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대한원격탐사학회> 대한원격탐사학회지> Monitoring Mount Sinabung in Indonesia Using Multi- Temporal InSAR

KCI등재

Monitoring Mount Sinabung in Indonesia Using Multi- Temporal InSAR

Chang-wook Lee , Zhong Lu , Jin Woo Kim
  • : 대한원격탐사학회
  • : 대한원격탐사학회지 33권1호
  • : 연속간행물
  • : 2017년 02월
  • : 37-46(10pages)
대한원격탐사학회지

DOI


목차

1. Introduction
2. Data processing
3. Results
4. Discussion and Conclusion
Acknowledgment
References

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초록 보기

Sinabung volcano in Indonesia was formed due to the subduction between the Eurasian and Indo-Australian plates along the Pacific Ring of Fire. After being dormant for about 400 years, Sinabung volcano erupted on the 29th of August, 2010 and most recently on the 1st of November, 2016. We measured the deformation of Sinabung volcano using Advanced Land Observing Satellite/Phased Array type L-band Synthetic Aperture Radar (ALOS/PALSAR) interferometric synthetic aperture radar (InSAR) images acquired from February 2007 to January 2011. Based on multi-temporal InSAR processing, we mapped the ground surface deformation before, during, and after the 2010 eruption with time-series InSAR technique. During the 3 years before the 2010 eruption, the volcano inflated at an average rate of ~1.7 cm/yr with a markedly higher rate of 6.6 cm/yr during the 6 months prior to the 2010 eruption. The inflation was constrained to the top of the volcano. From the 2010 eruption to January 2011, the volcano subsided by approximately 3 cm (~6 cm/yr). We interpreted that the inflation was due to magma accumulation in a shallow reservoir beneath Sinabung. The deflation was attributed to magma withdrawal from the shallow reservoir during the eruption as well as thermo-elastic compaction of erupted material. This result demonstrates once again the utility of InSAR for volcano monitoring.

UCI(KEPA)

I410-ECN-0102-2018-400-000455173

간행물정보

  • : 자연과학분야  > 기타(자연과학)
  • : KCI등재
  • :
  • : 격월
  • : 1225-6161
  • : 2287-9307
  • : 학술지
  • : 연속간행물
  • : 1985-2022
  • : 1757


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38권2호(2022년 04월) 수록논문
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KCI등재

1Sentinel-1 SAR 시계열 영상을 이용한 캐나다 앨버타 오일샌드 지역의 지표변위 분석

저자 : 김태욱 ( Taewook Kim ) , 한향선 ( Hyangsun Han )

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 38권 2호 발행 연도 : 2022 페이지 : pp. 139-151 (13 pages)

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오일샌드 채굴에 널리 이용되고 있는 증기 주입식 중력 배수(Steam-Assisted Gravity Drainage, SAGD) 공법은 지표의 변형을 야기하며, 이는 오일샌드 플랜트의 안정성에 영향을 미칠 뿐만 아니라 다양한 지질 재해의 원인이 되므로 지속적인 모니터링이 필요하다. 이 연구에서는 캐나다 앨버타의 Athabasca 오일샌드 지역에 대해 2016년부터 2021년까지 획득된 Sentinel-1 시계열 영상레이더(synthetic aperture radar, SAR) 자료에 고정산란체 간섭기법(Permanent Scatterer Interferometric SAR, PSInSAR)을 적용하여 SAGD 운용에 의한 지표변위를 관측하였다. 그리고 SAGD의 건설 및 확장을 Landsat-7/8 시계열 영상으로부터 파악하고, 이를 통해 SAGD의 원유 생산성에 따른 지표변위의 특성을 분석하였다. Athabasca 오일샌드 지역의 SAGD 및 그 주변에서는 레이더 관측방향으로 0.3-2.5 cm/yr의 지반융기가 관측된 반면, SAGD에서 수 km 이상 떨어져 있고 오일샌드 채굴의 영향이 없는 지역에서는 -0.3--0.6 cm/yr의 침하가 관측되었다. Landsat-7/8 시계열 영상 분석을 통해 2012년 이후에 건설되어 높은 생산성을 보이는 SAGD는 증기의 주입으로 인해 1.6 cm/yr 이상의 지반융기를 야기하는 반면에 더 오랜 기간 동안 운용되어 생산성이 상대적으로 낮은 SAGD에서는 증기 주입에도 불구하고 지속적인 원유 회수에 따른 사암의 압축 때문에 연간 수 mm의 매우 작은 융기가 발생함을 추정할 수 있었다. SAGD 및 그 주변을 제외한 대부분의 지역에서 관측된 침하는 동토층의 융해에 의한 점진적 지반침하로 추정되었다. 동토층의 침하를 고려할 때 SAGD 운용에 기인하는 지반의 융기는 관측된 것보다 더 클 것이라고 예상되었다. 이 연구의 결과를 통해 PSInSAR 기법이 극한지 오일샌드 SAGD의 생산성과 안정성 평가에 유용한 수단으로 활용될 수 있음을 확인할 수 있었다.


SAGD (Steam-Assisted Gravity Drainage) method is widely used for oil recovery in oil sands regions. The SAGD operation causes surface displacement, which can affect the stability of oil recovery plants and trigger various geological disasters. Therefore, it is important to monitor the surface displacement due to SAGD in the oil sands region. In this study, the surface displacement due to SAGD operations of the Athabasca oil sands region in Alberta, Canada, was observed by applying Permanent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) technique to the Sentinel-1 time series SAR data acquired from 2016 to 2021. We also investigated the construction and expansion of SAGD facilities from Landsat-7/8 time series images, from which the characteristics of the surface displacement according to the oil production activity of SAGD were analyzed. Uplift rates of 0.3-2.5 cm/yr in the direction of line of sight were observed over the SAGDs and their vicinity, whereas subsidence rates of -0.3--0.6 cm/yr were observed in areas more than several kilometers away from the SAGDs and not affected by oil recovery activities. Through the analysis of Landsat-7/8 images, we could confirm that the SAGDs operating after 2012 and showing high oil production activity caused uplift rates greater than 1.6 cm/yr due to the subsurface steam injection. Meanwhile, very small uplift rates of several mm per year occurred over SAGDs which have been operated for a longer period of time and show relatively low oil production activity. This was probably due to the compression of reservoir sandstone due to continuous oil recovery. The subsidence observed in areas except for the SAGDs and their vicinity estimated to be a gradual land subsidence caused by melting of the permafrost. Considering the subsidence, it was expected that the uplift due to SAGD operation would be greater than that observed by the PSInSAR. The results of this study confirm that the PSInSAR can be used as an effective means for evaluating productivity and stability of SAGD in the extreme cold regions.

KCI등재

2Sentinel-1 SAR 영상의 수체 탐지 기법을 활용한 저수지 관측 기반 수문학적 가뭄 지수 평가

저자 : 김완엽 ( Wanyub Kim ) , 정재환 ( Jaehwan Jeong ) , 최민하 ( Minha Choi )

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 38권 2호 발행 연도 : 2022 페이지 : pp. 153-166 (14 pages)

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저수량은 가용한 수자원의 양을 가장 직접적으로 나타내는 인자중의 하나이다. 또한 가뭄의 영향을 보다 직관적으로 나타낼 수 있으므로, 가뭄 평가를 위한 연구에서도 다양하게 활용되고 있다. 최근에는 광학영상으로 저수면적을 관측하고, 또 이를 활용한 수문학적 가뭄지수인 RADI가 개발되기도 하였다. 인공위성을 통해 얻을 수 있는 광학영상은 관측주기가 뛰어나 많은 양의 자료를 획득할 수 있으나, 구름 등 기상과 대기환경에 의한 영향에 취약하여 실제 활용에서는 다소 한계가 있다. 이에 본 연구에서는 기상이나, 관측시간대와 상관없이 영상을 획득할 수 있는 SAR 영상을 활용한 가뭄지수 산정 연구를 수행하고자 하였다. Sentinel-1 위성의 SAR 영상을 활용하여 충북 진천군에 위치한 백곡, 초평저수지의 저수면적을 탐지하여, RADI를 산정하여 지역규모 가뭄 모니터링을 수행하였다. RADI는 실측 저수량을 기반으로 한 RSDI와 비교, 검증하였다. RADI는 RSDI와 상관계수 r=0.87, ROC의 밑면적 AUC=0.97로 매우 높은 상관 관계를 보여주었다. 이 결과는 SAR 기반 RADI의 지역규모 수문학적 가뭄 모니터링의 가능성을 보여주며, 추후 가용 SAR 영상의 종류가 늘어나고, 재방문주기가 단축될 것이므로 가뭄 모니터링에 대한 활용성이 증대될 것으로 기대된다.


Water storage is one of the factors that most directly represent the amount of available water resources. Since the effects of drought can be more intuitively expressed, it is also used in various studies for drought evaluation. In a recent study, hydrological drought was evaluated through information on observing reservoirs with optical images. The short observation cycle and diversity of optical satellites provide a lot of data. However, there are some limitations because it is vulnerable to the influence of weather or the atmospheric environment. Therefore, this study attempted to conduct a study on estimating the drought index using Synthetic Aperture Radar (SAR) image with relatively little influence from the observation environment. We produced the waterbody of Baekgok and Chopyeong reservoirs using SAR images of Sentinel-1 satellites and calculated the Reservoir Area Drought Index (RADI), a hydrological drought index. In order to validate the applicability of RADI to drought monitoring, it was compared with Reservoir Storage Drought Index (RSDI) based on measured storage. The two indices showed a very high correlation with the correlation coefficient, r=0.87, Area Under curve, AUC=0.97. These results show the possibility of regional-scale hydrological drought monitoring of SAR-based RADI. As the number of available SAR images increases in the future, it is expected that the utilization of drought monitoring will also increase.

KCI등재

3위성 영상을 위한 경량화된 CNN 기반의 보간 기술 연구

저자 : 김현호 ( Hyun-ho Kim ) , 서두천 ( Doochun Seo ) , 정재헌 ( Jaeheon Jung ) , 김용우 ( Yongwoo Kim )

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 38권 2호 발행 연도 : 2022 페이지 : pp. 167-177 (11 pages)

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위성 영상 촬영 후 지상국에 전송된 영상을 이용하여 최종 위성 영상을 획득하기 위해 많은 영상 전/후처리 과정이 수반된다. 전/후처리 과정 중 레벨 1R 영상에서 레벨 1G 영상으로 변환 시 기하 보정은 필수적으로 요구된다. 기하 보정 알고리즘에서는 보간 기법을 필연적으로 사용하게 되며, 보간 기법의 정확도에 따라서 레벨 1G 영상의 품질이 결정된다. 또한, 레벨 프로세서에서 수행되는 보간 알고리즘의 고속화 역시 매우 중요하다. 본 논문에서는 레벨 1R에서 레벨 1G로 변환 시 기하 보정에 필요한 경량화된 심층 컨볼루션 신경망 기반 보간 기법에 대해 제안하였다. 제안한 기법은 위성 영상의 해상도를 2배 향상하며, 빠른 처리 속도를 위해 경량화된 심층 컨볼루션 신경망으로 딥러닝 네트워크를 구성하였다. 또한, panchromatic (PAN) 밴드 정보를 활용하여 multispectral (MS) 밴드의 영상 품질 개선이 가능한 피처 맵 융합 방법을 제안하였다. 제안된 보간 기술을 통해 획득한 영상은 기존의 딥러닝 기반 보간 기법에 비해 정량적인 peak signal-to-noise ratio (PSNR) 지표에서 PAN 영상은 약 0.4 dB, MS 영상은 약 4.9 dB 개선된 결과를 보여주었으며, PAN 영상 크기 기준 36,500×36,500 입력 영상의 해상도를 2배 향상된 영상 획득 시 기존 딥러닝 기반 보간 기법 대비 처리 속도가 약 1.6배 향상됨을 확인하였다.


In order to obtain satellite image products using the image transmitted to the ground station after capturing the satellite images, many image pre/post-processing steps are involved. During the pre/post-processing, when converting from level 1R images to level 1G images, geometric correction is essential. An interpolation method necessary for geometric correction is inevitably used, and the quality of the level 1G images is determined according to the accuracy of the interpolation method. Also, it is crucial to speed up the interpolation algorithm by the level processor. In this paper, we proposed a lightweight CNN-based interpolation method required for geometric correction when converting from level 1R to level 1G. The proposed method doubles the resolution of satellite images and constructs a deep learning network with a lightweight deep convolutional neural network for fast processing speed. In addition, a feature map fusion method capable of improving the image quality of multispectral (MS) bands using panchromatic (PAN) band information was proposed. The images obtained through the proposed interpolation method improved by about 0.4 dB for the PAN image and about 4.9 dB for the MS image in the quantitative peak signal-to-noise ratio (PSNR) index compared to the existing deep learning-based interpolation methods. In addition, it was confirmed that the time required to acquire an image that is twice the resolution of the 36,500×36,500 input image based on the PAN image size is improved by about 1.6 times compared to the existing deep learning-based interpolation method.

KCI등재

4GK2A AMI를 이용한 한반도 식생건강지수 산출

저자 : 이수진 ( Soo-jin Lee ) , 조재일 ( Jaeil Cho ) , 류재현 ( Jae-hyun Ryu ) , 김나리 ( Nari Kim ) , 김광진 ( Kwangjin Kim ) , 손은하 ( Eunha Sohn ) , 박기홍 ( Ki-hong Park ) , 장재철 ( Jae-cheol Jang ) , 이양원 ( Yangwon Lee )

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 38권 2호 발행 연도 : 2022 페이지 : pp. 180-189 (10 pages)

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지구온난화는 기후변화를 야기하며 전지구적으로 이상기상 현상을 유발하고 있다. 우리나라에서도 폭염, 가뭄과 같은 이상기상 현상이 증가하고 있는 상황이다. 이상기상 감시를 위하여 지표면온도(Land Surface Temperature, LST), 온도상태지수(Temperature Condition Index, TCI), 식생활력지수(Normalized Difference Vegetation Index, NDVI), 식생상태지수(Vegetation Condition Index, VCI), 식생건강지수(Vegetation Health Index, VHI) 등의 위성자료가 활용되고 있다. TCI와 VCI를 이용하여 계산되는 VHI는 온도, 강수와 같은 기상 요인에 의한 식생 스트레스를 나타내며, 기후변화 상황에서 가뭄 평가에 주로 활용되고 있다. TCI, VCI는 날짜 및 장소에 따른 LST, NDVI의 과거 평년치를 참조해서 산출되기 때문에, 아직 2년여의 자료밖에 없는 천리안위성 2A호(GK2A) AMI (Advanced Meteorological Imager) 자료로부터 TCI, VCI, VHI를 산출하는 것은 현재로서는 쉽지 않은 일이다. 본 연구에서는 대안적인 방법으로 VIIRS (Visible Infrared Imaging Radiometer Suite) 센서의 LST, NDVI를 이용하여 GK2A의 VHI 산출 가능성을 모색하였다. GK2A와 VIIRS의 LST, NDVI는 상당히 높은 상관성을 보이기 때문에, GK2A에 존재하지 않는 과거 평년치를 VIIRS 자료로 대체하는 방식을 택하였다. 8일 간격으로 GK2A 격자에 해당하는 LST, NDVI의 최소·최대값 조견표를 구축하여 TCI, VCI, VHI를 산출하였고, 최근 우리나라 이상기상 현상에 대한 해석을 수행하였다. GK2A VHI는 2020년 3월과 6월의 폭염, 4월과 7월의 저온, 8월의 폭우 등으로 인한 식생 스트레스의 변화를 잘 표현하는 것으로 나타났지만, 미국 해양대기청(National Oceanic and Atmospheric Administration, NOAA)의 VHI 산출물은 그렇지 않았다. 본 연구에서 제시한 GK2A VHI는 향후 LST, NDVI의 과거 평년치에 대한 통계적으로 엄밀한 보완을 거친다면 폭염, 가뭄으로 인한 식생 스트레스 감시에 활용될 수 있을 것으로 사료된다.


Global warming causes climate change and increases extreme weather events worldwide, and the occurrence of heatwaves and droughts is also increasing in Korea. For the monitoring of extreme weather, various satellite data such as LST (Land Surface Temperature), TCI (Temperature Condition Index), NDVI (Normalized Difference Vegetation Index), VCI (Vegetation Condition Index), and VHI (Vegetation Health Index) have been used. VHI, the combination of TCI and VCI, represents the vegetation stress affected by meteorological factors like precipitation and temperature and is frequently used to assess droughts under climate change. TCI and VCI require historical reference values for the LST and NDVI for each date and location. So, it is complicated to produce the VHI from the recent satellite GK2A (Geostationary Korea Multi-Purpose Satellite-2A). This study examined the retrieval of VHI using GK2A AMI (Advanced Meteorological Imager) by referencing the historical data from VIIRS (Visible Infrared Imaging Radiometer Suite) NDVI and LST as a proxy data. We found a close relationship between GK2A and VIIRS data needed for the retrieval of VHI. We produced the TCI, VCI, and VHI for GK2A during 2020-2021 at intervals of 8 days and carried out the interpretations of recent extreme weather events in Korea. GK2A VHI could express the changes in vegetation stress in 2020 due to various extreme weather events such as heatwaves (in March and June) and low temperatures (in April and July), and heavy rainfall (in August), while NOAA (National Oceanic and Atmospheric Administration) VHI could not well represent such characteristics. The GK2A VHI presented in this study can be utilized to monitor the vegetation stress due to heatwaves and droughts if the historical reference values of LST and NDVI can be adjusted in a more statistically significant way in the future work.

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5GEMS 이산화황 산출 현업 알고리즘에서 오프셋 보정 계수 산정 방법에 대한 영향 조사

저자 : 박정현 ( Jeonghyeon Park ) , 양지원 ( Jiwon Yang ) , 최원이 ( Wonei Choi ) , 김세린 ( Serin Kim ) , 이한림 ( Hanlim Lee )

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 38권 2호 발행 연도 : 2022 페이지 : pp. 189-198 (10 pages)

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본 연구에서는 지난 2020년 2월에 발사된 정지궤도환경위성탑재체(Geostationary Environment Monitoring Spectrometer; GEMS)의 이산화황 산출 현업 알고리즘에서 오프셋 보정 계수 산정 방법이 이산화황 칼럼 농도 산출 결과에 미치는 영향을 확인하였다. GEMS의 현업 이산화황 산출 알고리즘은 차등흡수분광법(Differential Optical Absorption Spectroscopy; DOAS)과 주성분분석방법(Principal component analysis; PCA)이 융합된 하이브리드 알고리즘이다. 하이브리드 알고리즘에서는 차등흡수분광법을 이용하여 스펙트럴 피팅 후 나오는 이산화황 경사층적분농도 값에 나타나는 오존에 의한 흡수 영향을 보정하기 위하여 편차 보정 과정을 필수적으로 거치게 되며, 오프셋 보정 계수를 산정하는 조건에 따라 이산화황 칼럼농도 산출결과가 달라질 수 있기 때문에 적절한 오프셋 보정 계수 값의 적용이 필요하다. 본 연구에서는 구름 화소가 많이 존재하는 날짜와 적게 존재하는 날짜에 대해 오존 보정 계수를 각각 계산하고, 각각의 오존 보정 계수를 GEMS 현업 이산화황 산출 알고리즘에 적용하여 산출한 이산화황 칼럼농도의 비교를 수행하였다. 구름 화소가 많이 존재하는 날의 GEMS 복사휘도 자료를 이용하여 계산된 오존 보정 계수를 사용한 경우, GEMS 관측 영역의 가장자리에 해당하는 인도 부근에서의 이산화황 칼럼농도의 표준편차가 1.27 DU, 한반도 부근에서 0.58 DU, 주변에 구름 화소가 많았던 홍콩 부근에서 0.77 DU로 나타났다. 한편, 구름 화소가 적은 날의 GEMS 자료를 이용하여 계산된 오존 보정 계수를 사용하였을 경우의 이산화황 칼럼농도의 표준편차는 인도주변에서 0.72 DU, 한반도 주변에서 0.38 DU, 홍콩 부근에서 0.44 DU로 다소 감소하였음을 확인하였으며, 구름 화소가 많은 날의 오존 보정 계수를 사용하여 이산화황을 산출한 경우 대비 비교적 안정적인 산출이 이루어졌음을 확인하였다. 이에 따라, GEMS 이산화황 산출 알고리즘의 불확실성 최소화 및 안정적인 산출을 위해서 적절한 조건에서의 오존 보정 계수 산정이 이루어져야 할 필요가 있다.


In this present study, we investigated the effect of the offset correction factor calculation method on the sulfur dioxide (SO2) column density in the SO2 retrieval algorithm of the Geostationary Environment Monitoring Spectrometer (GEMS) launched in February 2020. The GEMS operational SO2 retrieval algorithm is the Differential Optical Absorption Spectroscopy (DOAS) - Principal Component Analysis (PCA) Hybrid algorithm. In the GEMS Hybrid algorithm, the offset correction process is essential to correct the absorption effect of ozone appearing in the SO2 slant column density (SCD) obtained after spectral fitting using DOAS. Since the SO2 column density may depend on the conditions for calculating the offset correction factor, it is necessary to apply an appropriate offset correction value. In this present study, the offset correction values were calculated for days with many cloud pixels and few cloud pixels, respectively. And a comparison of the SO2 column density retrieved by applying each offset correction factor to the GEMS operational SO2 retrieval algorithm was performed. When the offset correction value was calculated using radiance data of GEMS on a day with many cloud pixels was used, the standard deviation of the SO2 column density around India and the Korean Peninsula, which are the edges of the GEMS observation area, was 1.27 DU, and 0.58 DU, respectively. And around Hong Kong, where there were many cloud pixels, the SO2 standard deviation was 0.77 DU. On the other hand, when the offset correction value calculated using the GEMS data on the day with few cloud pixels was used, the standard deviation of the SO2 column density slightly decreased around India (0.72 DU), Korean Peninsula (0.38 DU), and Hong Kong (0.44 DU). We found that the SO2 retrieval was relatively stable compared to the SO2 retrieval case using the offset correction value on the day with many cloud pixels. Accordingly, to minimize the uncertainty of the GEMS SO2 retrieval algorithm and to obtain a stable retrieval, it is necessary to calculate the offset correction factor under appropriate conditions.

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6작물 분류를 위한 딥러닝 기반 비지도 도메인 적응 모델 비교

저자 : 곽근호 ( Geun-ho Kwak ) , 박노욱 ( No-wook Park )

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 38권 2호 발행 연도 : 2022 페이지 : pp. 199-213 (15 pages)

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비지도 도메인 적응은 연단위 작물 분류를 위해 매년 반복적으로 양질의 훈련자료를 수집해야 하는 비실용적인 문제를 해결할 수 있다. 이 연구에서는 작물 분류를 위한 딥러닝 기반 비지도 도메인 적응 모델의 적용성을 평가하였다. 우리나라 마늘, 양파 주산지인 합천군과 창녕군을 대상으로 무인기 영상을 이용한 작물 분류 실험을 통해 deep adaptation network (DAN), deep reconstruction-classification network, domain adversarial neural network (DANN)의 3개의 비지도 도메인 적응 모델을 정량적으로 비교하였다. 비지도 도메인 적응 모델의 분류 성능을 평가하기 위해 소스 베이스라인 및 대상 베이스라인 모델로 convolutional neural networks (CNNs)을 추가로 적용하였다. 3개의 비지도 도메인 적응 모델은 소스 베이스라인 CNN보다 우수한 성능을 보였으나, 소스 도메인 영상과 대상 도메인 영상의 자료 분포 간 불일치 정도에 따라 서로 다른 분류 성능을 보였다. DAN의 분류 성능은 두 도메인 영상 간 불일치가 작을 때 다른 두 모델에 비해 분류 성능이 높은 반면에 DANN은 두 도메인 영상 간 불일치가 클 때 가장 우수한 분류 성능을 보였다. 따라서 신뢰할 수 있는 분류 결과를 생성하기 위해 두 도메인 영상의 분포가 일치하는 정도를 고려해서 최상의 비지도 도메인 적응 모델을 선택해야 한다.


The unsupervised domain adaptation can solve the impractical issue of repeatedly collecting high-quality training data every year for annual crop classification. This study evaluates the applicability of deep learning-based unsupervised domain adaptation models for crop classification. Three unsupervised domain adaptation models including a deep adaptation network (DAN), a deep reconstructionclassification network, and a domain adversarial neural network (DANN) are quantitatively compared via a crop classification experiment using unmanned aerial vehicle images in Hapcheon-gun and Changnyeong-gun, the major garlic and onion cultivation areas in Korea. As source baseline and target baseline models, convolutional neural networks (CNNs) are additionally applied to evaluate the classification performance of the unsupervised domain adaptation models. The three unsupervised domain adaptation models outperformed the source baseline CNN, but the different classification performances were observed depending on the degree of inconsistency between data distributions in source and target images. The classification accuracy of DAN was higher than that of the other two models when the inconsistency between source and target images was low, whereas DANN has the best classification performance when the inconsistency between source and target images was high. Therefore, the extent to which data distributions of the source and target images match should be considered to select the best unsupervised domain adaptation model to generate reliable classification results.

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7Pandora 원시자료로부터 차등흡수분광법을 이용하여 이산화질소 칼럼 농도 산출 시 파장 구간 및 흡수단면적에 따른 산출 정확도 평가

저자 : 김세린 ( Serin Kim ) , 김대원 ( Daewon Kim ) , 이한림 ( Hanlim Lee )

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 38권 2호 발행 연도 : 2022 페이지 : pp. 215-222 (8 pages)

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본 연구에서는 pandora 직달광 원시자료로부터 차등흡수분광법(DOAS, Differential Optical Absorption Spectroscopy)을 이용하여 이산화질소 연직칼럼농도(VCD, Vertical column density) 산출 시 파장구간과 흡수단 면적이 미치는 영향을 비교 분석하였다. GEMS Map of the Air Pollution (GMAP) 2020 캠페인 기간 동안 서산에서 Pandora 장비로 관측된 자료를 사용하였으며, 차등흡수분광법을 이용하여 CINDI-2 캠페인과 PGN의 산출 방법에 따라 4가지 조건으로 이산화질소 연직칼럼농도를 산출하였다. 4가지 조건으로 산출된 이산화질소 평균 연직칼럼농도는 1.22×1016~1.38×1016 molec. cm-2으로, 각 조건 간 최대 0.16×1016 molec. cm-2의 차이를 보였다. 피팅 에러는 평균 3.19~9.59%로 모든 조건에서 10% 이내였으며, RMS는 5.11×10-3~7.16×10-3 molec. cm-2으로 나타났다. 4가지 방법으로 산출된 이산화질소 연직칼럼농도와 Pandonia Global Network (PGN)에서 제공하는 이산화질소 연직칼럼농도와 기울기는 0.98~1.09이었으며, 0.96~0.98의 상관관계를 보여주었다.


In this study, the effect of wavelength range and absorption cross-section used to retrieve nitrogen dioxide (NO2) vertical column density (VCD) from Pandora was analyzed using Differential Optical Absorption Spectroscopy (DOAS). During the GEMS Map of the Air Pollution (GMAP) 2020 campaign, data from direct sunlight observation with Pandora instrument in Seosan was used, and NO2 VCD was retrieved under four conditions. The average NO2 VCD under the four conditions ranged from 1.22×1016~1.38×1016 molec. cm-2, with a maximum difference of 0.16×1016 molec. cm-2 between each condition. The fitting error averaged 3.19~9.59%, showing an error within 10% in all cases, and the RMS was 5.11×10-3~7.16×10-3 molec. cm-2. The retrieved NO2 VCD using 4 conditions shows a slope in the range of 0.98 to 1.09 and correlation of 0.96 to 0.98 in comparison with Pandonia Global Network (PGN).

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8정오표(Erratum) : 모의영상을 이용한 농림위성 대기보정의 주요 파라미터 민감도 분석 및 타위성 산출물 활용 가능성 제시

저자 : 강유진 ( Yoojin Kang ) , 조동진 ( Dongjin Cho ) , 한대현 ( Daehyeon Han ) , 임정호 ( Jungho Im ) , 임중빈 ( Joongbin Lim ) , 오금희 ( Kum-hui Oh ) , 권언혜 ( Eonhye Kwon )

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 38권 2호 발행 연도 : 2022 페이지 : pp. 223-223 (1 pages)

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1Analysis of Geometric and Spatial Image Quality of KOMPSAT-3A Imagery in Comparison with KOMPSAT-3 Imagery

저자 : Nyamjargal Erdenebaatar , Jaein Kim , Taejung Kim

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 33권 1호 발행 연도 : 2017 페이지 : pp. 1-13 (13 pages)

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This study investigates the geometric and spatial image quality analysis of KOMPSAT-3A stereo pair. KOMPSAT-3A is, the latest satellite of KOMPSAT family, a Korean earth observation satellite operating in optical bands. A KOMPSAT-3A stereo pair was taken on 23 November, 2015 with 0.55 m ground sampling distance over Terrassa area of Spain. The convergence angle of KOMPSAT-3A stereo pair was estimated as 58.68˚. The investigation was assessed through the evaluation of the geopositioning analysis, image quality estimation and the accuracy of automatic Digital Surface Model (DSM) generation and compared with those of KOMPSAT-3 stereo pair with the convergence angle of 44.80˚ over the same area. First, geopositioning accuracy was tested with initial rational polynomial coefficients (RPCs) and after compensating the biases of the initial RPCs by manually collected ground control points. Then, regarding image quality, relative edge response was estimated for manually selected points visible from two stereo pairs. Both of the initial and biascompensated positioning accuracy and the quality assessment result expressed that KOMPSAT-3A images showed higher performance than those of KOMPSAT-3 images. Finally, the accuracy of DSMs generated from KOMPSAT-3A and KOMPSAT-3 stereo pairs were examined with respect to the reference LiDAR-derived DSM. The various DSMs were generated over the whole coverage of individual stereo pairs with different grid spacing and over three types of terrain; flat, mountainous and urban area. Root mean square errors of DSM from KOMPSAT-3A pair were larger than those for KOMPSAT-3. This seems due to larger convergence angle of the KOMPSAT-3A stereo pair.

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2Potential Applications of Low Altitude Remote Sensing for Monitoring Jellyfish

저자 : Young-heon Jo , Hongsheng Bi , Jongsuk Lee

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 33권 1호 발행 연도 : 2017 페이지 : pp. 15-24 (10 pages)

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Jellyfish (cnidarian) are conspicuous in many marine ecosystems when in bloom. Despite their importance for the ecosystem structure and function, very few sampling programs are dedicated to sample jellyfish because they are patchily distributed and easily clogged plankton net. Although satellite remote sensing is an excellent observing tool for many phenomena in the ocean, their uses for monitoring jellyfish are not possible due to the coarse spatial resolutions. Hence, we developed the low altitude remote sensing platform to detect jellyfish in high resolutions, which allow us to monitor not only horizontal, but also vertical migration of them. Using low altitude remote sensing platform, we measured the jellyfish from the pier at the Chesapeake Biological Laboratory in Chesapeake Bay. The patterns observed included discrete patches, in rows that were aligned with waves that propagated from deeper regions, and aggregation around physical objects. The corresponding areas of exposed jellyfish on the sea surface were 0.1×104 pixel2, 0.3×104 pixel2, and 2.75×104 pixel2, respectively. Thus, the research result suggested that the migration of the jellyfish was related to the physical forcing in the sea surface.

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3Impact of Trend Estimates on Predictive Performance in Model Evaluation for Spatial Downscaling of Satellitebased Precipitation Data

저자 : Yeseul Kim , No-wook Park

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 33권 1호 발행 연도 : 2017 페이지 : pp. 25-35 (11 pages)

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Spatial downscaling with fine resolution auxiliary variables has been widely applied to predict precipitation at fine resolution from coarse resolution satellite-based precipitation products. The spatial downscaling framework is usually based on the decomposition of precipitation values into trend and residual components. The fine resolution auxiliary variables contribute to the estimation of the trend components. The main focus of this study is on quantitative analysis of impacts of trend component estimates on predictive performance in spatial downscaling. Two regression models were considered to estimate the trend components: multiple linear regression (MLR) and geographically weighted regression (GWR). After estimating the trend components using the two models, residual components were predicted at fine resolution grids using area-to-point kriging. Finally, the sum of the trend and residual components were considered as downscaling results. From the downscaling experiments with time-series Tropical Rainfall Measuring Mission (TRMM) 3B43 precipitation data, MLR-based downscaling showed the similar or even better predictive performance, compared with GWR-based downscaling with very high explanatory power. Despite very high explanatory power of GWR, the relationships quantified from TRMM precipitation data with errors and the auxiliary variables at coarse resolution may exaggerate the errors in the trend components at fine resolution. As a result, the errors attached to the trend estimates greatly affected the predictive performance. These results indicate that any regression model with high explanatory power does not always improve predictive performance due to intrinsic errors of the input coarse resolution data. Thus, it is suggested that the explanatory power of trend estimation models alone cannot be always used for the selection of an optimal model in spatial downscaling with fine resolution auxiliary variables.

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4Monitoring Mount Sinabung in Indonesia Using Multi- Temporal InSAR

저자 : Chang-wook Lee , Zhong Lu , Jin Woo Kim

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 33권 1호 발행 연도 : 2017 페이지 : pp. 37-46 (10 pages)

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Sinabung volcano in Indonesia was formed due to the subduction between the Eurasian and Indo-Australian plates along the Pacific Ring of Fire. After being dormant for about 400 years, Sinabung volcano erupted on the 29th of August, 2010 and most recently on the 1st of November, 2016. We measured the deformation of Sinabung volcano using Advanced Land Observing Satellite/Phased Array type L-band Synthetic Aperture Radar (ALOS/PALSAR) interferometric synthetic aperture radar (InSAR) images acquired from February 2007 to January 2011. Based on multi-temporal InSAR processing, we mapped the ground surface deformation before, during, and after the 2010 eruption with time-series InSAR technique. During the 3 years before the 2010 eruption, the volcano inflated at an average rate of ~1.7 cm/yr with a markedly higher rate of 6.6 cm/yr during the 6 months prior to the 2010 eruption. The inflation was constrained to the top of the volcano. From the 2010 eruption to January 2011, the volcano subsided by approximately 3 cm (~6 cm/yr). We interpreted that the inflation was due to magma accumulation in a shallow reservoir beneath Sinabung. The deflation was attributed to magma withdrawal from the shallow reservoir during the eruption as well as thermo-elastic compaction of erupted material. This result demonstrates once again the utility of InSAR for volcano monitoring.

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5On the Spatial and Temporal Variability of L-band Polarimetric SAR Observations of Permafrost Environment in Central Yakutia

저자 : Sang-eun Park

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 33권 1호 발행 연도 : 2017 페이지 : pp. 47-60 (14 pages)

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The permafrost active layer plays an important role in permafrost dynamics. Ecological patterns, processes, and water and ice contents in the active layer are spatially and temporally complex depending on landscape heterogeneity and local-scale variations in hydrological processes. Although there has been emerging interest in the application of optical remote sensing techniques to permafrost environments, optical sensors are significantly limited in accessing information on near surface geo-cryological conditions. The primary objective of this study was to investigate capability of L-band SAR data for monitoring spatio-temporal variability of permafrost ecosystems and underlying soil conditions. This study exploits information from different polarimetric SAR observables in relation to permafrost environmental conditions. Experimental results show that each polarimetric radar observable conveys different information on permafrost environments. In the case of the dual-pol mode, the radar observables consist of two backscattering powers and one correlation coefficient between polarimetric channels. Among them, the dual-pol scattering powers are highly sensitive to freeze/thaw transition and can discriminate grasslands or ponds in thermokarst area from other permafrost ecosystems. However, it is difficult to identify the ground conditions with dual-pol observables. Additional backscattering powers and correlation coefficients obtained from quad-pol mode help understanding seasonal variations of radar scattering and assessing geo-cryological information on soil layers. In particular, co-pol coherences at HV-basis and circular-basis were found to be very useful tools for mapping and monitoring near surface soil properties.

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6Oil Spill Detection from RADARSAT-2 SAR Image Using Non-Local Means Filter

저자 : Daeseong Kim , Hyung-sup Jung

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 33권 1호 발행 연도 : 2017 페이지 : pp. 61-67 (7 pages)

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The detection of oil spills using radar image has been studied extensively. However, most of the proposed techniques have been focused on improving detection accuracy through the advancement of algorithms. In this study, research has been conducted to improve the accuracy of oil spill detection by improving the quality of radar images, which are used as input data to detect oil spills. Thresholding algorithms were used to measure the image improvement both before and after processing. The overall accuracy increased by approximately 16%, the producer accuracy increased by 40%, and the user accuracy increased by 1.5%. The kappa coefficient also increased significantly, from 0.48 to 0.92.

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7Accuracy Evaluation of DEM generated from Satellite Images Using Automated Geo-positioning Approach

저자 : Kwan-young Oh , Hyung-sup Jung , Moung-jin Lee

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 33권 1호 발행 연도 : 2017 페이지 : pp. 69-77 (9 pages)

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S The need for an automated geo-positioning approach for near real-time results and to boost cost-effectiveness has become increasingly urgent. Following this trend, a new approach to automatically compensate for the bias of the rational function model (RFM) was proposed. The core idea of this approach is to remove the bias of RFM only using tie points, which are corrected by matching with the digital elevation model (DEM) without any additional ground control points (GCPs). However, there has to be a additional evaluation according to the quality of DEM because DEM is used as a core element in this approach. To address this issue, this paper compared the quality effects of DEM in the conduct of the this approach using the Shuttle Radar Topographic Mission (SRTM) DEM with the spatial resolution of 90m. and the National Geographic Information Institute (NGII) DEM with the spatial resolution of 5m. One KOMPSAT-2 stereo-pair image acquired at Busan, Korea was used as experimental data. The accuracy was compared to 29 check points acquired by GPS surveying. After bias-compensation using the two DEMs, the Root Mean Square (RMS) errors were less than 6 m in all coordinate components. When SRTM DEM was used, the RMSE vector was about 11.2m. On the other hand, when NGII DEM was used, the RMSE vector was about 7.8 m. The experimental results showed that automated geo-positioning approach can be accomplished more effectively by using NGII DEM with higher resolution than SRTM DEM.

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8Land Cover Classification of RapidEye Satellite Images Using Tesseled Cap Transformation (TCT)

저자 : Hogyung Moon , Taeyoung Choi , Guhyeok Kim , Nyunghee Park , Honglyun Park , Jaewan Choi

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 33권 1호 발행 연도 : 2017 페이지 : pp. 79-88 (10 pages)

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The RapidEye satellite sensor has various spectral wavelength bands, and it can capture large areas with high temporal resolution. Therefore, it affords advantages in generating various types of thematic maps, including land cover maps. In this study, we applied a supervised classification scheme to generate highresolution land cover maps using RapidEye images. To improve the classification accuracy, object-based classification was performed by adding brightness, yellowness, and greenness bands by Tasseled Cap Transformation (TCT) and Normalized Difference Water Index (NDWI) bands. It was experimentally confirmed that the classification results obtained by adding TCT and NDWI bands as input data showed high classification accuracy compared with the land cover map generated using the original RapidEye images.

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9An efficient ship detection method for KOMPSAT-5 synthetic aperture radar imagery based on adaptive filtering approach

저자 : Jeongin Hwang , Daeseong Kim , Hyung-sup Jung

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 33권 1호 발행 연도 : 2017 페이지 : pp. 89-95 (7 pages)

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Ship detection in synthetic aperture radar (SAR) imagery has long been an active research topic and has many applications. In this paper, we propose an efficient method for detecting ships from SAR imagery using filtering. This method exploits ship masking using a median filter that considers maximum ship sizes and detects ships from the reference image, to which a Non-Local means (NL-means) filter is applied for speckle de-noising and a differential image created from the difference between the reference image and the median filtered image. As the pixels of the ship in the SAR imagery have sufficiently higher values than the surrounding sea, the ship detection process is composed primarily of filtering based on this characteristic. The performance test for this method is validated using KOMPSAT-5 (Korea Multi-Purpose Satellite-5) SAR imagery. According to the accuracy assessment, the overall accuracy of the region that does not include land is 76.79%, and user accuracy is 71.31%. It is demonstrated that the proposed detection method is suitable to detect ships in SAR imagery and enables us to detect ships more easily and efficiently.

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10Tracking the Movement and Distribution of Green Tides on the Yellow Sea in 2015 Based on GOCI and Landsat Images

저자 : Seung-hwan Min , Hyun-ju Oh , Jae-dong Hwang , Young-sang Suh , Mi-ok Park , Ji-sun Shin , Wonkook Kim

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 33권 1호 발행 연도 : 2017 페이지 : pp. 97-109 (13 pages)

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Green tides that developed along the coast of China in 2015 were detected and tracked using vegetation indices from GOCI and Landsat images. Green tides first appeared near the Jiangsu Province on May 14 before increasing in size and number and moving northward to the Shandong Peninsula in mid-June. Typhoon Cham-hom passed through the Yellow Sea on July 12, significantly decreasing the algal population. An algae patch moved east toward Korea and on June 18 and July 4, several masses were found between the southwestern shores of Korea and Jeju Island. The floating masses found in Korean waters were concentrated at the boundary of the open sea and the Jindo cold pool, a phenomenon also observed at the boundary of coastal and offshore waters in China. Sea surface temperatures, derived from NOAA SST data, were found to play a role in generation of the green tides.

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