• Title/Summary/Keyword: high resolution satellite image

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Analysis of Satellite Images to Estimate Forest Biomass (산림 바이오매스를 산정하기 위한 위성영상의 분석)

  • Lee, Hyun Jik;Ru, Ji Ho;Yu, Young Geol
    • Journal of Korean Society for Geospatial Information Science
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    • v.21 no.3
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    • pp.63-71
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    • 2013
  • This study calculated vegetation indexes such as SR, NDVI, SAVI, and LAI to figure out correlations regarding vegetation by using high resolution KOMPSAT-2 images and LANDSAT images based on the forest biomass distribution map that utilized field survey data, satellite images and LiDAR data and then analyzed correlations between their values and forest biomass. The analysis results reveal that the vegetation indexes of high resolution KOMPSAT-2 images had higher correlations than those of LANDSAT images and that NDVI recorded high correlations among the vegetation indexes. In addition, the study analyzed the characteristics of hyperspectral images by using the COMIS of STSAT-3 and Hyperion images of a similar sensor, EO-1, and further the usability of biomass estimation in hyperspectral images by comparing vegetation index, which had relatively high correlations with biomass, with the vegetation indexes of LANDSAT with the same GSD conditions.

Application of LiDAR Data & High-Resolution Satellite Image for Calculate Forest Biomass (산림바이오매스 산정을 위한 LiDAR 자료와 고해상도 위성영상 활용)

  • Lee, Hyun-Jik;Ru, Ji-Ho
    • Journal of Korean Society for Geospatial Information Science
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    • v.20 no.1
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    • pp.53-63
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    • 2012
  • As a result of the economical loss caused by unusual climate changes resulting from emission of excessive green house gases such as carbon dioxide which is expected to account for 5~20% of the world GDP by 2100, researching technologies regarding the reduction of carbon dioxide emission is being favored worldwide as a part of the high value-added industry. As one of the Annex II countries of Kyoto Protocol of 1997 that should keep the average $CO_2$ emission rate of 5% by 2013, South Korea is also dedicated to the researches and industries of $CO_2$ emission reduction. In this study, Application of LiDAR data & KOMPSAT-2 satellite image for calculated forest Biomass. Raw LiDAR data's tree numbers and tree-high with field survey data resulted in 90% similarity of objects and an average of 0.3m difference in tree-high. Calculating the forest biomass through forest type information categorized as KOMPSAT-2 image and LiDAR data's tree-high data of tree enabled the estimation of $CO_2$ absorption and forest biomass of forest type, The similarity between the field survey average of 90% or higher were analyzed.

Report of Wave Glider Detecting by KOMPSAT-5 Spotlight Mode SAR Image (KOMPSAT-5 Spotlight Mode SAR 영상을 이용한 웨이브글라이더 탐지 사례 보고)

  • Lee, Yoon-Kyung;Kim, Sang-Wan;Ryu, Joo-Hyung
    • Korean Journal of Remote Sensing
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    • v.34 no.2_2
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    • pp.431-437
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    • 2018
  • We analyzed the feasibility of detecting wave gliders moving on the sea surface using SAR images. For the experiment, a model was constructed and placed on the sea using a towing ship before and after the satellite observation time. In the acquisition of KOMPSAT-5 image, high resolution SAR data of spotlight mode was collected considering the small size of wave glider. As a result of the backscattering intensity analysis around the towing ship along with wave glider, several scattering points away from the ship were observed, which are not strong but clearly distinguished from the surrounding clutter values. Considering the distance from the center of the ship, it seems to be a signal by the wave glider. On the other hand, it is confirmed that the wave glider can be detected even at the very low false alarm rate ($10^{-6}$) of the target detection using CFAR. Although the scatter signal by the wave glider could be distinguished from the surrounding ocean clutter in the high resolution SAR image, further research is needed to determine if actual wave gliders are detected in various marine environments.

Calculation Method of Oil Slick Area on Sea Surface Using High-resolution Satellite Imagery: M/V Symphony Oil Spill Accident (고해상도 광학위성을 이용한 해상 유출유 면적 산출: 심포니호 기름유출 사고 사례)

  • Kim, Tae-Ho;Shin, Hye-Kyeong;Jang, So Yeong;Ryu, Joung-Mi;Kim, Pyeongjoong;Yang, Chan-Su
    • Korean Journal of Remote Sensing
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    • v.37 no.6_1
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    • pp.1773-1784
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    • 2021
  • In order to minimize damage to oil spill accidents in the ocean, it is essential to collect a spilled area as soon as possible. Thus satellite-based remote sensing is a powerful source to detect oil spills in the ocean. With the recent rapid increase in the number of available satellites, it has become possible to generate a status report of marine oil spills soon after the accident. In this study, the oil spill area was calculated using various satellite images for the Symphony oil spill accident that occurred off the coast of Qingdao Port, China, on April 27, 2021. In particular, improving the accuracy of oil spill area determination was applied using high-resolution commercial satellite images with a spatial resolution of 2m. Sentinel-1, Sentinel-2, LANDSAT-8, GEO-KOMPSAT-2B (GOCI-II) and Skysat satellite images were collected from April 27 to May 13, but five images were available considering the weather conditions. The spilled oil had spread northeastward, bound for coastal region of China. This trend was confirmed in the Skysat image and also similar to the movement prediction of oil particles from the accident location. From this result, the look-alike patch observed in the north area from the Sentinel-1A (2021.05.01) image was discriminated as a false alarm. Through the survey period, the spilled oil area tends to increase linearly after the accident. This study showed that high-resolution optical satellites can be used to calculate more accurately the distribution area of spilled oil and contribute to establishing efficient response strategies for oil spill accidents.

Reconstruction of 3D Building Model from Satellite Imagery Based on the Grouping of 3D Line Segments Using Centroid Neural Network (중심신경망을 이용한 3차원 선소의 군집화에 의한 위성영상의 3차원 건물모델 재구성)

  • Woo, Dong-Min;Park, Dong-Chul;Ho, Hai-Nguyen;Kim, Tae-Hyun
    • Korean Journal of Remote Sensing
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    • v.27 no.2
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    • pp.121-130
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    • 2011
  • This paper highlights the reconstruction of the rectilinear type of 3D rooftop model from satellite image data using centroid neural network. The main idea of the proposed 3D reconstruction method is based on the grouping of 3D line segments. 3D lines are extracted by 2D lines and DEM (Digital Elevation Map) data evaluated from a pair of stereo images. Our grouping process consists of two steps. We carry out the first grouping process to group fragmented or duplicated 3D lines into the principal 3D lines, which can be used to construct the rooftop model, and construct the groups of lines that are parallel each other in the second step. From the grouping result, 3D rooftop models are reconstructed by the final clustering process. High-resolution IKONOS images are utilized for the experiments. The experimental result's indicate that the reconstructed building models almost reflect the actual position and shape of buildings in a precise manner, and that the proposed approach can be efficiently applied to building reconstruction problem from high-resolution satellite images of an urban area.

Object-Based Road Extraction from VHR Satellite Image Using Improved Ant Colony Optimization (개선된 개미 군집 최적화를 이용한 고해상도 위성영상에서의 객체 기반 도로 추출)

  • Kim, Han Sae;Choi, Kang Hyeok;Kim, Yong Il;Kim, Duk-Jin;Jeong, Jae Joon
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.37 no.3
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    • pp.109-118
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    • 2019
  • Road information is one of the most significant geospatial data for applications such as transportation, city planning, map generation, LBS (Location-Based Service), and GIS (Geographic Information System) database updates. Robust technologies to acquire and update accurate road information can contribute significantly to geospatial industries. In this study, we analyze the limitations of ACO (Ant Colony Optimization) road extraction, which is a recently introduced object-based road extraction method using high-resolution satellite images. Object-based ACO road extraction can efficiently extract road areas using both spectral and morphological information. This method, however, is highly dependent on object descriptor information and requires manual designations of descriptors. Moreover, reasonable iteration closing point needs to be specified. In this study, we perform improved ACO road extraction on VHR (Very High Resolution) optical satellite image by proposing an optimization stopping criteria and descriptors that complements the limitations of the existing method. The proposed method revealed 52.51% completeness, 6.12% correctness, and a 51.53% quality improvement over the existing algorithm.

The Improvement of RFM RPC Using Ground Control Points and 3D Cube

  • Cho, Woo-Sug;Kim, Joo-Hyun
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.1143-1145
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    • 2003
  • Some of satellites such as IKONOS don't provide the orbital elements so that we can’ utilize the physical sensor model. Therefore, Rational Function Model(RFM) which is one of mathematical models could be a feasible solution. In order to improve 3D geopositioning accuracy of IKONOS stereo imagery, Rational Polynomial Coefficients(RPCs) of the RFM need to be updated with Ground Control Points(GCPs). In this paper, a method to improve RPCs of RFM using GCPs and 3D cube is proposed. Firstly, the image coordinates of GCPs are observed. And then, using offset values and scale values of RPC provided, the image coordinates and ground coordinates of 3D cube are initially determined and updated RPCs are computed by the iterative least square method. The proposed method was implemented and analyzed in several cases: different numbers of 3D cube layers and GCPs. The experimental results showed that the proposed method improved the accuracy of RPCs in great amount.

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A Study on 3D Reconstruction of Urban Area

  • Park Y. M.;Kwon K. R.;Lee K. W.
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.470-473
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    • 2005
  • This paper proposes a reconstruction method for the shape and color information of 3-dimensional buildings. The proposed method is range scanning by laser range finder and image coordinates' color information mapping to laser coordinate by a fixed CCD camera on laser range finder. And we make a 'Far-View' using high-resolution satellite image. The 'Far-View' is created that the height of building using DEM after contours of building extraction. The user select a region of 'Far View' and then, appear detailed 3D-reconstruction of building The outcomes apply to city plan, 3D-environment game and movie background etc.

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A Study on Fusion and Visualization using Multibeam Sonar Data with Various Spatial Data Sets for Marine GIS

  • Kong, Seong-Kyu
    • Journal of Advanced Marine Engineering and Technology
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    • v.34 no.3
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    • pp.407-412
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    • 2010
  • According to the remarkable advances in sonar technology, positioning capabilities and computer processing power we can accurately image and explore the seafloor in hydrography. Especially, Multibeam Echo Sounder can provide nearly perfect coverage of the seafloor with high resolution. Since the mid-1990's, Multibeam Echo Sounders have been used for hydrographic surveying in Korea. In this study, new marine data set as an effective decision-making tool in various fields was proposed by visualizing and combining with Multibeam sonar data and marine spatial data sets such as satellite image and digital nautical chart. The proposed method was tested around the port of PyeongTaek-DangJin in the west coast of Korea. The Visualization and fusion methods are described with various marine data sets with processing. We demonstrated that new data set in marine GIS is useful in safe navigation and port management as an efficient decision-making tool.

RADIOMETRIC RESTORATION OF SHADOW AREAS FROM KOMPSAT-2 IMAGERY

  • Choi, Jae-Wan;Kim, Hye-Jin;Han, You-Kyung;Kim, Yong-II
    • Proceedings of the KSRS Conference
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    • 2008.10a
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    • pp.371-374
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    • 2008
  • In very high-spatial resolution remote sensing imagery, it is difficult to extract the feature information of various objects because of occlusion and shadows. Moreover, various and feeble information within shadows can be of use in GIS-based applications and remote sensing analysis. In this paper, we developed a radiometric restoration method for shadow areas using KOMPSAT-2 satellite image. After detecting the shadow, non-shadow pixels nearby are extracted using a morphological filter. An iterative linear regression method is applied to calculate the relationship between shadow and non-shadow pixels. The shadows are restored by the parameters of the linear regression algorithm. Tests show that recovery of shadowed areas by our method leads to improved image quality.

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