• Title/Summary/Keyword: Sentinel-1A

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Activity of the Fushun West Open-pit Mine in China Observed by Sentinel-1 InSAR Coherence Images

  • Jung, Da-woon;Lee, Hoonyol
    • Korean Journal of Remote Sensing
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    • v.38 no.4
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    • pp.365-374
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    • 2022
  • Mining activity causes environmental pollution and geological hazards such as ground subsidence or landslide of which continuous monitoring is necessary. In this study, the activity on the Fushun West Open-Pit Mine (FWOPM), one of the largest open-pit coal mines in Asia located in Fushun, Liaoning Province, China, was analyzed by using a time-series Sentinel-1 InSAR coherence dataset. By using the difference between the two Digital Elevation Models (DEM) of the area, it was possible to confirm that there was a stockpiling activity in the western area of the FWOPM while excavation activity in the eastern area. By using RGB composite images using the yearly-averaged InSAR coherence images, the activity of the mine was confirmed by period, which was confirmed by Google Earth optical images. As a result, it was possible to confirm three landslides and the related activities on the northwest slope and the dumping activity on the west slope of FWOPM.

Experimental Retrieval of Soil Moisture for Cropland in South Korea Using Sentinel-1 SAR Data (Sentinel-1 SAR 데이터를 이용한 우리나라 농지의 토양수분 산출 실험)

  • Lee, Soo-Jin;Hong, Sungwook;Cho, Jaeil;Lee, Yang-Won
    • Korean Journal of Remote Sensing
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    • v.33 no.6_1
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    • pp.947-960
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    • 2017
  • Soil moisture plays an important role to affect the Earth's radiative energy balance and water cycle. In general, satellite observations are useful for estimating the soil moisture content. Passive microwave satellites have an advantage of direct sensitivity on surface soil moisture. However, their coarse spatial resolutions (10-36 km) are not suitable for regional-scale hydrological applications. Meanwhile, in-situ ground observations of point-based soil moisture content have the disadvantage of spatially discontinuous information. This paper presents an experimental soil moisture retrieval using Sentinel-1 SAR (Synthetic Aperture Radar) with 10m spatial resolution for cropland in South Korea. We developed a soil moisture retrieval algorithm based on the technique of linear regression and SVR (support vector regression) using the ground observations at five in-situ sites and Sentinel-1 SAR data from April to October in 2015-2017 period. Our results showed the polarization dependency on the different soil sensitivities at backscattered signals, but no polarization dependence on the accuracies. No particular seasonal characteristics of the soil moisture retrieval imply that soil moisture is generally more affected by hydro-meteorology and land surface characteristics than by phenological factors. At the narrower range of incidence angles, the relationship between the backscattered signal and soil moisture content was more distinct because the decreasing surface interference increased the retrieval accuracies under the condition of evenly distributed soil moisture (during the raining period or on the paddy field). We had an overall error estimate of RMSE (root mean square error) of approximately 6.5%. Our soil moisture retrieval algorithm will be improved if the effects of surface roughness, geomorphology, and soil properties would be considered in the future works.

Early Estimation of Rice Cultivation in Gimje-si Using Sentinel-1 and UAV Imagery (Sentinel-1 및 UAV 영상을 활용한 김제시 벼 재배 조기 추정)

  • Lee, Kyung-do;Kim, Sook-gyeong;Ahn, Ho-yong;So, Kyu-ho;Na, Sang-il
    • Korean Journal of Remote Sensing
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    • v.37 no.3
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    • pp.503-514
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    • 2021
  • Rice production with adequate level of area is important for decision making of rice supply and demand policy. It is essential to grasp rice cultivation areas in advance for estimating rice production of the year. This study was carried out to classify paddy rice cultivation in Gimje-si using sentinel-1 SAR (synthetic aperture radar) and UAV imagery in early July. Time-series Sentinel-1A and 1B images acquired from early May to early July were processed to convert into sigma naught (dB) images using SNAP (SeNtinel application platform, Version 8.0) toolbox provided by European Space Agency. Farm map and parcel map, which are spatial data of vector polygon, were used to stratify paddy field population for classifying rice paddy cultivation. To distinguish paddy rice from other crops grown in the paddy fields, we used the decision tree method using threshold levels and random forest model. Random forest model, trained by mainly rice cultivation area and rice and soybean cultivation area in UAV image area, showed the best performance as overall accuracy 89.9%, Kappa coefficient 0.774. Through this, we were able to confirm the possibility of early estimation of rice cultivation area in Gimje-si using UAV image.

Clinical outcomes after sentinel lymph node biopsy in clinically node-negative breast cancer patients

  • Han, Hee Ji;Kim, Ju Ree;Nam, Hee Rim;Keum, Ki Chang;Suh, Chang Ok;Kim, Yong Bae
    • Radiation Oncology Journal
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    • v.32 no.3
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    • pp.132-137
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    • 2014
  • Purpose: To evaluate non-sentinel lymph node (LN) status after sentinel lymph node biopsy (SNB) in patients with breast cancer and to identify the predictive factors for disease failure. Materials and Methods: From January 2006 to December 2007, axillary lymph node (ALN) dissection after SNB was performed for patients with primary invasive breast cancer who had no clinical evidence of LN metastasis. A total of 320 patients were treated with breast-conserving surgery and radiotherapy. Results: The median age of patients was 48 years, and the median follow-up time was 72.8 months. Close resection margin (RM) was observed in 13 patients. The median number of dissected SNB was two, and that of total retrieved ALNs was 11. Sentinel node accuracy was 94.7%, and the overall false negative rate (FNR) was 5.3%. Eleven patients experienced treatment failure. Local recurrence, regional LN recurrence, and distant metastasis were identified in 0.9%, 1.9%, and 2.8% of these patients, respectively. Sentinel LN status were not associated with locoregional recurrence (p > 0.05). Close RM was the only significant factor for disease-free survival (DFS) in univariate and multivariate analysis. The 5-year overall survival, DFS, and locoregional DFS were 100%, 96.8%, and 98.1%, respectively. Conclusion: In this study, SNB was performed with high accuracy and low FNR and high locoregional control was achieved.

Atmospheric Correction of Sentinel-2 Images Using Enhanced AOD Information

  • Kim, Seoyeon;Lee, Yangwon
    • Korean Journal of Remote Sensing
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    • v.38 no.1
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    • pp.83-101
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    • 2022
  • Accurate atmospheric correction is essential for the analysis of land surface and environmental monitoring. Aerosol optical depth (AOD) information is particularly important in atmospheric correction because the radiation attenuation by Mie scattering makes the differences between the radiation calculated at the satellite sensor and the radiation measured at the land surface. Thus, it is necessary to use high-quality AOD data for an appropriate atmospheric correction of high-resolution satellite images. In this study, we examined the Second Simulation of a Satellite Signal in the Solar Spectrum (6S)-based atmospheric correction results for the Sentinel-2 images in South Korea using raster AOD (MODIS) and single-point AOD (AERONET). The 6S result was overall agreed with the Sentinel-2 level 2 data. Moreover, using raster AOD showed better performance than using single-point AOD. The atmospheric correction using the single-point AOD yielded some inappropriate values for forest and water pixels, where as the atmospheric correction using raster AOD produced stable and natural patterns in accordance with the land cover map. Also, the Sentinel-2 normalized difference vegetation index (NDVI) after the 6S correction had similar patterns to the up scaled drone NDVI, although Sentinel-2 NDVI had relatively low values. Also, the spatial distribution of both images seemed very similar for growing and harvest seasons. Future work will be necessary to make efforts for the gap-filling of AOD data and an accurate bi-directional reflectance distribution function (BRDF) model for high-resolution atmospheric correction. These methods can help improve the land surface monitoring using the future Compact Advanced Satellite 500 in South Korea.

Application of KOMPSAT-5 SAR Interferometry by using SNAP Software (SNAP 소프트웨어를 이용한 KOMPSAT-5 SAR 간섭기법 구현)

  • Lee, Hoonyol
    • Korean Journal of Remote Sensing
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    • v.33 no.6_3
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    • pp.1215-1221
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    • 2017
  • SeNtinel's Application Platform (SNAP) is an open source software developed by the European Space Agency and consists of several toolboxes that process data from Sentinel satellite series, including SAR (Synthetic Aperture Radar) and optical satellites. Among them, S1TBX (Sentinel-1 ToolBoX)is mainly used to process Sentinel-1A/BSAR images and interferometric techniques. It provides flowchart processing method such as Graph Builder, and has convenient functions including automatic downloading of DEM (Digital Elevation Model) and image mosaicking. Therefore, if computer memory is sufficient, InSAR (Interferometric SAR) and DInSAR (Differential InSAR) perform smoothly and are widely used recently in the world through rapid upgrades. S1TBX also includes existing SAR data processing functions, and since version 5, the processing capability of KOMPSAT-5 has been added. This paper shows an example of processing the interference technique of KOMPSAT-5 SAR image using S1TBX of SNAP. In the open mine of Tavan Tolgoi in Mongolia, the difference between DEM obtained in KOMPSAT-5 in 2015 and SRTM 1sec DEM obtained in 2000 was analyzed. It was found that the maximum depth of 130 meters was excavated and the height of the accumulated ore is over 70 meters during 15 years. Tidal and topographic InSAR signals were observed in the glacier area near Jangbogo Antarctic Research Station, but SNAP was not able to treat it due to orbit error and DEM error. In addition, several DInSAR images were made in the Iraqi desert region, but many lines appearing in systematic errors were found on coherence images. Stacking for StaMPS application was not possible due to orbit error or program bug. It is expected that SNAP can resolve the problem owing to a surge in users and a very fast upgrade of the software.

Analysis of Algal Bloom Occurrence Characteristics Namyang Lake using Sentinel-2 MSI (Sentinel-2 MSI를 활용한 남양 간척담수호의 조류발생 특성 분석)

  • Wonjin Jang;Jinuk Kim;Jiwan Lee;Yongeun Park;Seongjoon Kim
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.56-56
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    • 2023
  • 남양호는 농업용수 공급을 위해 건설된 하구 담수호로 과도한 영양물질 축적으로 인해 매년 여름 녹조류가 번성한다. 따라서 본 연구에서는 조류발생 특성을 분석하고자 식물성 플랑크톤 및 관련 분해 산물에 의해 고유 광학특성을 가지고 있는 Chlorophyll-a(Chl-a)의 추정을 통한 녹조 발생을 파악하고자 Sentinel-2 Multi Spectral Image(MSI)의 원격 반사율 광학 스펙트럼을 사용하였다. Chl-a 추정알고리즘 개발을 위하여 Sentinel-2 A, B의 교차 방문주기인 5일 간격에 맞추어 현장수질자료(2022년: 27회 2023년: 27회)를 측정하였다. Chl-a 농도는 EXO-YSI를이용하여 측정하였으며 해당기간동안 9.4 ~ 127.1 mg/L의 범위를 보였으며, Sentine-2 자료는 A, B자료에서 B1(443 nm) ~ B8A(865 nm)파장의 값을 기상조건(구름, 안개, 강수)을 고려하여 현장수질측정 위치에서 반사도를 추출하였다. 입력자료는 대기 및 방사영향을 고려해 반사도 간의 비율자료와 선행연구에서 활용된 반사도를 활용하였으며 알고리즘은 다중선형회귀분석(Multi Linear Regression Model)과 Random Forest를 활용하였다. MLR의 경우 결정계수(R2)가 학습 및 검증에서 각각 0.68, 0.59의 성능을 보였으며, RF의 경우 각각 0.94, 0.85의 성능을 보였다. 해당알고리즘으로 생성된 Chl-a 시공간농도 자료는 담수호내 조류발생 특성을 분석하고 효율적 조류관리 및 대처에 활용될 것으로 판단된다.

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Performance of Random Forest Classifier for Flood Mapping Using Sentinel-1 SAR Images

  • Chu, Yongjae;Lee, Hoonyol
    • Korean Journal of Remote Sensing
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    • v.38 no.4
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    • pp.375-386
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    • 2022
  • The city of Khartoum, the capital of Sudan, was heavily damaged by the flood of the Nile in 2020. Classification using satellite images can define the damaged area and help emergency response. As Synthetic Aperture Radar (SAR) uses microwave that can penetrate cloud, it is suitable to use in the flood study. In this study, Random Forest classifier, one of the supervised classification algorithms, was applied to the flood event in Khartoum with various sizes of the training dataset and number of images using Sentinel-1 SAR. To create a training dataset, we used unsupervised classification and visual inspection. Firstly, Random Forest was performed by reducing the size of each class of the training dataset, but no notable difference was found. Next, we performed Random Forest with various number of images. Accuracy became better as the number of images in creased, but converged to a maximum value when the dataset covers the duration from flood to the completion of drainage.

A Study on the Radiometric Correction of Sentinel-1 HV Data for Arctic Sea Ice Detection (북극해 해빙 탐지를 위한 Sentinel-1 HV자료의 방사보정 연구)

  • Kim, Yunjee;Kim, Duk-jin;Kwon, Ui-Jin;Kim, Hyun-Cheol
    • Korean Journal of Remote Sensing
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    • v.34 no.6_2
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    • pp.1273-1282
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    • 2018
  • Recently, active research on the Arctic Ocean has been conducted due to the influence of global warming and new Arctic ship route. Although previous studies already calculated quantitative extent of sea ice using passive microwave radiometers, melting at the edge of sea ice and surface roughness were hardly considered due to low spatial resolution. Since Sentienl-1A/B data in Extended Wide (EW) mode are being distributed as free of charge and bulk data for Arctic sea can be generated during a short period, the entire Arctic sea ice data can be covered in high spatial resolution by mosaicking bulk data. However, Sentinel-1A/B data in EW mode, especially in HV polarization, needs significant radiometric correction for further classification. Thus, in this study, we developed algorithms that can correct thermal noise and scalloping effects, and confirmed that Arctic sea ice and open-water were well classified using the corrected dual-polarization SAR data.

Flow Velocity Change of David Glacier, East Antarctica, from 2016 to 2020 Observed by Sentinel-1A SAR Offset Tracking Method

  • Moon, Jihyun;Cho, Yuri;Lee, Hoonyol
    • Korean Journal of Remote Sensing
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    • v.37 no.1
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    • pp.1-11
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    • 2021
  • This study measures the change of ice flow velocity of David Glacier, one of the fast-moving glaciers in East Antarctica that drains through Drygalski Ice Tongue. In order to effectively observe the rapid flow velocity, we applied the offset tracking technique to Sentinel-1A SAR images obtained from 2016 to 2020 with 36-day temporal baseline. The resulting velocity maps were averaged and the two relatively fast points (A1 and A2) were selected for further time-series analysis. The flow velocity increased during the Antarctic summer (around December to March) over the four years' observation period probably due to the ice surface melting and reduced friction on the ice bottom. Bedmap2 showed that the fast flow velocities at A1 and A2 are associated with a sharp decrease in the ice surface and bottom elevation so that ice volumetric cross-section narrows down and the crevasses are being created on the ice surface. The local maxima in standard deviation of ice velocity, S1 and S2, showed random temporal fluctuation due to the rotational ice swirls causing error in offset tracking method. It is suggested that more robust offset tracking method is necessary to incorporate rotational motion.