논문 상세보기

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

키워드 보기


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
  • : 1985-2021
  • : 1692


저작권 안내

한국학술정보㈜의 모든 학술 자료는 각 학회 및 기관과 저작권 계약을 통해 제공하고 있습니다.

이에 본 자료를 상업적 이용, 무단 배포 등 불법적으로 이용할 시에는 저작권법 및 관계법령에 따른 책임을 질 수 있습니다.

37권5호(2021년 10월) 수록논문
최근 권호 논문
| | | |

KCI등재

1기후변화 시나리오를 고려한 위성영상 기반 미래 탄소흡수량 분포 추정

저자 : 나상일 ( Sang-il Na ) , 안호용 ( Ho-yong Ahn ) , 류재현 ( Jae-hyun Ryu ) , 소규호 ( Kyu-ho So ) , 이경도 ( Kyung-do Lee )

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 37권 5호 발행 연도 : 2021 페이지 : pp. 833-845 (13 pages)

다운로드

(기관인증 필요)

초록보기

탄소흡수량 산정 및 토지이용 변화에 대한 이해는 기후변화 연구에서 매우 중요하다. 기존의 연구에서는 토지이용 변화에 따른 탄소흡수량 산정에 원격탐사 기술이 사용되고 있으나 대부분 과거의 탄소흡수량 변화에 초점을 맞추고 있다. 따라서 미래 탄소흡수량 변화 예측 연구는 부족한 실정이다. 본 연구에서 CLUE-S 모형을 사용하여 토지이용 변화를 모의하고 기후변화 시나리오를 고려하여 미래 탄소흡수량의 변화를 예측하였다. 그 결과, RCP 4.5 및 8.5 시나리오에서 탄소흡수량은 각각 7.92, 13.02% 감소되는 것으로 예측되었다. 따라서 본 연구에서 제안한 방법은 다른 기후변화 시나리오를 고려한 미래 탄소흡수량 변화에도 적용이 가능할 것으로 기대된다.


Quantification of carbon absorption and understanding the human induced land use changes forms one of the major study with respect to global climatic changes. An attempt study has been made to quantify the carbon absorption by land use changes through remote sensing technology. However, it focused on past carbon absorption changes. So prediction of future carbon absorption changes is insufficient. This study simulated land use change using the Conversion of Land Use and its Effects at Small regional extent (CLUE-S) model and predicted future changes in carbon absorption considering climate change scenarios 4.5 and 8.5 of the Representative Concentration Pathways (RCP). Results of this study, in the RCP 4.5 scenarios there predicted to be loss of 7.92% of carbon absorption, but in the RCP 8.5 scenarios was 13.02%. Therefore, the approach used in this study is expected to enable exploration of future carbon absorption change considering other climate change scenarios.

KCI등재

2SAR 영상 정합 정확도 평가를 위한 FSIM 인자 활용 가능성

저자 : 김상완 ( Sang-wan Kim ) , 이동준 ( Dongjun Lee )

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 37권 5호 발행 연도 : 2021 페이지 : pp. 847-859 (13 pages)

다운로드

(기관인증 필요)

초록보기

최근 고해상도 위성 SAR 영상이 늘어남에 따라, 변화탐지, 영상 융합 등 다양한 분야에서 SAR 영상에 대한 정밀 정합 요구가 커지고 있다. 영상 정합 결과에 대한 정량적 평가는 분석자에 의해 추출된 GCPs (Ground Control Points)를 이용한 RMSE (Root Mean Square Error) 값이 널리 사용되어 왔으나, 영상정합 결과의 정확도를 자동으로 측정하는 방법에 대한 연구는 미비한 실정이다. 본 연구에서는 SAR 영상 정합의 정확도 평가지표로, 단일채널 영상의 품질 평가 알고리즘으로 개발된 FSIM (Feature Similarity) 값을 적용하는 것에 대한 타당성 분석을 수행하였다. 다양한 관측각도 및 관측방향에서 수집된 TerraSAR-X staring spotlight 자료를 분석에 사용하였다. SAR 영상의 공간 해상도에 따른 FSIM 값 변화는 매우 작은 값을 보였다. 따라서, 다양한 공간해상도의 SAR 영상 간에도 동일한 척도를 가지고 FSIM 값을 사용할 수 있다. 단일 SAR 영상을 이용하여 정합 오차에 따른 FSIM값 변화를 분석하였으며, 이 값을 기준으로 서로 다른 관측조건에서 수집된 영상 간의 정합 오차에 따른 FSIM 값 변화를 분석하였다. 서로 다른 관측각 또는 관측방향 자료 조합에서, 관측기하 차이에 의해 FSIM 값은 다소 저하되었다. 토지피복별 FSIM 값 분석 결과에서, 도심지역에서 정합오차에 따른 FSIM 값의 변화가 가장 뚜렷하게 나타났다. 따라서, FSIM 값을 이용하여 영상정합의 정확도를 판별하기 위해서는 도심지역에서 산출된 FSIM 값을 이용하는 것이 바람직하다. FSIM 값은 SAR 영상 정합 정확도에 대한 지표로 사용될 수 있는 충분한 가능성이 있는 것으로 판단된다.


Recently, as the number of high-resolution satellite SAR images increases, the demand for precise matching of SAR images in change detection and image fusion is consistently increasing. RMSE (Root Mean Square Error) values using GCPs (Ground Control Points) selected by analysts have been widely used for quantitative evaluation of image registration results, while it is difficult to find an approach for automatically measuring the registration accuracy. In this study, a feasibility analysis was conducted on using the FSIM (Feature Similarity) index as a measure to evaluate the registration accuracy. TerraSAR-X (TSX) staring spotlight data collected from various incidence angles and orbit directions were used for the analysis. FSIM was almost independent on the spatial resolution of the SAR image. Using a single SAR image, the FSIM with respect to registration errors was analyzed, then use it to compare with the value estimated from TSX data with different imaging geometry. FSIM index slightly decreased due to the differences in imaging geometry such as different look angles, different orbit tracks. As the result of analyzing the FSIM value by land cover type, the change in the FSIM index according to the co-registration error was most evident in the urban area. Therefore, the FSIM index calculated in the urban was most suitable for determining the accuracy of image registration. It is likely that the FSIM index has sufficient potential to be used as an index for the co-registration accuracy of SAR image.

KCI등재

3GOCI와 AHI 자료를 활용한 에어로졸 광학두께 합성장 산출 연구

저자 : 강형우 ( Hyeongwoo Kang ) , 최원이 ( Wonei Choi ) , 박정현 ( Jeonghyun Park ) , 김세린 ( Serin Kim ) , 이한림 ( Hanlim Lee )

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 37권 5호 발행 연도 : 2021 페이지 : pp. 861-870 (10 pages)

다운로드

(기관인증 필요)

초록보기

본 연구에서는 COMS (Communication, Oceanography and Meteorology Satellite) 위성의GOCI (Geostationary Ocean Color Imager) 센서와 Himawari-8 위성의 AHI (Advanced Himawari Imager) 센서에서 산출되는 에어로졸 광학두께 (Aerosol Optical Depth; AOD)를 활용하여 단일화된 AOD 합성장을 생산하였다. 위성 간의 공간해상도와 위치좌표계가 다르기 때문에 이를 맞춰주는 전처리 작업을 선행하였다. 이후 지상관측 기반인 AERONET (AErosol RObotic NETwork)의 레벨 1.5 AOD 자료를 사용하여 각 위성과 AERONET과의 상관관계 분석 및 추세를 보간하여 기존 위성 AOD 보다 정확한 위성 AOD 자료를 생산하였다. 이후 합성과정을 진행하며 최종적으로 시공간적으로 더 완벽하고 정확한 AOD 합성장을 생산하였다. 생산된 AOD 합성장의 제곱근 평균 오차(Root Mean Square Error; RMSE)는 0.13, 평균 편향(mean bias)는 0.05로, 기존의 GOCI AOD (RMSE: 0.15, Mean bias: 0.11)와 AHI AOD (RMSE: 0.15, Mean bias: 0.05) 보다 나은 성능을 보였다. 또한 합성된 AOD는 단일위성에서 구름으로 인하여 관측되지 못한 지역에서 시공간적으로 보다 완벽하게 생산되었음을 확인하였다.


In this study, fused Aerosol Optical Depth (AOD) data were produced using AOD products from the Geostationary Ocean Color Imager (GOCI) onboard Communication, Oceanography and Meteorology Satellite (COMS) satellite and the Advanced Himawari Imager (AHI) onboard Himawari-8. Since the spatial resolution and the coordinate system between the satellite sensors are different, a preprocessing was first preceded. After that, using the level 1.5 AOD dataset of AErosol RObotic NETwork (AERONET), which is ground-based observation, correlations and trends between each satellite AOD and AERONET AOD were utilized to produce more accurate satellite AOD data than the original satellite AODs. The fused AOD were found to be more accurate than the original satellite AODs. Root Mean Square Error (RMSE) and mean bias of the fused AODs were calculated to be 0.13 and 0.05, respectively. We also compared errors of the fused AODs against those of the original GOCI AOD (RMSE: 0.15, mean bias: 0.11) and the original AHI AOD (RMSE: 0.15, mean bias: 0.05). It was confirmed that the fused AODs have better spatial coverage than the original AODs in areas where there are no observations due to the presence of cloud from a single satellite.

KCI등재

4항공 및 위성영상을 활용한 토지피복 관련 인공지능 학습 데이터 구축 및 알고리즘 적용 연구

저자 : 이성혁 ( Seong-hyeok Lee ) , 이명진 ( Moung-jin Lee )

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 37권 5호 발행 연도 : 2021 페이지 : pp. 871-884 (14 pages)

다운로드

(기관인증 필요)

초록보기

본 연구의 목적은 항공 및 위성영상을 활용한 토지피복 관련 인공지능 학습 데이터를 구축, 검증 및 알고리즘 적용의 효율화 방안을 연구하였다. 이를 위하여 토지피복 8개 항목에 대하여 고해상도의 항공영상 및 Sentinel-2 인공위성에서 얻은 이미지를 사용하여 0.51 m 및 10 m Multi-resolution 데이터셋을 구축하였다. 또한, 학습 데이터의 구성은 Fine data (총 17,000개) 와 Coarse data (총 33,000개)를 동시 구축 및 정밀한 변화 탐지 및 대규모 학습 데이터셋 구축이라는 2가지 목적을 달성하였다. 학습 데이터의 정확도를 위한 검수는 정제 데이터, 어노테이션 및 샘플링으로 3단계로 진행하였다. 최종적으로 검수가 완료된 학습데이터를 Semantic Segmentation 알고리즘 중 U-Net, DeeplabV3+에 적용하여, 결과를 분석하였다. 분석결과 항공영상 기반의 토지피복 평균 정확도는 U- Net 77.8%, Deeplab V3+ 76.3% 및 위성영상 기반의 토지피복에 대한 평균 정확도는 U-Net 91.4%, Deeplab V3+ 85.8%이다. 본 연구를 통하여 구축된 고해상도 항공영상 및 위성영상을 이용한 토지피복 인공지능 학습 데이터셋은 토지피복 변화 및 분류에 도움이 되는 참조자료로 활용이 가능하다. 향후 우리나라 전체를 대상으로 인공지능 학습 데이터셋 구축 시, 토지피복을 연구하는 다양한 인공지능 분야에 활용될 것으로 기대된다.


The purpose of this study was to determine ways to increase efficiency in constructing and verifying artificial intelligence learning data on land cover using aerial and satellite images, and in applying the data to AI learning algorithms. To this end, multi-resolution datasets of 0.51 m and 10 m each for 8 categories of land cover were constructed using high-resolution aerial images and satellite images obtained from Sentinel-2 satellites. Furthermore, fine data (a total of 17,000 pieces) and coarse data (a total of 33,000 pieces) were simultaneously constructed to achieve the following two goals: precise detection of land cover changes and the establishment of large-scale learning datasets. To secure the accuracy of the learning data, the verification was performed in three steps, which included data refining, annotation, and sampling. The learning data that was finally verified was applied to the semantic segmentation algorithms U-Net and DeeplabV3+, and the results were analyzed. Based on the analysis, the average accuracy for land cover based on aerial imagery was 77.8% for U-Net and 76.3% for Deeplab V3+, while for land cover based on satellite imagery it was 91.4% for U-Net and 85.8% for Deeplab V3+. The artificial intelligence learning datasets on land cover constructed using high-resolution aerial and satellite images in this study can be used as reference data to help classify land cover and identify relevant changes. Therefore, it is expected that this study's findings can be used in the future in various fields of artificial intelligence studying land cover in constructing an artificial intelligence learning dataset on land cover of the whole of Korea.

KCI등재

5천리안위성 2A호 고속 관측 영상의 시·공간 해상도가 중규모 대기운동벡터 산출에 미치는 영향 분석

저자 : 김희애 ( Hee-ae Kim ) , 정성래 ( Sung-rae Chung ) , 오수민 ( Soo Min Oh ) , 이병일 ( Byung-il Lee ) , 신인철 ( In-chul Shin )

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 37권 5호 발행 연도 : 2021 페이지 : pp. 885-901 (17 pages)

다운로드

(기관인증 필요)

초록보기

천리안위성 2A호의 2분 주기 고속 관측(rapid-scan) 자료를 이용하여, 가시·수증기·적외 채널의 시간 해상도와 표적의 크기가 해당 채널의 중규모 대기운동벡터 생산에 미치는 영향을 분석하였다. 중규모 대기운동벡터 산출을 위하여 2-10분의 영상 시간 간격 변화 하에서 표적의 크기를 8×8에서 40×40 화소 크기로 변환시키며, 시·공간적인 조건 변화에 따른 벡터 생산량과 평균 속력, 오차 특성의 변화 양상을 비교하였다. 그 결과, 표적의 크기가 작을수록 위성의 시간 간격 변화에 따른 벡터 개수의 변화와, 표준화된 평균 제곱근 편차(Normalized Root Mean Squared Vector Difference; NRMSVD) 값의 변화가 더욱 뚜렷해졌다. 또한 고도별 오차 특성 분석 결과에서는 평균 속력이 낮고 대기 현상의 시·공간 규모가 작은 하층(700-1000 hPa)의 경우, 짧은 시간 간격의 영상 자료와 작은 표적을 이용하는 것이 벡터 산출에 더욱 유리하게 작용하는 것을 확인할 수 있었다. 위성의 시간 간격과 표적의 크기는 대기 순환의 시·공간 규모와 밀접한 연관이 있는 요소이다. 따라서, 대기운동벡터 활용 목적에 맞게 표적 크기와 위성 시간 간격을 최적화하는 과정이 필요하며, 중규모 기상현상의 실황 분석을 위한 대기운동벡터 산출 알고리즘에서는 표적 크기와 영상 시간 간격을 각각 16×16, 4분으로 설정해주는 것이 가장 적합하다고 판단된다.


This paper illustrates the impact of the temporal gap between satellite images and target size in mesoscale atmospheric motion vector (AMV) algorithm. A test has been performed using GEO-KOMPSAT-2A (GK2A) rapid-scan data sets with a temporal gap varying between 2 and 10 minutes and a target size between 8×8 and 40×40. Results show the variation of the number of AMVs produced, mean AMV speed, and validation scores as a function of temporal gap and target size. As a results, it was confirmed that the change in the number of vectors and the normalized root-mean squared vector difference (NRMSVD) became more pronounced when smaller targets are used. In addition, it was advantageous to use shorter temporal gap and smaller target size for the AMV calculation in the lower layer, where the average speed is low and the spatio-temporal scale of atmospheric phenomena is small. The temporal gap and the target size are closely related to the spatial and temporal scale of the atmospheric circulation to be observed with AMVs. Thus, selecting the target size and temporal gap for an optimum calculation of AMVs requires considering them. This paper recommends that the optimized configuration to be used operationally for the near-real time analysis of mesoscale meteorological phenomena is 4-min temporal gap and 16×16 pixel target size, respectively.

KCI등재

6오픈소스 GIS 프로그램의 지형인자 계산 비교: 도서지역 경사도와 지형습윤지수 중심으로

저자 : 이보라 ( Bora Lee ) , 이호상 ( Ho-sang Lee ) , 이광수 ( Gwang-soo Lee )

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 37권 5호 발행 연도 : 2021 페이지 : pp. 903-916 (14 pages)

다운로드

(기관인증 필요)

초록보기

지형은 고도, 경사, 측면으로 설명되는 지표면의 물리적인 모양을 나타내는 것으로 지형적 조건에 따라 에너지의 이동이 결정된다. 이것은 태양 에너지를 얼마나 많이 받을지, 바람이나 비가 얼마나 많은 영향을 미칠지 등에 대한 중요한 결정 요인들로 지표면 상에 존재하는 모든 생물, 특히 산림 식생의 입지 환경에 큰 영향을 준다. 도서지역 산림과 같이 자연적으로 형성된 지형 인자가 산림 식생의 생태환경을 결정하는 요인이 될 때 보다 정확한 지형 인자들의 계산은 도서산림의 입지환경을 이해하는데 매우 중요하다. 최근에는 연구자, 학교, 산업 및 정부를 위해 수많은 무료오픈소스 소프트웨어 지리정보시스템 프로그램(Free Open Source Software Geographic Information Systems, FOSS GIS)들이 이러한 지형인자들을 보다 정확하게 계산하기 위해 다양한 알고리즘을 적용하고 있다. FOSS GIS 프로그램은 사용자 요구에 맞게 수정이 가능한 유연한 알고리즘을 제공한다. 이와 같은 수요에 맞춰 이 연구에서는 지형 분석이 특히 중요한 도서지역 산림을 대상으로 하여 FOSS GIS 프로그램들의 지형인자 계산 결과값을 비교해 보고 향후 지역 생태 연구에 있어 지형 인자 계산 방법을 결정할 때 그 기준을 마련하고자 한다. 연구 지역은 전라남도 도서 지역을 대상으로 하였고 FOSS GIS 프로그램 중 가장 널리 사용되는 GRASS GIS와 SAGA GIS로 처리하였다. 입지환경에 있어 가장 널리 사용되는 설명인자인 경사도와 TWI(Topographical Wetness Index) 지도를 각 FOSS GIS 프로그램으로 생성하고 그 차이를 분석하여 각 FOSS GIS 프로그램의 장단점을 토의하였다.


An area's topography refers to the shape of the earth's surface, described by its elevation, slope, and aspect, among other features. The topographical conditions determine energy flows that move water and energy from higher to lower elevations, such as how much solar energy will be received and how much wind or rain will affect it. Another common factor, the topographic wetness index (TWI), is a calculation in digital elevation models of the tendency to accumulate water per slope and unit area, and is one of the most widely referenced hydrologic topographic factors, which helps explain the location of forest vegetation. Analyses of topographical factors can be calculated using a geographic information system (GIS) program based on digital elevation model (DEM) data. Recently, a large number of free open source software (FOSS) GIS programs are available and developed for researchers, industries, and governments. FOSS GIS programs provide opportunities for flexible algorithms customized for specific user needs. The majority of biodiversity in island areas exists at about 20% higher elevations than in land ecosystems, playing an important role in ecological processes and therefore of high ecological value. However, island areas are vulnerable to disturbances and damage, such as through climate change, environmental pollution, development, and human intervention, and lacks systematic investigation due to geographical limitations (e.g. remoteness; difficulty to access). More than 4,000 of Korea's islands are within a few hours of its coast, and 88% are uninhabited, with 52% of them forested. The forest ecosystems of islands have fewer encounters with human interaction than on land, and therefore most of the topographical conditions are formed naturally and affected more directly by weather conditions or the environment. Therefore, the analysis of forest topography in island areas can be done more precisely than on its land counterparts, and therefore has become a major focus of attention in Korea. This study is focused on calculating the performance of different topographical factors using FOSS GIS programs. The test area is the island forests in Korea's south and the DEM of the target area was processed with GRASS GIS and SAGA GIS. The final slopes and TWI maps were produced as comparisons of the differences between topographic factor calculations of each respective FOSS GIS program. Finally, the merits of each FOSS GIS program used to calculate the topographic factors is discussed.

KCI등재

7무인기 기반 다중분광 영상을 이용한 벼 쓰러짐 영역의 특성 분석

저자 : 문현동 ( Hyun-dong Moon ) , 류재현 ( Jae-hyun Ryu ) , 나상일 ( Sang-il Na ) , 장선웅 ( Seon Woong Jang ) , 신서호 ( Seo-ho Sin ) , 조재일 ( Jaeil Cho )

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 37권 5호 발행 연도 : 2021 페이지 : pp. 917-926 (10 pages)

다운로드

(기관인증 필요)

초록보기

벼 쓰러짐은 벼농사의 대표적인 기상재해 피해로써 강한 바람과 강우로 발생한다. 원격탐사 기법은 넓은 지역의 벼 쓰러짐을 효과적으로 탐지하기에 적절한 방법이다. 실제로 벼 쓰러짐은 벼 키가 최대인 생육 시기에 주로 발생하여 군락의 큰 구조적 변화를 불러오기 때문에 분광 반사도 차이를 야기한다. 따라서, 본고에서는 나주에 위치한 전남농업기술원의 2020년 태풍에 의한 논벼 피해를 444 nm부터 842 nm까지 10개 밴드로 구성된 카메라 영상으로 분석하였다. 드론 영상마다 벼 쓰러짐 피해를 받은 영역과 벼 쓰러짐 피해가 없는 영역으로 구분하여 벼 쓰러짐 영역의 분광 반사도 특성 차이와 식생 탐지에 주로 사용되는 식생지수인 NDVI (Normalized Difference Vegetation Index), NDRE (Normalized Difference Red Edge), CCI (Chlorophyll Carotenoid Index)의 변화를 살펴보았다. 반사도 값의 변화는 밴드6(668 nm)에서 가장 적었으며, 이를 중심으로 밴드 파장이 감소와 증가할수록 일반 논벼 보다 쓰러짐 영역 반사도가 커졌다. 또한, 쓰러진 벼를 묶어 세운 복구 지역은 대부분의 밴드에 걸쳐 반사도가 크게 감소함을 볼 수 있었다. NDVI와 NDRE는 벼 쓰러짐 영역에 대해 민감하게 반응하였으나, 그 반응 대상 및 정도는 서로 달랐다. 본 연구의 결과는 향후 드론과 위성을 이용한 벼 쓰러짐 피해 조사 알고리즘에 기여될 것으로 기대한다.


Lodging rice is one of critical agro-meteorological disasters. In this study, the UAV-based multispectral imageries before and after rice lodging in rice paddy field of Jeollanamdo agricultural research and extension services in 2020 was analyzed. The UAV imagery on 14th Aug. includes the paddy rice without any damage. However, 4th and 19th Sep. showed the area of rice lodging. Multispectral camera of 10 bands from 444 nm to 842 nm was used. At the area of restoration work against lodging rice, the reflectance from 531 nm to 842 nm were decreased in comparison to un-lodging rice. At the area of lodging rice, the reflectance of around 668 nm had small increases. Further, the blue and NIR (Near-Infrared) wavelength had larger. However, according to the types of lodging, the change of reflectance was different. The NDVI (Normalized Difference Vegetation Index) and NDRE (Normalized Difference Red Edge) shows dome sensitivities to lodging rice, but they were different to types of lodging. These results will be useful to make algorithm to detect the area of lodging rice using a UAV.

KCI등재

8신경망 모델을 사용한 편대비행 저궤도위성 가속도계 데이터 예측 기법

저자 : 김민규 ( Mingyu Kim ) , 김정래 ( Jeongrae Kim )

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 37권 5호 발행 연도 : 2021 페이지 : pp. 927-938 (12 pages)

다운로드

(기관인증 필요)

초록보기

편대 비행하는 저궤도위성에는 비슷한 크기의 비중력 섭동이 일정한 시간 차이를 두고 가해진다. 이러한 시간상관관계를 이용하면 한 개 위성의 가속도계에서 측정된 가속도 값으로 다른 편대비행 저궤도위성의 비중력가속도를 추정할 수 있다. 편대비행 저궤도위성인 GRACE 및 GRACE-FO 위성에서 한 개 위성의 가속도계 데이터를 사용할 수 없는 기간이 존재하는데, 앞서 기술된 시간 이식 기법이 JPL (Jet Propulsion Laboratory)에서 공식적으로 가속도계 데이터 복원 시 사용되고 있다. 본 논문에서는 기존의 시간 이식 기법의 가속도계 추정 정확도를 개선하기 위하여 신경망 (neural network; NN) 모델 기반 편대비행 저궤도위성 가속도계 데이터 추정 방법을 제안하였다. 시간 이식 기법은 위성의 위치 및 우주환경요소 등을 반영할 수 없지만, NN 모델은 이를 모델 입력으로 사용할 수 있으므로 예측 정확도를 높일 수 있다. 1개월간 NN 모델을 사용하여 가속도계 예측 시험을 수행하고 시간 이식 기법과 예측 정확도를 비교하였다. 그 결과 along-track 및 radial 방향에서 NN 모델의 가속도계 데이터의 예측 오차는 시간 이식 기법에 비해 각각 55.0%, 40.1% 감소하였다.


A similar magnitude of non-gravitational perturbations are act on the formation flying low earth orbit satellites with a certain time difference. Using this temporal correlation, the non-gravity acceleration of the low earth orbiting satellites can be transferred for the other satellites. There is a period in which the accelerometer data of one satellite is unavailable for GRACE and GRACE-FO satellites. In this case, the accelerometer data transplant method described above is officially used to recover the accelerometer data at the Jet Propulsion Laboratory (JPL). In this paper, we proposed a model for predicting accelerometer data of formation flying low earth orbit satellites using a neural network (NN) model to improve the estimation accuracy of the transplant method. Although the transplant method cannot reflect the satellite's position and space environmental factors, the NN model can use them as model inputs to increase the prediction accuracy. A prediction test of an accelerometer data using NN model was performed for one month, and the prediction accuracy was compared with the transplant method. The NN model outperforms the transplant method with 55.0% and 40.1% error reduction in the along-track and radial directions, respectively.

KCI등재

9산불 후 식생 회복 모니터링을 위한 Sentinel-2 위성영상의 RGB 합성기술

저자 : 김상일 ( Sang-il Kim ) , 안도섭 ( Do-seob Ahn ) , 김승철 ( Seung-chul Kim )

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 37권 5호 발행 연도 : 2021 페이지 : pp. 939-946 (8 pages)

다운로드

(기관인증 필요)

초록보기

산불로 인한 피해지역의 산림 변화를 모니터링하는 것은 식생복원에 중요한 정보를 제공하며, 자연 재해를 완화하고 복구하기 위해 공간정보를 가지는 원격탐사 자료는 모니터링에 필요한 유용한 정보를 제공하는 것으로 알려져 있다. 하지만 원격탐사자료를 활용한 복구 측면에 초점 두어 연구된 사례가 미비한 상황이다. 본 연구는 화재 후 식생회복을 모니터링하기 위한 것으로, Sentinel-2 위성 데이터를 사용하여 산불 피해 지역을 모니터링하는 방법을 제시하는 것을 목적으로 한다. 산불피해지역의 식생회복 모니터링을 위해 Tasseled Cap 선형회귀 추세를 기반으로 RGB 합성기술을 제안하였다. 이러한 위성영상을 활용한 원격탐사 시각화 기법을 통해 효과적인 모니터링 가능성을 확인할 수 있었다.


Monitoring of post wildfire provides important information for vegetation restoration. In particular, remote sensing data are known to provide useful information necessary for monitoring. However, there are insufficient research results which is monitoring the vegetation recovery using remote sensing data. This study is directed to monitoring post-wildfire vegetation restoration. It proposes a method for monitoring vegetation restoration using Sentinel-2 satellite data by compositing Tasseled Cap linear regression trend in a post wildfire study sites. Although it is a simple visualization technique using satellite images, it was able to confirm the possibility of effective monitoring.

KCI등재

10무인비행체 탑재 다중분광 센서별 반사율 및 식생지수 변화 비교

저자 : 이경도 ( Kyung-do Lee ) , 안호용 ( Ho-yong Ahn ) , 류재현 ( Jae-hyun Ryu ) , 소규호 ( Kyu-ho So ) , 나상일 ( Sang-il Na )

발행기관 : 대한원격탐사학회 간행물 : 대한원격탐사학회지 37권 5호 발행 연도 : 2021 페이지 : pp. 947-958 (12 pages)

다운로드

(기관인증 필요)

초록보기

본 연구는 무인비행체에 탑재해서 활용되고 있는 다중분광 센서의 센서별 반사율 및 식생지수를 산정하여 시계열 작황분석을 위한 센서별, 센서간 활용 가능성을 평가하기 위해 수행하였다. RedEdge-MX, S110 NIR, Sequioa, P4M 등 4종의 무인비행체 탑재 다중분광센서에 대하여 2020년 9월 14일과 9월 15일에 걸쳐 오전, 오후 각 1회, 총 4회씩 항공영상을 촬영하고 반사율 및NDVI를 산정하여 비교하였다. 반사율의 경우 모든 센서에서 시계열 변동계수가 평균 약 10% 이상의 값을 보여 활용에는 한계가 있는 것으로 나타났다. 작물 시험구에 대한 센서별NDVI 변동계수는 식생이 우거져 활력도가 높은 시험구에서 평균 1.2~3.6%의 값을 보여 5% 이내의 변동성을 보였다. 그러나 이는 청천일의 변동계수에 비해서는 높은 값을 보인 것으로서 실험 기간 동안 오전, 오후에 구름 등 기상환경이 달랐기 때문으로 판단되며 시계열 작황 분석을 위한 정밀NDVI 산정 시에는 일정한 광 환경을 유지할 수 있는 촬영 계획 수립과 이행이 필요할 것으로 판단된다. 무인비행체 다중분광센서 간NDVI를 상호 비교한 결과 본 실험에서는 RedEdeg-MX 센서의 경우 안정적인 광 환경 내에서 동종의 센서를 여러 대 사용하더라도NDVI 값의 특별한 보정 없이 함께 활용할 수 있을 것으로 판단된다. RedEdge-MX, P4M, Sequioa 센서는 상호 선형적인 관계를 보였으나NDVI 간의 off-set 보정을 통한 공동 활용 가능성 평가를 위해서는 보완 실험이 필요할 것으로 생각된다.


This study was conducted to provide basic data for crop monitoring by comparing and analyzing changes in reflectance and vegetation index by sensor of multi-spectral sensors mounted on unmanned aerial vehicles. For four types of unmanned aerial vehicle-mounted multispectral sensors, such as RedEdge-MX, S110 NIR, Sequioa, and P4M, on September 14 and September 15, 2020, aerial images were taken, once in the morning and in the afternoon, a total of 4 times, and reflectance and vegetation index were calculated and compared. In the case of reflectance, the time-series coefficient of variation of all sensors showed an average value of about 10% or more, indicating that there is a limit to its use. The coefficient of variation of the vegetation index by sensor for the crop test group showed an average value of 1.2 to 3.6% in the crop experimental sites with high vitality due to thick vegetation, showing variability within 5%. However, this was a higher value than the coefficient of variation on a clear day, and it is estimated that the weather conditions such as clouds were different in the morning and afternoon during the experiment period. It is thought that it is necessary to establish and implement a UAV flight plan. As a result of comparing the NDVI between the multi-spectral sensors of the unmanned aerial vehicle, in this experiment, it is thought that the RedEdeg-MX sensor can be used together without special correction of the NDVI value even if several sensors of the same type are used in a stable light environment. RedEdge-MX, P4M, and Sequioa sensors showed a linear relationship with each other, but supplementary experiments are needed to evaluate joint utilization through off-set correction between vegetation indices.

권호별 보기
같은 권호 다른 논문
| | | | 다운로드

KCI등재

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)

다운로드

(기관인증 필요)

초록보기

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.

KCI등재

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)

다운로드

(기관인증 필요)

초록보기

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.

KCI등재

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)

다운로드

(기관인증 필요)

초록보기

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.

KCI등재

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)

다운로드

(기관인증 필요)

초록보기

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.

KCI등재

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)

다운로드

(기관인증 필요)

초록보기

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.

KCI등재

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)

다운로드

(기관인증 필요)

초록보기

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.

KCI등재

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)

다운로드

(기관인증 필요)

초록보기

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.

KCI등재

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)

다운로드

(기관인증 필요)

초록보기

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.

KCI등재

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)

다운로드

(기관인증 필요)

초록보기

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.

KCI등재

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)

다운로드

(기관인증 필요)

초록보기

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.

1
발행기관 최신논문
자료제공: 네이버학술정보
발행기관 최신논문
자료제공: 네이버학술정보

내가 찾은 최근 검색어

최근 열람 자료

맞춤 논문

보관함

내 보관함
공유한 보관함

1:1문의

닫기