• Title/Summary/Keyword: 다중시기 영상분석

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NDVI Based on UAVs Mapping to Calculate the Damaged Areas of Chemical Accidents (화학물질사고 피해영역 산출을 위한 드론맵핑 기반의 정규식생지수 활용방안 연구)

  • Lim, Eontaek;Jung, Yonghan;Kim, Seongsam
    • Korean Journal of Remote Sensing
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    • v.38 no.6_3
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    • pp.1837-1846
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    • 2022
  • The annual increase in chemical accidents is causing damage to life and the environment due to the spread and residual of substances. Environmental damage investigation is more difficult to determine the geographical scope and timing than human damage investigation. Considering the reality that there is a lack of professional investigation personnel, it is urgent to develop an efficient quantitative evaluation method. In order to improve this situation, this paper conducted a chemical accidents investigation using unmanned aerial vehicles(UAV) equipped with various sensors. The damaged area was calculated by Ortho-image and strength of agreement was calculated using the normalized difference vegetation index image. As a result, the Cohen's Kappa coefficient was 0.649 (threshold 0.7). However, there is a limitation in that analysis has been performed based on the pixel of the normalized difference vegetation index. Therefore, there is a need for a chemical accident investigation plan that overcomes the limitations.

Detecting Surface Changes Triggered by Recent Volcanic Activities at Kīlauea, Hawai'i, by using the SAR Interferometric Technique: Preliminary Report (SAR 간섭기법을 활용한 하와이 킬라우에아 화산의 2018 분화 활동 관측)

  • Jo, MinJeong;Osmanoglu, Batuhan;Jung, Hyung-Sup
    • Korean Journal of Remote Sensing
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    • v.34 no.6_4
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    • pp.1545-1553
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    • 2018
  • Recent eruptive activity at Kīlauea Volcano started on at the end of April in 2018 showed rapid ground deflation between May and June in 2018. On summit area Halema'uma'u lava lake continued to drop at high speed and Kīlauea's summit continued to deflate. GPS receivers and electronic tiltmeters detected the surface deformation greater than 2 meters. We explored the time-series surface deformation at Kīlauea Volcano, focusing on the early stage of eruptive activity, using multi-temporal COSMO-SkyMed SAR imagery. The observed maximum deformation in line-of-sight (LOS) direction was about -1.5 meter, and it indicates approximately -1.9 meter in subsiding direction by applying incidence angle. The results showed that summit began to deflate just after the event started and most of deformation occurred between early May and the end of June. Moreover, we confirmed that summit's deflation rarely happened since July 2018, which means volcanic activity entered a stable stage. The best-fit magma source model based on time-series surface deformation demonstrated that magma chambers were lying at depths between 2-3 km, and it showed a deepening trend in time. Along with the change of source depth, the center of each magma model moved toward the southwest according to the time. These results have a potential risk of including bias coming from single track observation. Therefore, to complement the initial results, we need to generate precise magma source model based on three-dimensional measurements in further research.

Wintering Population Change of the Cranes according to the Climatic Factors in Cheorwon, Korea: Effect of the Snow Cover Range and Period by Using MODIS Satellite Data (기후요인에 의한 철원지역 두루미류 월동개체수 변화 - MODIS 위성영상을 이용한 눈 덮임 범위와 지속기간의 영향 -)

  • Yoo, Seung-Hwa;Lee, Ki-Sup;Jung, Hwa-Young;Kim, Hwa-Jung;Hur, Wee-Haeng;Kim, Jin-Han;Park, Chong-Hwa
    • Korean Journal of Ecology and Environment
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    • v.48 no.3
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    • pp.176-187
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    • 2015
  • In this study, we hypothesized that the size of wintering crane population would change due to the climate factors. We assumed that wintering population size would differ by climate values in January, which is the coldest period in year. Especially, White-naped cranes were able to choose wintering site between Cheorwon and other alternative place where snow coverage had low influence, differing from Red crowned cranes. For this reason, we predicted the population size of White-naped cranes would fluctuate according to the extent of snow coverage in Cheorwon. Therefore we used snow coverage data based on MODIS and climate data from KMA (Korea Meteorological Administration) that are generally used. We analyzed the crane's population size in Cheorwon in January from 2002 to 2014. The temperature in the Cheorwon increased from 2002 to wintering period in 2007~ 2008 and went down, showing the lowest temperature in 2011~ 2012. With this phenomenon, warmth index showed the similar pattern with temperature. Amount of newly accumulated snow (the amount of snow that fallen from 0:01 am to 11:29 pm in a day) was low after 2002, but rapidly increased in 2010~ 2011 and 2011~ 2012. The area of snow coverage rapidly declined from 2002 to 2005~ 2006 but suddenly expanded in wintering period in 2009~ 2010 and 2010~ 2011. Wintering population size of the White-naped cranes decreased as snow coverage area increased in January and the highest correlation was found between them, compared to the other climatic factors. However, the number of individuals of Red crowned cranes had little relationship with general climate factors including snow cover range. Therefore it seems that population size of the Red crowned crane varied by factors related with habitat selection such as secure roosting site and area of foraging place, not by climatic factors. In multiple regression analysis, wintering population of White-naped cranes showed significant relationship with logarithmic value of snow cover range and its period. Therefore, it suggests that the population size of the White-naped crane was affected by snow cover range n wintering period and this was because it was hard for them to find out rice grains which are their main food items, buried in snow cover. The population size variation in White-naped cranes was caused by some individuals which left Cheorwon for Izumi where snow cover had little influence on them. The wintering population in Izumi and Cheorwon had negative correlation, implying they were mutually related.

Analysis of Spatial Correlation between Surface Temperature and Absorbed Solar Radiation Using Drone - Focusing on Cool Roof Performance - (드론을 활용한 지표온도와 흡수일사 간 공간적 상관관계 분석 - 쿨루프 효과 분석을 중심으로 -)

  • Cho, Young-Il;Yoon, Donghyeon;Lee, Moung-Jin
    • Korean Journal of Remote Sensing
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    • v.38 no.6_2
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    • pp.1607-1622
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    • 2022
  • The purpose of this study is to determine the actual performance of cool roof in preventing absorbed solar radiation. The spatial correlation between surface temperature and absorbed solar radiation is the method by which the performance of a cool roof can be understood and evaluated. The research area of this study is the vicinity of Jangyu Mugye-dong, Gimhae-si, Gyeongsangnam-do, where an actual cool roof is applied. FLIR Vue Pro R thermal infrared sensor, Micasense Red-Edge multi-spectral sensor and DJI H20T visible spectral sensor was used for aerial photography, with attached to the drone DJI Matrice 300 RTK. To perform the spatial correlation analysis, thermal infrared orthomosaics, absorbed solar radiation distribution maps were constructed, and land cover features of roof were extracted based on the drone aerial photographs. The temporal scope of this research ranged over 9 points of time at intervals of about 1 hour and 30 minutes from 7:15 to 19:15 on July 27, 2021. The correlation coefficient values of 0.550 for the normal roof and 0.387 for the cool roof were obtained on a daily average basis. However, at 11:30 and 13:00, when the Solar altitude was high on the date of analysis, the difference in correlation coefficient values between the normal roof and the cool roof was 0.022, 0.024, showing similar correlations. In other time series, the values of the correlation coefficient of the normal roof are about 0.1 higher than that of the cool roof. This study assessed and evaluated the potential of an actual cool roof to prevent solar radiation heating a rooftop through correlation comparison with a normal roof, which serves as a control group, by using high-resolution drone images. The results of this research can be used as reference data when local governments or communities seek to adopt strategies to eliminate the phenomenon of urban heat islands.