyper-spectral UV Sensor Based on Direct Sun Measurement Geometry (지상관측 기반 태양 직달광 관측장비의 초분광 자외센서로부터 이산화황 연직칼럼농도의 불확실성 분석 연구)

  • Kang, Hyeongwoo;Park, Junsung;Yang, Jiwon;Choi, Wonei;Kim, Daewon;Lee, Hanlim
    • Korean Journal of Remote Sensing
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    • v.35 no.2
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    • pp.289-298
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    • 2019
  • In this present study, the effects of Signal to Noise Ratio (SNR), Full Width Half Maximum (FWHM), Aerosol Optical Depth (AOD), $O_3$ Vertical Column Density ($O_3$ VCD), and Solar Zenith Angle (SZA) on the accuracy of sulfur dioxide Vertical Column Density ($SO_2$ VCD) retrieval have been quantified using the Differential Optical Absorption Spectroscopy (DOAS) method with the ground-based direct-sun synthetic radiances. The synthetic radiances produced based on the Beer-Lambert-Bouguer law without consideration of the diffuse effect. In the SNR condition of 650 (1300) with FWHM = 0.6 nm, AOD = 0.2, $O_3$ VCD = 300 DU, and $SZA=30^{\circ}$, the Absolute Percentage Difference (APD) between the true $SO_2$ VCD values and those retrieved ranges from 80% (28%) to 16% (5%) for the $SO_2$ VCD of $8.1{\times}10^{15}$ and $2.7{\times}10^{16}molecules\;cm^{-2}$, respectively. For an FWHM of 0.2 nm (1.0 nm) with the $SO_2$ VCD values equal to or greater than $2.7{\times}10^{16}molecules\;cm^{-2}$, the APD ranges from 6.4% (29%) to 6.2% (10%). Additionally, when FWHM, SZA, AOD, and $O_3$ VCD values increase, APDs tend to be large. On the other hand, SNR values increase, APDs are found to decrease. Eventually, it is revealed that the effects of FWHM and SZA on $SO_2$ VCD retrieval accuracy are larger than those of $O_3$ VCD and AOD. The SZA effects on the reduction of $SO_2$ VCD retrieval accuracy is found to be dominant over the that of FWHM for the condition of $SO_2$ VCD larger than $2.7{\times}10^{16}molecules\;cm^{-2}$.

Geographical Characteristics of PM2.5, PM10 and O3 Concentrations Measured at the Air Quality Monitoring Systems in the Seoul Metropolitan Area (수도권 지역 도시대기측정소 PM2.5, PM10, O3 농도의 지리적 분포 특성)

  • Kang, Jung-Eun;Mun, Da-Som;Kim, Jae-Jin;Choi, Jin-Young;Lee, Jae-Bum;Lee, Dae-Gyun
    • Korean Journal of Remote Sensing
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    • v.37 no.3
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    • pp.657-664
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    • 2021
  • In this study, we investigated the relationships between the air quality (PM2.5, PM10, O3) concentrations and local geographical characteristics (terrain heights, building area ratios, population density in 9 km × 9 km gridded subareas) in the Seoul metropolitan area. To analyze the terrain heights and building area ratios, we used the geographic information system data provided by the NGII (National Geographic Information Institute). Also, we used the administrative districts and population provided by KOSIS (Korean Statistical Information Service) to estimate population densities. We analyzed the PM2.5, PM10, and O3 concentrations measured at the 146 AQMSs (air quality monitoring system) within the Seoul metropolitan area. The analysis period is from January 2010 to December 2020, and the monthly concentrations were calculated by averaging the hourly concentrations. The terrain is high in the northern and eastern parts of Gyeonggi-do and low near the west coastline. The distributions of building area ratios and population densities were similar to each other. During the analysis period, the monthly PM2.5 and PM10 concentrations at 146 AQMSs were high from January to March. The O3 concentrations were high from April to June. The population densities were negatively correlated with PM2.5, PM10, and O3 concentrations (weakly with PM2.5 and PM10 but strongly with O3). On the other hand, the AQMS heights showed no significant correlation with the pollutant concentrations, implying that further studies on the relationship between terrain heights and pollutant concentrations should be accompanied.

Study of Feature Based Algorithm Performance Comparison for Image Matching between Virtual Texture Image and Real Image (가상 텍스쳐 영상과 실촬영 영상간 매칭을 위한 특징점 기반 알고리즘 성능 비교 연구)

  • Lee, Yoo Jin;Rhee, Sooahm
    • Korean Journal of Remote Sensing
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    • v.38 no.6_1
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    • pp.1057-1068
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    • 2022
  • This paper compares the combination performance of feature point-based matching algorithms as a study to confirm the matching possibility between image taken by a user and a virtual texture image with the goal of developing mobile-based real-time image positioning technology. The feature based matching algorithm includes process of extracting features, calculating descriptors, matching features from both images, and finally eliminating mismatched features. At this time, for matching algorithm combination, we combined the process of extracting features and the process of calculating descriptors in the same or different matching algorithm respectively. V-World 3D desktop was used for the virtual indoor texture image. Currently, V-World 3D desktop is reinforced with details such as vertical and horizontal protrusions and dents. In addition, levels with real image textures. Using this, we constructed dataset with virtual indoor texture data as a reference image, and real image shooting at the same location as a target image. After constructing dataset, matching success rate and matching processing time were measured, and based on this, matching algorithm combination was determined for matching real image with virtual image. In this study, based on the characteristics of each matching technique, the matching algorithm was combined and applied to the constructed dataset to confirm the applicability, and performance comparison was also performed when the rotation was additionally considered. As a result of study, it was confirmed that the combination of Scale Invariant Feature Transform (SIFT)'s feature and descriptor detection had the highest matching success rate, but matching processing time was longest. And in the case of Features from Accelerated Segment Test (FAST)'s feature detector and Oriented FAST and Rotated BRIEF (ORB)'s descriptor calculation, the matching success rate was similar to that of SIFT-SIFT combination, while matching processing time was short. Furthermore, in case of FAST-ORB, it was confirmed that the matching performance was superior even when 10° rotation was applied to the dataset. Therefore, it was confirmed that the matching algorithm of FAST-ORB combination could be suitable for matching between virtual texture image and real image.

Prediction of Prognosis to Concurrent Chemo-Radiotherapy by Standardized Uptake Value of $2-[18^F]$ Fluovo-2-Deoxy-D-Glucose for Nasopharyngeal Carcinomas (비인강암 환자의 예후에서 $2-[18^F]$ Fluoro-2-Deoxy-D-Glucose PET 영상에서 계산되는 Standardized Uptake Value의 의의)

  • Lee Sang-wook;Im Ki Chun;Nam Soon Yuhl;Kim Jae Seung;Choi Eun Kyung;Ahn Seung Do;Shin Seong Soo;Ryu Jin Sook;Kim Sang Yoon;Lee Bong-Jae;Choi Seung-Ho;Kim Sung-Bae;Moon Dae Hyuk
    • Radiation Oncology Journal
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    • v.23 no.1
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    • pp.9-16
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    • 2005
  • Purpose : To prospectively evaluate the use of positron emission tomography with the glucose analog fluoro-deoxyglucose (FDG-PET) to deoxyglucose (FDG-PET) to predict disease-free survival (DFS) after concurrent chemo-radiotherapy (CCRT) in patients with non-disseminated nasopharyngeal carcinoma (NPC). Materials and Methods : We studied 41 patients with non-disseminated NPC scheduled to undergo platinum-based CCRT were eligible for this study. Patients were studied by FDG-PET prior to the CCRT. FDG uptake of tumors were measured with the maximal standardized uptake value (SUV). Results : Complete response rate was $100\%$. In ten patients who presented with any component of treatment failure, the median $SUV_{max}$ was 8.55 (range: $2.49\~14.81$) in any component of failure and the median $SUV_{max}$ was 5.48 (range: $2.31\~26.07$) In the remaining patients without any such failure. Patients having tumors with high FDG uptake had a significantly lower 3-year DFS ($51\%\;{\nu}91\%$, p=0.0070) compared with patients having low uptake tumors. Conclusion : FDG uptake, as measured by the SUV, has potential value in predicting DFS in NPC treated by CCRT, High FDG uptake may be a useful parameter for Identifying patients requiring more aggressive treatment approaches.

Detection of Arctic Summer Melt Ponds Using ICESat-2 Altimetry Data (ICESat-2 고도계 자료를 활용한 여름철 북극 융빙호 탐지)

  • Han, Daehyeon;Kim, Young Jun;Jung, Sihun;Sim, Seongmun;Kim, Woohyeok;Jang, Eunna;Im, Jungho;Kim, Hyun-Cheol
    • Korean Journal of Remote Sensing
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    • v.37 no.5_1
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    • pp.1177-1186
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    • 2021
  • As the Arctic melt ponds play an important role in determining the interannual variation of the sea ice extent and changes in the Arctic environment, it is crucial to monitor the Arctic melt ponds with high accuracy. Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2), which is the NASA's latest altimeter satellite based on the green laser (532 nm), observes the global surface elevation. When compared to the CryoSat-2 altimetry satellite whose along-track resolution is 250 m, ICESat-2 is highly expected to provide much more detailed information about Arctic melt ponds thanks to its high along-track resolution of 70 cm. The basic products of ICESat-2 are the surface height and the number of reflected photons. To aggregate the neighboring information of a specific ICESat-2 photon, the segments of photons with 10 m length were used. The standard deviation of the height and the total number of photons were calculated for each segment. As the melt ponds have the smoother surface than the sea ice, the lower variation of the height over melt ponds can make the melt ponds distinguished from the sea ice. When the melt ponds were extracted, the number of photons per segment was used to classify the melt ponds covered with open-water and specular ice. As photons are much more absorbed in the water-covered melt pondsthan the melt ponds with the specular ice, the number of photons persegment can distinguish the water- and ice-covered ponds. As a result, the suggested melt pond detection method was able to classify the sea ice, water-covered melt ponds, and ice-covered melt ponds. A qualitative analysis was conducted using the Sentinel-2 optical imagery. The suggested method successfully classified the water- and ice-covered ponds which were difficult to distinguish with Sentinel-2 optical images. Lastly, the pros and cons of the melt pond detection using satellite altimetry and optical images were discussed.

GOCI-II Based Low Sea Surface Salinity and Hourly Variation by Typhoon Hinnamnor (GOCI-II 기반 저염분수 산출과 태풍 힌남노에 의한 시간별 염분 변화)

  • So-Hyun Kim;Dae-Won Kim;Young-Heon Jo
    • Korean Journal of Remote Sensing
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    • v.39 no.6_2
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    • pp.1605-1613
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    • 2023
  • The physical properties of the ocean interior are determined by temperature and salinity. To observe them, we rely on satellite observations for broad regions of oceans. However, the satellite for salinity measurement, Soil Moisture Active Passive (SMAP), has low temporal and spatial resolutions; thus, more is needed to resolve the fast-changing coastal environment. To overcome these limitations, the algorithm to use the Geostationary Ocean Color Imager-II (GOCI-II) of the Geo-Kompsat-2B (GK-2B) was developed as the inputs for a Multi-layer Perceptron Neural Network (MPNN). The result shows that coefficient of determination (R2), root mean square error (RMSE), and relative root mean square error (RRMSE) between GOCI-II based sea surface salinity (SSS) (GOCI-II SSS) and SMAP was 0.94, 0.58 psu, and 1.87%, respectively. Furthermore, the spatial variation of GOCI-II SSS was also very uniform, with over 0.8 of R2 and less than 1 psu of RMSE. In addition, GOCI-II SSS was also compared with SSS of Ieodo Ocean Research Station (I-ORS), suggesting that the result was slightly low, which was further analyzed for the following reasons. We further illustrated the valuable information of high spatial and temporal variation of GOCI-II SSS to analyze SSS variation by the 11th typhoon, Hinnamnor, in 2022. We used the mean and standard deviation (STD) of one day of GOCI-II SSS, revealing the high spatial and temporal changes. Thus, this study will shed light on the research for monitoring the highly changing marine environment.

Estimation of Fractional Urban Tree Canopy Cover through Machine Learning Using Optical Satellite Images (기계학습을 이용한 광학 위성 영상 기반의 도시 내 수목 피복률 추정)

  • Sejeong Bae ;Bokyung Son ;Taejun Sung ;Yeonsu Lee ;Jungho Im ;Yoojin Kang
    • 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.

Hypofractionated Radiation Therapy for Early Glottic Cancer - Preliminary Results - (초기 성문암 환자에서의 소분할 조사법을 이용한 방사선치료 - 예비적 결과 -)

  • Wu Hong-Gyun;Hong Semie;Shin Seong Soo;Park Charn Il
    • Radiation Oncology Journal
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    • v.19 no.4
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    • pp.301-305
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    • 2001
  • Purpose : This study was peformed for the evaluation of the feasibility and toxicity of hypofractionated radiation therapy for early glottic cancer Methods and Materials : From February 1999 to February 2000, 20 patients with Histologically confirmed Stage I, II glottic cancer were enrolled into this study. There were 18 males and 2 females, the median age of the patients was 59 years. The distribution of stage distribution was as fellows; T1aN0-16 patients, T1bN0-1 patient, T2N0-3 patients. Eighteen patients underwent laryngomicroscopic biopsy only, and two patients underwent laser cordectomy. All patients received radical radiation therapy (2.5 Gy per fraction, 24 fractions, total 60 Gy). Median duration of treatment was 36 days (range $31\~45\;days$). Results : Radiation therapy were well tolerated. Most common acute reactions were odynophagia and hoarseness, and these reactions resolved after radiation therapy. There were one case of RTOG grade 3 odynophagia $(5\%)$, six cases of grade 3 hoarseness $(30\%)$. Response of radiation therapy was evaluated one month after completion of treatment. All patients revealed complete response. During follow up, total three cases of treatment failure were detected. two cases were local recurrence in 10 and 13 months of radiation therapy and one case was local recurrence and distant metastasis in 2 months of radiation therapy. Conclusion : This hypofractionated radiation therapy schedule was feasible and effective for control of early glottic cancer But longer follow up time would be required to assess the long-term disease control and the late complication by shortening radiation therapy duration.

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Variability of Satellite-derived Chlorophyll-a Concentration in Relation to Indian Ocean Dipole (IOD) Variation (인도양 쌍극진동 변동에 따른 위성에서 추정된 표층 클로로필-a 농도 변화 연구)

  • Son, Young Baek;Kim, Suk Hyun;Kim, Sang-Hyun;Rho, TaeKeun
    • Korean Journal of Remote Sensing
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    • v.33 no.6_1
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    • pp.917-930
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    • 2017
  • To understand the temporal and spatial variations of surface chlorophyll-a concentration (Chl-a) distribution in the Indian Ocean ($30^{\circ}E{\sim}120^{\circ}E$, $30^{\circ}S{\sim}30^{\circ}N$) by the Indian Ocean Dipole (IOD), we conducted EOF and K means analyses of monthly satellite-derived Chl-a data in the region during 1998~2016 periods. Chl-a showed low values in the central region of the Indian Ocean and relatively high values in the upwelling region and around the marginal regions of the Indian Ocean. It also had a strong seasonal variation of Chl-a, showing the lowest value in the spring and the highest value in summer due to the change of the monsoon and current system. The EOF analysis showed that Chl-a variation in EOF mode 1 is related to ENSO (El $Ni{\tilde{n}}o$/Southern Oscillation) and that of mode 2 is linked to IOD. Both modes explained spatially opposite trends of Chl-a in the east and west Indian Ocean. From K means analysis, the Chl-a variation in the east and west Indian Ocean, and around India have relatively good relationship with IOD while that in the tropical and middle Indian Ocean closely associated with ENSO. The spatial and temporal distribution of Chl-a also showed distinct spatial and temporal variations depend on the different types of IOD events. IOD classifies two patterns, which occurred during the developing ENSO (First Type IOD) and the year following ENSO event (Second Type IOD). Chl-a variation in the First Type IOD started in summer and peaked in fall around the east and west Indian Ocean. Chl-a variation in the Second Type IOD occurred started in spring, peaked in summer and fall, and disappeared in winter. In the Chl-a variation related to IOD, developing process appearing in the Chl-a difference between the east and west Indian ocean was similar. Chl-a variation in the northern Indian Ocean were opposite trend with changing developing phase of IOD.

Improvement of infrared channel emissivity data in COMS observation area from recent MODIS data(2009-2012) (최근 MODIS 자료(2009-2012)를 이용한 천리안 관측 지역의 적외채널 방출률 자료 개선)

  • Park, Ki-Hong;Suh, Myoung-Seok
    • Korean Journal of Remote Sensing
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    • v.30 no.1
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    • pp.109-126
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    • 2014
  • We improved the Land Surface Emissivity (LSE) data (Kongju National University LSE v.2: KNULSE_v2) over the Communication, Ocean and Meteorological Satellite (COMS) observation region using recent(2009-2012) Moderate Resolution Imaging Spectroradiometer (MODIS) data. The surface emissivity was derived using the Vegetation Cover Method (VCM) based on the assumption that the pixel is only composed of ground and vegetation. The main issues addressed in this study are as follows: 1) the impacts of snow cover are included using Normalized Difference Snow Index (NDSI) data, 2) the number of channels is extended from two (11, 12 ${\mu}m$) to four channels (3.7, 8.7, 11, 12 ${\mu}m$), 3) the land cover map data is also updated using the optimized remapping of the five state-of-the-art land cover maps, and 4) the latest look-up table for the emissivity of land surface according to the land cover is used. The updated emissivity data showed a strong seasonal variation with high and low values for the summer and winter, respectively. However, the surface emissivity over the desert or evergreen tree areas showed a relatively weak seasonal variation irrespective of the channels. The snow cover generally increases the emissivity of 3.7, 8.7, and 11 ${\mu}m$ but decreases that of 12 ${\mu}m$. As the results show, the pattern correlation between the updated emissivity data and the MODIS LSE data is clearly increased for the winter season, in particular, the 11 ${\mu}m$. However, the differences between the two emissivity data are slightly increased with a maximum increase in the 3.7 ${\mu}m$. The emissivity data updated in this study can be used for the improvement of accuracy of land surface temperature derived from the infrared channel data of COMS.