• Title/Summary/Keyword: Satellite map

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Analysis of the Radiation Patterns of Satellite SAR System with Active-Transponder (능동전파반사기를 이용한 위성 SAR 시스템 방사 패턴 분석)

  • Hwang, Ji-Hwan;Kweon, Soon-Koo;Oh, Yisok
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.23 no.10
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    • pp.1204-1211
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    • 2012
  • Measurement and analysis results of the extracted radiation-patterns from the field-experiments which were conducted to acquire the generic technology for calibration and validation of the satellite SAR system(Synthetic Aperture Radar) are presented in this study. Prototype of active transponder is adjustable within maximum 63.1 dBsm of RCS (Radar Cross Section) and includes the receiving-function with external receiver. To increase an accuracy of these field experiments, we repetitively measured satellite SAR systems of the same operating mode(i.e., COSMO-SkyMed No. 2 & 3, hh-pol., strip-map himage mode, 3 m resolution). Then, the reliability of experimental results was cross-checked through analysis of the RCS of active transponder on SAR image. The property of azimuth radiation patterns of satellite SAR system extracted from them has $0.352^{\circ}$ of HPBW(half-power beamwidth), $0.691^{\circ}$ of FNBW(first-null beamwidth), and 11.17 dB of PSLR(peak to side lobe ratio), respectively.

A Generation of Digital Elevation Model for GSIS using SPOT Satellite Imagery (GSIS의 자료기반 구축을 위한 SPOT 위성영상으로부터의 수치표고모형 생성)

  • Yeu, Bock-Mo;Park, Hong-Gi;Jeong, Soo;Kim, Won-Dae
    • Journal of Korean Society for Geospatial Information Science
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    • v.1 no.1 s.1
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    • pp.141-152
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    • 1993
  • This study aims to generate digital elevation model from digital satellite imagery. Digital elevation model is being increasingly used for geo-spatial information system database development and for digital map production. Image matching technique was applied to acquire conjugate image coordinates and the algorithm for digital elevation model generation is presented in this study The exterior orientation parameters of the satellite imagery is determined by bundle adjustment and standard correlation was applied for image matching conjugate of image points. The window as well as the searching area have to be defined in image matching. Different sizes of searching area were tested to study the appropriate size of the searching area. Various coordinate transformation methods were applied to improve the computation speed as well as the geometric accuracy. The results were then statistically analysed after which the searching area is determined with the safety factor. To evaluate the accuracy of digital elevation model, 3-D coordinates were extracted from 1/5000 scale topographic map and this was compared to the digital elevation model generated from satellite imagery. The algorithm for generation of digital elevation model generated from satellite imagery is presented in this study which will prove effective in the database development of geo-spatial information system and in digital elevation modelling of large areas.

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A Study on Pre-evaluation of Tree Species Classification Possibility of CAS500-4 Using RapidEye Satellite Imageries (농림위성 활용 수종분류 가능성 평가를 위한 래피드아이 영상 기반 시험 분석)

  • Kwon, Soo-Kyung;Kim, Kyoung-Min;Lim, Joongbin
    • Korean Journal of Remote Sensing
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    • v.37 no.2
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    • pp.291-304
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    • 2021
  • Updating a forest type map is essential for sustainable forest resource management and monitoring to cope with climate change and various environmental problems. According to the necessity of efficient and wide-area forestry remote sensing, CAS500-4 (Compact Advanced Satellite 500-4; The agriculture and forestry satellite) project has been confirmed and scheduled for launch in 2023. Before launching and utilizing CAS500-4, this study aimed to pre-evaluation the possibility of satellite-based tree species classification using RapidEye, which has similar specifications to the CAS500-4. In this study, the study area was the Chuncheon forest management complex, Gangwon-do. The spectral information was extracted from the growing season image. And the GLCM texture information was derived from the growing and non-growing seasons NIR bands. Both information were used to classification with random forest machine learning method. In this study, tree species were classified into nine classes to the coniferous tree (Korean red pine, Korean pine, Japanese larch), broad-leaved trees (Mongolian oak, Oriental cork oak, East Asian white birch, Korean Castanea, and other broad-leaved trees), and mixed forest. Finally, the classification accuracy was calculated by comparing the forest type map and classification results. As a result, the accuracy was 39.41% when only spectral information was used and 69.29% when both spectral information and texture information was used. For future study, the applicability of the CAS500-4 will be improved by substituting additional variables that more effectively reflect vegetation's ecological characteristics.

A Study on Establishing a Market Entry Strategy for the Satellite Industry Using Future Signal Detection Techniques (미래신호 탐지 기법을 활용한 위성산업 시장의 진입 전략 수립 연구)

  • Sehyoung Kim;Jaehyeong Park;Hansol Lee;Juyoung Kang
    • Journal of Intelligence and Information Systems
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    • v.29 no.3
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    • pp.249-265
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    • 2023
  • Recently, the satellite industry has been paying attention to the private-led 'New Space' paradigm, which is a departure from the traditional government-led industry. The space industry, which is considered to be the next food industry, is still receiving relatively little attention in Korea compared to the global market. Therefore, the purpose of this study is to explore future signals that can help determine the market entry strategies of private companies in the domestic satellite industry. To this end, this study utilizes the theoretical background of future signal theory and the Keyword Portfolio Map method to analyze keyword potential in patent document data based on keyword growth rate and keyword occurrence frequency. In addition, news data was collected to categorize future signals into first symptom and early information, respectively. This is utilized as an interpretive indicator of how the keywords reveal their actual potential outside of patent documents. This study describes the process of data collection and analysis to explore future signals and traces the evolution of each keyword in the collected documents from a weak signal to a strong signal by specifically visualizing how it can be used through the visualization of keyword maps. The process of this research can contribute to the methodological contribution and expansion of the scope of existing research on future signals, and the results can contribute to the establishment of new industry planning and research directions in the satellite industry.

Automatic Generation of Land Cover Map Using Residual U-Net (Residual U-Net을 이용한 토지피복지도 자동 제작 연구)

  • Yoo, Su Hong;Lee, Ji Sang;Bae, Jun Su;Sohn, Hong Gyoo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.40 no.5
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    • pp.535-546
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    • 2020
  • Land cover maps are derived from satellite and aerial images by the Ministry of Environment for the entire Korea since 1998. Even with their wide application in many sectors, their usage in research community is limited. The main reason for this is the map compilation cycle varies too much over the different regions. The situation requires us a new and quicker methodology for generating land cover maps. This study was conducted to automatically generate land cover map using aerial ortho-images and Landsat 8 satellite images. The input aerial and Landsat 8 image data were trained by Residual U-Net, one of the deep learning-based segmentation techniques. Study was carried out by dividing three groups. First and second group include part of level-II (medium) categories and third uses group level-III (large) classification category defined in land cover map. In the first group, the results using all 7 classes showed 86.6 % of classification accuracy The other two groups, which include level-II class, showed 71 % of classification accuracy. Based on the results of the study, the deep learning-based research for generating automatic level-III classification was presented.

Generation of the Ortho-Rectified Photo Map and Analysis of the Three-Dimensional Image Using the PKNU 2 Imagery (PKNU2호 영상을 이용한 정사영상 지도 제작 및 3차원 입체 분석)

  • Lee, Chang Hun;Choi, Chul Uong
    • Journal of the Korean Association of Geographic Information Studies
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    • v.7 no.4
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    • pp.77-87
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    • 2004
  • It is important for hydrographers to extract the accurate cross section of a river for the hydrographical analysis of the topography. Aerial photographs were used to extract the cross section of a river for the advantages of the accuracy and economical efficiency in this study, while the direct measurement has been used in existing studies. An ortho-rectified photo map using imageries taken by the PKNU 2 (High-resolution, multi-spectral, aerial photographic system developed by our laboratory) was generated using the surveyed data and a digital map. The cross section of a river that was obtained from the ortho-rectified by the surveyed Kinematic data of GPS was compared with the result using ImageStation stereo-plotter of corp. Z/I Imaging. As a result of this study, the RMSE in the ortho-rect process using the surveyed GPS data was lowered as from 5.5788 pixels (about 2m) to 2.84 (about 1m) in comparison with it in the process using a digital map. The surveyed kinematic GPS in extraction of the cross section of a river was excellent as 6.6cm of the planimetric and precision in the confidence level of 95%. The correlation coefficient between the result from the using stereo-plotter and the extraction of cross section of a river using aerial photos was 0.8 hydrographical acquisition of it using PKNU 2 imagery will be possible.

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A Case Study of GIS-Based Site Classification in the Gyeongsang Province Constrained by Geologic and Topographic Information (GIS기반의 지질·지형 자료를 활용한 경상도지역의 지반분류 사례)

  • Kang, Su-Young;Kim, Kwang-Hee
    • Journal of the Korean Association of Geographic Information Studies
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    • v.12 no.4
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    • pp.136-145
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    • 2009
  • Site characteristic is an important input parameter in the geologic hazard assessments including, but not limited to, earthquakes, liquefaction and landslides. Although it is a routine to use data collected by boreholes or seismic prospecting for site classifications, we used indirect methods using the geologic and the topographic maps. A site classification map in the Gyeongsang Province has been produced by GIS tools based on geologic age, rock types, and elevations from the geologic map and the topographic map of Korea. Site B (rock site) is dominant in the study area, although softer soils are observed along rivers and in reclaimed lands. We have found that 73% of the site classification results in the study are in concordance with those obtained from borehole data. Observed discrepancies are attributed to errors in the geologic and the topographic maps. For some sites, the origin of the differences is not clear, which requires a further field study or a drilling. Site classification from this study provides essential information for reliable hazard assessments of earthquakes, floods, landslides and liquefaction. Results obtained in the study also play a crucial role in land use planning for developing areas.

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An Experiment for Surface Soil Moisture Mapping Using Sentinel-1 and Sentinel-2 Image on Google Earth Engine (Google Earth Engine 제공 Sentinel-1과 Sentinel-2 영상을 이용한 지표 토양수분도 제작 실험)

  • Jihyun Lee ;Kwangseob Kim;Kiwon Lee
    • Korean Journal of Remote Sensing
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    • v.39 no.5_1
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    • pp.599-608
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    • 2023
  • The increasing interest in soil moisture data using satellite data for applications of hydrology, meteorology, and agriculture has led to the development of methods for generating soil moisture maps of variable resolution. This study demonstrated the capability of generating soil moisture maps using Sentinel-1 and Sentinel-2 data provided by Google Earth Engine (GEE). The soil moisture map was derived using synthetic aperture radar (SAR) image and optical image. SAR data provided by the Sentinel-1 analysis ready data in GEE was applied with normalized difference vegetation index (NDVI) based on Sentinel-2 and Environmental Systems Research Institute (ESRI)-based Land Cover map. This study produced a soil moisture map in the research area of Victoria, Australia and compared it with field measurements obtained from a previous study. As for the validation of the applied method's result accuracy, the comparative experimental results showed a meaningful range of consistency as 4-10%p between the values obtained using the algorithm applied in this study and the field-based ones, and they also showed very high consistency with satellite-based soil moisture data as 0.5-2%p. Therefore, public open data provided by GEE and the algorithm applied in this study can be used for high-resolution soil moisture mapping to represent regional land surface characteristics.

Extraction and Revision of Building Information from Single High Resolution Image and Digital Map (단일 고해상도 위성영상과 수치지도로부터 건물 정보 추출 및 갱신)

  • Byun, Young-Gi;Kim, Hye-Jin;Choi, Jae-Wan;Han, You-Kyung;Kim, Yong-Il
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.26 no.2
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    • pp.149-156
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    • 2008
  • In this paper, we propose a method aiming at updating the building information of the digital maps using single high resolution satellite image and digital map. Firstly we produced a digital orthoimage through the automatic co-registration of QuickBird image and 1:1,000 digital map. Secondly we extracted building height information through the template matching of digital map's building vector data and the image's edges obtained by Canny operator. Finally we refined the shape of some buildings by using the result from template matching as the seed polygon of the greedy snake algorithm. In order to evaluate the proposed method's effectiveness, we estimated accuracy of the extracted building information using LiDAR DSM and 1:1,000 digital map. The evaluation results showed the proposed method has a good potential for extraction and revision of building information.

Method for Calculating the Pollution Load Amount of Agricultural Non-Point Sources Using Land Cover Map (토지피복지도를 활용한 농업비점오염원 오염부하량 산정에 관한 연구)

  • Yu, Jieun;Kim, Yoonji;Sung, Hyun-Chan;Lee, Kyung-il;Choi, Ji-yong;Jeon, Seung-woo
    • Journal of Environmental Science International
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    • v.29 no.12
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    • pp.1249-1260
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    • 2020
  • Non-point source pollutants have characteristics the render them difficult to manage owing to the uncertainty of flow paths. As agricultural non-point sources account for more than 57% of non-point source pollutants, the necessity for management is increasing. This study examines the possibility of utilizing land cover maps to suggest a more appropriate method of setting management priority for agricultural non-point sources in the Daecheong Lake area and draws implications by comparing the results derived using the cadastral map, as mentioned in the TMDL Basic Policy. To define the prioritized areas for management, the pollution load was calculated for each subbasin using the formula from the TMDL technical guidelines. As a result, the difference in the average pollution load between the land cover map and cadastral map ranged from 11.6% to 21% among the subbasins. In almost all subbasins, there were differences in the ranking of management priorities depending on the land information that was used. In addition, it was found that it was reasonable to use the level 3 land cover map to calculate the load generated by the land system for examining the implementation goals and methods of each data and comparing them with satellite images.