• Title/Summary/Keyword: meteorological image

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Evaluating Applicability of Photochemical Reflectance Index using Airborne-Based Hyperspectral Image: With Shadow Effect and Spectral Bands Characteristics (항공 초분광 영상을 이용한 광화학반사지수 이용 가능성 평가: 그림자 영향 및 대체 밴드를 중심으로)

  • Ryu, Jae-Hyun;Shin, Jung Il;Lee, Chang Suk;Hong, Sungwook;Lee, Yang-Won;Cho, Jaeil
    • Korean Journal of Remote Sensing
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    • v.33 no.5_1
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    • pp.507-519
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    • 2017
  • The applications of NDVI (Normalized Difference Vegetation Index) as a vegetation index has been widely used to understand vegetation biomass and physiological activities. However, NDVI is not suitable way for monitoring vegetation stress because it is less sensitive to change in physiological state than biomass. PRI (Photochemical Reflectance Index) is well developed to present physiological activities of vegetation, particularly high-light-stress condition, and it has been adopted in several satellites to be launched in the future. Thus, the understanding of PRI performance and the development of analysis method will be necessary. This study aims to interpret the characteristics of light-stress-sensitive PRI in shadow areas and to evaluate the PRI calculated by other wavelengths (i.e., 488.9 nm, 553.6 nm, 646.9 nm, and 668.4 nm) instead of 570 nm that used in original PRI. Using airborne-based hyperspectral image, we found that PRI values were increased in shadow detection due to the reduction of high light induced physiological stress. However, the qualities of both PRI and NDVI data were dramatically decreased when the shadow index (SI) exceeded the threshold (SI<25). In addition, the PRI calculated using by 553.6 nm had best correlation with original PRI. This relationship was improved by multiple regression analysis including reflectances of RED and NIR. These results will be helpful to the understanding of physiological meaning on the application of PRI.

Study on Flood Prediction System Based on Radar Rainfall Data (레이더 강우자료에 의한 홍수 예보 시스템 연구)

  • Kim, Won-Il;Oh, Kyoung-Doo;Ahn, Won-Sik;Jun, Byong-Ho
    • Journal of Korea Water Resources Association
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    • v.41 no.11
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    • pp.1153-1162
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    • 2008
  • The use of radar rainfall for hydrological appraisal has been a challenge due to the limitations in raw data generation followed by the complex analysis needed to come up with precise data interpretation. In this study, RAIDOM (RAdar Image DigitalizatiOn Method) has been developed to convert synthetic radar CAPPI(Constant Altitude Plan Position Indicator) image data from Korea Meteorological Administration into digital format in order to come up with a more practical and useful radar image data. RAIDOM was used to examine a severe local rainstorm that occurred in July 2006 as well as two other separate events that caused heavy floods on both upper and mid parts of the HanRiver basin. A distributed model was developed based on the available radar rainfall data. The Flood Hydrograph simulation has been found consistent with actual values. The results show the potentials of RAIDOM and the distributed model as tools for flood prediction. Furthermore, these findings are expected to extend the usefulness of radar rainfall data in hydrological appraisal.

Creating Atmospheric Scattering Corrected True Color Image from the COMS/GOCI Data (천리안위성 해양탑재체 자료를 이용한 대기산란 효과가 제거된 컬러합성 영상 제작)

  • Lee, Kwon-Ho
    • Journal of the Korean Association of Geographic Information Studies
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    • v.16 no.1
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    • pp.36-46
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    • 2013
  • The Geostationary Ocean Color Imager (GOCI), the first geostationary ocean color observation instrument launched in 2010 on board the Communication, Ocean, and Meteorological Satellite (COMS), has been generating the operational level 1 data. This study describes a methodology for creating the GOCI true color image and data processing software, namely the GOCI RGB maker. The algorithm uses a generic atmospheric correction and reprojection technique to produce the color composite image. Especially, the program is designed for educational purpose in a way that the region of interest and image size can be determined by the user. By distributing software to public, it would maximize the understanding and utilizing the GOCI data. Moreover, images produced from the geostationary observations are expected to be an excellent tool for monitoring environmental changes.

Tracking Changes of Snow Area Using Satellite Images of Mt.Halla at an Altitude of 1,600 m (위성화상을 이용한 고도 1,600 m 이상의 한라산 적설 면적 변화 추적)

  • Han, Gyung Deok;Yoon, Seong Uk;Chung, Yong Suk;Ahn, Jinhyun;Lee, Seung-Jae;Kim, Yoon Seok;Min, Taesun
    • Journal of Environmental Science International
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    • v.31 no.10
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    • pp.815-824
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    • 2022
  • It is necessary to understand the amount of snowfall and area of snow cover of Mt. Halla to ensure the safety of mountaineers and to protect the ecosystem of Mt. Halla against climate change. However, there are not enough related studies and observation posts for monitoring snow load. Therefore, to supplement the insufficient data, this study proposes an analysis of snow load and snow cover using normalized-difference snow index. Using the images obtained from the Sentinel2 satellite, the normalized-difference snow index image of Mt. Halla could be acquired. This was examined together with the meteorological data obtained from the existing observatory to analyze the change in snow cover for the years 2020 and 2021. The normalized-difference snow index images showed a smaller snow pixel number in 2021 than that in 2020. This study concluded that 2021 may have been warmer than 2020. In the future, it will be necessary to continuously monitor the amount of snow and the snow-covered area of Mt. Halla using the normalized-difference snow index image analysis method.

Analysis of 2012 Spring Drought Using Meteorological and Hydrological Drought Indices and Satellite-based Vegetation Indices (기상 및 수문학적 가뭄지수와 위성 식생지수를 활용한 2012년 봄 가뭄 분석)

  • Ahn, So-Ra;Lee, Jun-Woo;Kim, Seong-Joon
    • KCID journal
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    • v.21 no.1
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    • pp.78-88
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    • 2014
  • This study is to analyze the 2012 spring drought of Korea using drought index and satellite image. The severe spring drought recorded in May of 2012 showed 36.4% of normal rainfall(99.5mm). The areas of west part of Gyeonggi-do and Chungcheong-do were particularly serious. The drought indices both the SPI(Standardized Precipitation Index) and WADI(WAter supply Drought Index) represented the drought areas from the end of May and to the severe drought at the end of June. The drought by SPI completely ended at the middle of July, but the drought by WADI continued severe drought in the agricultural reservoir watersheds of whole country even to the end of the July. On the other hand, the results by spatial NDVI(Normalized Difference Vegetation Index) and EVI(Enhanced Vegetation Index) data from Terra MODIS, both indices showed relatively low values around the areas of Sinuiju, Pyongyang, and west coast of North Korea and Gyeonggi-do and Chungcheong-do of South Korea indicating drought condition. Especially, the values of NDVI and EVI at Chungcheong-do were critically low in June compared to the normal year value.

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SATELLITE MONITORING OF OIL SPILLS CAUSED BY THE HEBEI SPIRIT ACCIDENT

  • Yang, Chan-Su;Yeom, Gi-Ho;Chang, Ji-Seong
    • Proceedings of the KSRS Conference
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    • 2008.10a
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    • pp.368-368
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    • 2008
  • Oil spills are a principal factor of the ocean pollution. The complicated problems involved in detecting oil spills are usually due to varying wind and sea surface condition such as ocean wave and current. The Hebei Spirit accident was happened in the west sea ($36^{\circ}$41'04" N, $126^{\circ}$03'12" E) near about 8 km distant from Tae-An, Korea on December 7, 2007. The aim of this work is to improve the detection and classification performance in order to define a more accurate training set and identifying the feature of oil spill region. This paper deals with an optimization technique for the detection and classification scheme using multi-frequency and multi-polarization SAR and optical image data sets of the oil spilled sea. The used image data are the ENVISAT ASAR WS and Radarsat-1 of C-band and ALOS PALSAR of L-band SAR data and KOMPSAT-2 optical images together with meteorological or oceanographic data. Both the theory and the experimental results obtained are discussed.

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Surface Heat Flux and Oceanic Heat Advection in Sendai Bay

  • Yang Chan-Su;Hanawa Kimio
    • Korean Journal of Remote Sensing
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    • v.22 no.1
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    • pp.11-24
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    • 2006
  • Coastal sea surface temperature (CSST) and meteorological data from January through December 1995 are used to estimate the net surface heat flux and heat content for Sendai Bay. The average annual surface heat flux in the area north of the bay is estimated to be $+35Wm^{-2}$, whereas the southwestern area is estimated to be $+56Wm^{-2}$. Therefore, the net surface heat flux shows a net gain of heat over the whole bay. The largest heat gain occurs near Matsukawaura, where the strong Kuroshio/Oyashio interaction produces anomalously cold SST and wind is more moderate than in other regions of Sendai Bay over most of the year. The lowest heat gain occurs around Tashiro Island, where the temperature difference between air and sea surface is lower and wind is stronger. The heat budget shows that both surface forcing and horizontal advection are potentially important contributors to the seasonal evolution of CSST in the bay. From the A VHRR and SeaWiFS data, it is found that offshore conditions between the bay and Eno Island are different due to the presence of the Ojika Peninsula. It is also shown that the temporal behaviors of SSTs in the bay are closely connected with the air-sea heat flux and offshore conditions.

Construction of Spatial Information Big Data for Urban Thermal Environment Analysis (도시 열환경 분석을 위한 공간정보 빅데이터 구축)

  • Lee, Jun-Hoo;Yoon, Seong-Hwan
    • Journal of the Architectural Institute of Korea Planning & Design
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    • v.36 no.5
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    • pp.53-58
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    • 2020
  • The purpose of this study is to build a database of Spatial information Bigdata of cities using satellite images and spatial information, and to examine the correlations with the surface temperature. Using architectural structure and usage in building information, DEM and Slope topographical information for constructed with 300 × 300 mesh grids for Busan. The satellite image is used to prepare the Normalized Difference Built-up Index (NDBI), Normalized Difference Vegetation Index (NDVI), Bare Soil Index (BI), and Land Surface Temperature (LST). In addition, the building area in the grid was calculated and the building ratio was constructed to build the urban environment DB. In architectural structure, positive correlation was found in masonry and concrete structures. On the terrain, negative correlations were observed between DEM and slope. NDBI and BI were positively correlated, and NDVI was negatively correlated. The higher the Building ratio, the higher the surface temperature. It was found that the urban environment DB could be used as a basic data for urban environment analysis, and it was possible to quantitatively grasp the impact on the architecture and urban environment by adding local meteorological factors. This result is expected to be used as basic data for future urban environment planning and disaster prevention data construction.

Developing a Solution to Improve Road Safety Using Multiple Deep Learning Techniques

  • Humberto, Villalta;Min gi, Lee;Yoon Hee, Jo;Kwang Sik, Kim
    • International Journal of Internet, Broadcasting and Communication
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    • v.15 no.1
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    • pp.85-96
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    • 2023
  • The number of traffic accidents caused by wet or icy road surface conditions is on the rise every year. Car crashes in such bad road conditions can increase fatalities and serious injuries. Historical data (from the year 2016 to the year 2020) on weather-related traffic accidents show that the fatality rates are fairly high in Korea. This requires accurate prediction and identification of hazardous road conditions. In this study, a forecasting model is developed to predict the chances of traffic accidents that can occur on roads affected by weather and road surface conditions. Multiple deep learning algorithms taking into account AlexNet and 2D-CNN are employed. Data on orthophoto images, automatic weather systems, automated synoptic observing systems, and road surfaces are used for training and testing purposes. The orthophotos images are pre-processed before using them as input data for the modeling process. The procedure involves image segmentation techniques as well as the Z-Curve index. Results indicate that there is an acceptable performance of prediction such as 65% for dry, 46% for moist, and 33% for wet road conditions. The overall accuracy of the model is 53%. The findings of the study may contribute to developing comprehensive measures for enhancing road safety.

Analysis of GPS Precipitable Water Vapor Variation During the Influence of a Typhoon EWINIAR (태풍 에위니아 영향력에서의 GPS 가강수량 변화 분석)

  • Song, Dong Seob;Yun, Hong Sic
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.6D
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    • pp.1033-1041
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    • 2006
  • In this study, we calculated a space-time variation of GPS precipitable water vapor using GPS meteorology technique during a progress of the typhoon EWINIAR had made an effect on Korean peninsular at 10 July, 2006. We estimated tropospheric dry delay and wet delay for one hourly using 22 GPS permanent stations and precipitable water vapor was conversed by using surface meteorological data. The Korean weighted mean temperature and air-pressure of versa-reduction to the mean sea level have been used for an accuracy improvement of GPS precipitable water vapor estimation. Finally, we compared MTSAT water vapor image, radar image and precipitable water vapor map during a passage of the typhoon EWINIAR.