• Title/Summary/Keyword: Very High Resolution Satellite Imagery

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A Study on RFM Based Stereo Radargrammetry Using TerraSAR-X Datasets (스테레오 TerraSAR-X 자료를 이용한 RFM 기반 Radargrammetry에 관한 연구)

  • Bang, SooNam;Koh, JinWoo;Yun, KongHyun;Kwak, JunHyuck
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.32 no.1D
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    • pp.89-94
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    • 2012
  • The RFM (Rational Function Model), as an alternative to physical sensor models has been widely used for photogrammetric processing of high resolution optical satellite imagery. However, the application of RF modeling to the SAR (Synthetic Aperture Radar) is very limited. In this paper, stereo radargrammetric processing of TerraSAR-X stereo pairs with RFM is implemented and analyzed. The investigation has shown that the accuracy of TerraSAR-X DSM is similar to that of the commercial S/W product. Finally, it is demonstrated that RFM is effective and feasible in the application to the radargrammetric SAR image processing.

Effect Analysis of Worldview-3 SWIR Bands for Wetland Classification in Suncheon Bay, South Korea

  • Han, Youkyung;Jung, Sejung;Park, Honglyun;Choi, Jaewan
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.36 no.5
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    • pp.371-379
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    • 2018
  • Unlike general VHR (Very-High-Resolution) satellite sensors that are mainly for panchromatic and MS (Multispectral) imaging, Worldview-3 sensor additionally provides eight SWIR (Short Wavelength Infrared) bands in wavelength range from 1198 nm to 2365 nm. This study investigates the effect of informative Worldview-3 SWIR bands for wetland classification performance. Worldview-3 imagery acquired over Sunchon Bay, which is a coastal wetland located in South Korea, is used to implement the classification. Land-cover classes for the scene are determined by referring to national land-cover maps, which are provided by the Ministry of Environment, overlapped with the scene. After that, training data for each determined class are collected. In order to analyze the effect of SWIR bands, classifications with and without SWIR bands are carried out and the results are then compared. In this regard, a SVM (Support Vector Machine) is utilized as their classifier. As a result of the accuracy assessments performed by test data that are independently extracted from training data, it was confirmed that classification performance was improved when the SWIR bands are included as input features for SVM-based classification.

Detection of Surface Changes by the 6th North Korea Nuclear Test Using High-resolution Satellite Imagery (고해상도 위성영상을 활용한 북한 6차 핵실험 이후 지표변화 관측)

  • Lee, Won-Jin;Sun, Jongsun;Jung, Hyung-Sup;Park, Sun-Cheon;Lee, Duk Kee;Oh, Kwan-Young
    • Korean Journal of Remote Sensing
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    • v.34 no.6_4
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    • pp.1479-1488
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    • 2018
  • On September 3rd 2017, strong artificial seismic signals from North Korea were detected in KMA (Korea Meteorological Administration) seismic network. The location of the epicenter was estimated to be Punggye-ri nuclear test site and it was the most powerful to date. The event was not studied well due to accessibility and geodetic measurements. Therefore, we used remote sensing data to analyze surface changes around Mt. Mantap area. First of all, we tried to detect surface deformation using InSAR method with Advanced Land Observation Satellite-2 (ALOS-2). Even though ALOS-2 data used L-band long wavelength, it was not working well for this particular case because of decorrelation on interferogram. The main reason would be large deformation near the Mt. Mantap area. To overcome this limitation of decorrelation, we applied offset tracking method to measure deformation. However, this method is affected by window kernel size. So we applied various window sizes from 32 to 224 in 16 steps. We could retrieve 2D surface deformation of about 3 m in maximum in the west side of Mt. Mantap. Second, we used Pleiadas-A/B high resolution satellite optical images which were acquired before and after the 6th nuclear test. We detected widespread surface damage around the top of Mt. Mantap such as landslide and suspected collapse area. This phenomenon may be caused by a very strong underground nuclear explosion test. High-resolution satellite images could be used to analyze non-accessible area.

Fine Co-registration Performance of KOMPSAT-3·3A Imagery According to Convergence Angles (수렴각에 따른 KOMPSAT-3·3A호 영상 간 정밀 상호좌표등록 결과 분석)

  • Han, Youkyung;Kim, Taeheon;Kim, Yeji;Lee, Jeongho
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.37 no.6
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    • pp.491-498
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    • 2019
  • This study analyzed how the accuracy of co-registration varies depending on the convergence angles between two KOMPSAT-3·3A images. Most very-high-resolution satellite images provide initial coordinate information through metadata. Since the search area for performing image co-registration can be reduced by using the initial coordinate information, in this study, the mutual information method showing high matching reliability in the small search area is used. Initial coarse co-registration was performed by using multi-spectral images with relatively low resolution, and precise fine co-registration was conducted centering on the region of interest of the panchromatic image for more accurate co-registration performance. The experiment was conducted by 120 combination of 16 KOMPSAT-3·3A 1G images taken in Daejeon area. Experimental results show that a correlation coefficient between the convergence angles and fine co-registration errors was 0.59. In particular, we have shown the larger the convergence angle, the lower the accuracy of co-registration performance.

Study on the Retreatment Techniques for NOAA Sea Surface Temperature Imagery (NOAA 수온영상 재처리 기법에 관한 연구)

  • Kim, Sang-Woo;Kang, Yong-Q.;Ahn, Ji-Sook
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.17 no.4
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    • pp.331-337
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    • 2011
  • We described for the production of cloud-free satellite sea surface temperature(SST) data around Northeast Asian using NOAA AVHRR(Advanced Very High Resolution Radiometer) SST data during 1990-2005. As a result of Markov model, it was found that the value of Markov coefficient in the strong current region such as Kuroshio region showed smaller than that in the weak current. The variations of average SST and regional difference of seasonal day-to-day SST in spring and fall were larger than those in summer and winter. In particular, the distribution of the regional difference appeared large in the vicinity of continental in spring and fall. The difference of seasonal day-to-day SST was also small in Kuroshio region and southern part of East Sea due to the heat advection by warm currents.

Analysis of Urban Heat Island Intensity Among Administrative Districts Using GIS and MODIS Imagery (GIS 및 MODIS 영상을 활용한 행정구역별 도시열섬강도 분석)

  • SEO, Kyeong-Ho;PARK, Kyung-Hun
    • Journal of the Korean Association of Geographic Information Studies
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    • v.20 no.2
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    • pp.1-16
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    • 2017
  • This study was conducted to analyze the urban heat island(UHI) intensity of South Korea by using Moderate Resolution Imaging Spectroradiometer(MODIS) satellite imagery. For this purpose, the metropolitan area was spatially divided according to land cover classification into urban and non-urban land. From the analysis of land surface temperature(LST) in South Korea in the summer of 2009 which was calculated from MODIS satellite imagery it was determined that the highest temperature recorded nationwide was $36.0^{\circ}C$, lowest $16.2^{\circ}C$, and that the mean was $24.3^{\circ}C$, with a standard deviation of $2.4^{\circ}C$. In order to analyze UHI by cities and counties, UHI intensity was defined as the difference in average temperature between urban and non-urban land, and was calculated through RST1 and RST2. The RST1 calculation showed scattered distribution in areas of high UHI intensity, whereas the RST2 calculation showed that areas of high UHI intensity were concentrated around major cities. In order to find an effective method for analyzing UHI by cities and counties, analysis was conducted of the correlation between the urbanization ratio, number of tropical heat nights, and number of heat-wave days. Although UHI intensity derived through RST1 showed barely any correlation, that derived through RST2 showed significant correlation. The RST2 method is deemed as a more suitable analytical method for measuring the UHI of urban land in cities and counties across the country. In cities and counties with an urbanization ratio of < 20%, the rate of increase for UHI intensity in proportion to increases in urbanization ratio, was very high; whereas this rate gradually declined when the urbanization ratio was > 20%. With an increase of $1^{\circ}C$ in RST2 UHI intensity, the number of tropical heat nights and heat wave days was predicted to increase by approximately five and 0.5, respectively. These results can be used for reference when predicting the effects of increased urbanization on UHI intensity.

The Classification Accuracy Improvement of Satellite Imagery Using Wavelet Based Texture Fusion Image (웨이브릿 기반 텍스처 융합 영상을 이용한 위성영상 자료의 분류 정확도 향상 연구)

  • Hwang, Hwa-Jeong;Lee, Ki-Won;Kwon, Byung-Doo;Yoo, Hee-Young
    • Korean Journal of Remote Sensing
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    • v.23 no.2
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    • pp.103-111
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    • 2007
  • The spectral information based image analysis, visual interpretation and automatic classification have been widely carried out so far for remote sensing data processing. Yet recently, many researchers have tried to extract the spatial information which cannot be expressed directly in the image itself. Using the texture and wavelet scheme, we made a wavelet-based texture fusion image which includes the advantages of each scheme. Moreover, using these schemes, we carried out image classification for the urban spatial analysis and the geological structure analysis around the caldera area. These two case studies showed that image classification accuracy of texture image and wavelet-based texture fusion image is better than that of using only raw image. In case of the urban area using high resolution image, as both texture and wavelet based texture fusion image are added to the original image, the classification accuracy is the highest. Because detailed spatial information is applied to the urban area where detail pixel variation is very significant. In case of the geological structure analysis using middle and low resolution image, the images added by only texture image showed the highest classification accuracy. It is interpreted to be necessary to simplify the information such as elevation variation, thermal distribution, on the occasion of analyzing the relatively larger geological structure like a caldera. Therefore, in the image analysis using spatial information, each spatial information analysis method should be carefully selected by considering the characteristics of the satellite images and the purpose of study.

A Study on the Utilization of SAR Microsatellite Constellation for Ship Detection (선박탐지를 위한 초소형 SAR 군집위성 활용방안 연구)

  • Kim, Yunjee;Kang, Ki-mook
    • Korean Journal of Remote Sensing
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    • v.37 no.3
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    • pp.627-636
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    • 2021
  • Although many studies on ship detection using synthetic aperture radar (SAR) satellite images are being conducted around the world, there are still very few employing SAR microsatellites, as most of the microsatellites are optical satellites. Recently, the ICEYE and Capella Space have embarked on the development of microsatellites with SAR sensor, and similar projects are being initiated globally in line with the flow of the new space era [e.g., for the ICEYE: 18 satellites (~2021); Capella Space: 36 satellites (~2023); and the Coast Guard SAR: 32 satellites in the early development stage]. In preparation for these new systems, it is important to review the SAR microsatellite system and the recent advances in this technology. Accordingly, in this paper, the current status and characteristics of optical and SAR microsatellite constellation operation are described, and studies using them are investigated. In addition, based on the status and characteristics of the representative SAR microsatellites, specifically the ICEYE and Capella systems, methods for using SAR microsatellite data for ship detection applications are described. Our results confirm that the SAR microsatellites operate as a constellation and have the advantages of short revisit cycles and quick provision of high-resolution images. With this technology, we expect SAR microsatellites to contribute greatly to the monitoring a wide-area target vessel, in which the spatiotemporal resolution of the imagery is especially important.

Multiresolution 4- 8 Tile Hierarchy Construction for Realtime Visualization of Planetary Scale Geological Information (행성 규모 지리 정보의 실시간 시각화를 위한 다계층 4-8 타일 구조의 구축)

  • Jin, Jong-Wook;Wohn, Kwang-Yun
    • Journal of the Korean Association of Geographic Information Studies
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    • v.9 no.4
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    • pp.12-21
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    • 2006
  • Recently, Very large and high resolution geological data from aerial or satellite imagery are available. Many researches and applications require to do realtime visualization of interest geological area or entire planet. Important operation of wide-spreaded terrain realtime visualization technique is the appropriate model resolution selection from pre-processed multi-resolution model hierarchy depend upon participant's view. For embodying such realtime rendering system with large geometric data, Preprocessing multi-resolution hierarchy from large scale geological information of interest area is required. In this research, recent Cubic multiresolution 4-8 tile hierarchy is selected for global planetary applications. Based upon the tile hierarchy, It constructs the selective terminal level tile mesh for original geological information area and starts to sample individual generated tiles for terminal level tiles. It completes the hierarchy by constructing intermediate tiles with low pass filtering in bottom-up direction. This research embodies series of efficient cubic 4-8 tile hierarchy construction mechanism with out-of-core storage. The planetary scale Mars' geographical altitude data and image data were selected for the experiment.

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Quantitative Evaluations of Deep Learning Models for Rapid Building Damage Detection in Disaster Areas (재난지역에서의 신속한 건물 피해 정도 감지를 위한 딥러닝 모델의 정량 평가)

  • Ser, Junho;Yang, Byungyun
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.40 no.5
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    • pp.381-391
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    • 2022
  • This paper is intended to find one of the prevailing deep learning models that are a type of AI (Artificial Intelligence) that helps rapidly detect damaged buildings where disasters occur. The models selected are SSD-512, RetinaNet, and YOLOv3 which are widely used in object detection in recent years. These models are based on one-stage detector networks that are suitable for rapid object detection. These are often used for object detection due to their advantages in structure and high speed but not for damaged building detection in disaster management. In this study, we first trained each of the algorithms on xBD dataset that provides the post-disaster imagery with damage classification labels. Next, the three models are quantitatively evaluated with the mAP(mean Average Precision) and the FPS (Frames Per Second). The mAP of YOLOv3 is recorded at 34.39%, and the FPS reached 46. The mAP of RetinaNet recorded 36.06%, which is 1.67% higher than YOLOv3, but the FPS is one-third of YOLOv3. SSD-512 received significantly lower values than the results of YOLOv3 on two quantitative indicators. In a disaster situation, a rapid and precise investigation of damaged buildings is essential for effective disaster response. Accordingly, it is expected that the results obtained through this study can be effectively used for the rapid response in disaster management.