• Title/Summary/Keyword: artificial satellite image

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Development of Vegetation Structure Measurement System using Multi-angle Stereo pair Images

  • DEMIZU Masaki;KAJIWARA Koji;HONDA Yoshiaki
    • Proceedings of the KSRS Conference
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    • 2004.10a
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    • pp.170-173
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    • 2004
  • When the data from the artificial satellite is analyzed, recent years it is perceived to vegetation index using BRF(Bi-directional Reflectance Factor) of the observation target. To make the BRF models, it is important to measure the 3D structure of the observation target actually. In this study, it is proposed to the observation technique by using multi-angle stereo pair image, and shown the observation result in grassland area. Also, our team has been operating the radio controlled helicopter which can fly over the tall forest canopy and it can be equipped the measurement system.

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Monitoring of Lake area Change and Drought using Landsat Images and the Artificial Neural Network Method in Lake Soyang, Chuncheon, Korea (Landsat 영상 및 인공 신경망 기법을 활용한 춘천 소양호 면적 및 가뭄 모니터링)

  • Eom, Jinah;Park, Sungjae;Ko, Bokyun;Lee, Chang-Wook
    • Journal of the Korean earth science society
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    • v.41 no.2
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    • pp.129-136
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    • 2020
  • Drought is an environmental disaster typically defined as an unusual deficiency of water supply over an extended period. Satellite remote sensing provides an alternative approach to monitoring drought over large areas. In this study, we monitored drought patterns over about 30 years (1985-2015), using satellite imagery of Lake Soyang, Gangwondo, South Korea. Landsat images were classified using ISODATA, maximum likelihood analysis, and an artificial neural network to derive the lake area. In addition, the relationship between areas of Lake Soyang and the Standardized Precipitation Index (SPI) was analyzed. The results showed that the artificial neural network was a better method for determining the area of the lake. Based on the relationship between the SPI value and changes in area, the R2 value was 0.52. This means that the area of the lake varied depending on SPI value. This study was able to detect and monitor drought conditions in the Lake Soyang area. The results of this study are used in the development of a regional drought monitoring program.

Neural Network Based Land Cover Classification Technique of Satellite Image for Pollutant Load Estimation (신경망 기반의 오염부하량 산정을 위한 위성영상 토지피복 분류기법)

  • Park, Sang-Young;Ha, Sung-Ryong
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2001.12a
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    • pp.1-4
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    • 2001
  • The classification performance of Artificial Neural Network (ANN) and RBF-NN was compared for Landsat TM image. The RBF-NN was validated for three unique landuse types (e.g. Mixed landuse area, Cultivated area, Urban area), different input band combinations and classification class. The bootstrap resampling technique was employed to estimate the confidence intervals and distribution for unit load, The pollutant generation was varied significantly according to the classification accuracy and percentile unit load applied. Especially in urban area, where mixed landuse is dominant, the difference of estimated pollutant load is largely varied.

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A STUDY ON EXTRACTING THE SURFACE TEMPERATURE USING THERMAL INFRARED OF ASTER IMAGES IN URBAN AREA

  • Jo Myung-Hee;Kim Hyung-Sub;Kim Sung-Jae;Yu Seong-Ok
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.717-720
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    • 2005
  • Recently as large sized urban development and the city ward drifting of population are caused, the urban surface temperature is raised very seriously and rapidly. These artificial developments have destroyed the inner and outer landscapes such as topography and have changed complex local climate such as a sudden rise in temperature, the change of wind field and air pollution. In order to clarify this problem visually, the studies on extracting the thermal infrared and the characteristic analysis of local climate in urban area had been performed by using the sixth band of Landsat TM and ETM+. However, there is a need to alternate Landsat TM and ETM+ because these satellite images are not applied any more. Therefore, in this paper it is proposed to use 2 Aster image (2004.4.17 daily 2b03, 2004.10.10 night 2b03) of EOS AM and to extract the surface temperature. Also, the pattern of surface temperature in urban area and the application possibility in local climate study are proposed by verifying the correlation with A WS data. Also, IKONOS image was used to figure out the artificial development area in visual.

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Technique of Seam-Line Extraction for Automatic Image Mosaic Generation (자동 모자이크 영상제작을 위한 접합선 추출기법에 관한 연구)

  • Song, Nak-Hyeon;Lee, Sung-Hun;Oh, Kum-Hui;Cho, Woo-Sug
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.25 no.1
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    • pp.47-53
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    • 2007
  • Satellite image mosaicking is essential for image interpretation and analysis especially for a large area such as the Korean Peninsula. This paper proposed the technique of automatic seam-line extraction and the method of creating image mosaic in automated fashion. The seam-line to minimize artificial discontinuity was extracted using Minimum Absolute Gray Difference Sum algorithm with constraint condition on search-area width and Canny Edge Detection algorithm. To maintain the radiometric balance among images acquired at different time epochs, we utilized Match Cumulative Frequency method. Experimental results showed that edge detection algorithm extracted the seam-lines significantly well along linear features such as roads and rivers.

A Study of CNN-based Super-Resolution Method for Remote Sensing Image (원격 탐사 영상을 활용한 CNN 기반의 초해상화 기법 연구)

  • Choi, Yeonju;Kim, Minsik;Kim, Yongwoo;Han, Sanghyuck
    • Korean Journal of Remote Sensing
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    • v.36 no.3
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    • pp.449-460
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    • 2020
  • Super-resolution is a technique used to reconstruct an image with low-resolution into that of high-resolution. Recently, deep-learning based super resolution has become the mainstream, and applications of these methods are widely used in the remote sensing field. In this paper, we propose a super-resolution method based on the deep back-projection network model to improve the satellite image resolution by the factor of four. In the process, we customized the loss function with the edge loss to result in a more detailed feature of the boundary of each object and to improve the stability of the model training using generative adversarial network based on Wasserstein distance loss. Also, we have applied the detail preserving image down-scaling method to enhance the naturalness of the training output. Finally, by including the modified-residual learning with a panchromatic feature in the final step of the training process. Our proposed method is able to reconstruct fine features and high frequency information. Comparing the results of our method with that of the others, we propose that the super-resolution method improves the sharpness and the clarity of WorldView-3 and KOMPSAT-2 images.

Evaluation of the Utilization Potential of High-Resolution Optical Satellite Images in Port Ship Management: A Case Study on Berth Utilization in Busan New Port (고해상도 광학 위성영상의 항만선박관리 활용 가능성 평가: 부산 신항의 선석 활용을 대상으로)

  • Hyunsoo Kim ;Soyeong Jang ;Tae-Ho Kim
    • Korean Journal of Remote Sensing
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    • v.39 no.5_4
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    • pp.1173-1183
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    • 2023
  • Over the past 20 years, Korea's overall import and export cargo volume has increased at an average annual rate of approximately 5.3%. About 99% of the cargo is still being transported by sea. Due to recent increases in maritime cargo volume, congestion in maritime logistics has become challenging due to factors such as the COVID-19 pandemic and conflicts. Continuous monitoring of ports has become crucial. Various ground observation systems and Automatic Identification System (AIS) data have been utilized for monitoring ports and conducting numerous preliminary studies for the efficient operation of container terminals and cargo volume prediction. However, small and developing countries' ports face difficulties in monitoring due to environmental issues and aging infrastructure compared to large ports. Recently, with the increasing utility of artificial satellites, preliminary studies have been conducted using satellite imagery for continuous maritime cargo data collection and establishing ocean monitoring systems in vast and hard-to-reach areas. This study aims to visually detect ships docked at berths in the Busan New Port using high-resolution satellite imagery and quantitatively evaluate berth utilization rates. By utilizing high-resolution satellite imagery from Compact Advanced Satellite 500-1 (CAS500-1), Korea Multi-Purpose satellite-3 (KOMPSAT-3), PlanetScope, and Sentinel-2A, ships docked within the port berths were visually detected. The berth utilization rate was calculated using the total number of ships that could be docked at the berths. The results showed variations in berth utilization rates on June 2, 2022, with values of 0.67, 0.7, and 0.59, indicating fluctuations based on the time of satellite image capture. On June 3, 2022, the value remained at 0.7, signifying a consistent berth utilization rate despite changes in ship types. A higher berth utilization rate indicates active operations at the berth. This information can assist in basic planning for new ship operation schedules, as congested berths can lead to longer waiting times for ships in anchorages, potentially resulting in increased freight rates. The duration of operations at berths can vary from several hours to several days. The results of calculating changes in ships at berths based on differences in satellite image capture times, even with a time difference of 4 minutes and 49 seconds, demonstrated variations in ship presence. With short observation intervals and the utilization of high-resolution satellite imagery, continuous monitoring within ports can be achieved. Additionally, utilizing satellite imagery to monitor changes in ships at berths in minute increments could prove useful for small and developing country ports where harbor management is not well-established, offering valuable insights and solutions.

Progress and Land-Use Characteristics of Urban Sprawl in Busan Metropolitan City using Remote Sensing and GIS (원격탐사와 GIS를 이용한 부산광역시 도시화지역의 확산과정과 토지이용 특성에 관한 연구)

  • Park, Ho-Myung;Baek, Tae-Kyung
    • Journal of the Korean Association of Geographic Information Studies
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    • v.12 no.2
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    • pp.23-33
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    • 2009
  • Satellite image is very usefully practiced to predict and analyze physical expansion and change of city. Physical expansion and change of city is closely related to the use of land, and continuous growth management focused on the use of land is essential for sustainable city growth. In this research, the change of land cover and land-use were analyzed with basic input data from 1985 to 2000 according to artificial satellite. Moreover, the land-use turnover rate was understood and expansion trend of urban sprawl in Busan metropolitan city and land-use characteristics of the expansion area. The results are, first, the area for urban region was expanded continuously but areas for agriculture area, forest area, and water area had different changes due to administrative district reform of Busan by each year. Second, the urbanization area in Busan was increased by 3.8% from $92.5km^2$ in 1985 to $167.5km^2$ in 2000. Third, the result of analysis on land-use turnover rate showed that agriculture area was turned into urbanized area the most, and forest area was followed by. Fourth, the result of analysis on database and overlay of buildings in Busan established in 2001 showed that agriculture area are had type 1 and 2 neighborhood living facilities (45.63%), apartment house in forest area (18.49%), and factory in water area (31.84%) with high ratio.

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Shadow Detection and Correction Method for Urban Area using KOMPSAT-3 Image (KOMPSAT-3 영상을 활용한 도심지 그림자 영역의 탐지 및 보정 방법)

  • Park, Sung-Hwan;Lee, Gyu-Seok;Jung, Hyung-Sup
    • Korean Journal of Remote Sensing
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    • v.33 no.6_3
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    • pp.1197-1213
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    • 2017
  • This study was carried out to correct shadow area in urban area on KOMPSAT-3 satellite image. For this study, we analyzed characteristics of the shadow area represented by artificial structures in urban area. The proposed shadow correction method divides shadow area into umbra and penumbra areas according to intensity of darkness. The umbra area was detected through the histogram analysis and the statistical method of the NIR image, and then penumbra area and the sunlit area were detected from around the detected umbra area. The correction of the detected umbra and penumbra area were performed by applying the linear correlation correction method. As a result, it was confirmed that the proposed shadow correction method was visually performed well. Quantitative analysis was performed through profile analysis. It is proved that proposed method is useful for shadow area correction.

Construction of the image database of Earth's lava caves useful in identifying the lunar caves

  • Hong, Ik-Seon;Jeong, Jongil;Sohn, Jongdae;Oh, Suyeon;Yi, Yu
    • The Bulletin of The Korean Astronomical Society
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    • v.37 no.2
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    • pp.138.2-138.2
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    • 2012
  • Cave on the Moon is considered as the most appropriate place for human to live during the frontier lunar exploration. While the lava flows, the outer crust gets cooled and solidified. Then, the empty space is remained inside after lava flow stops. Such empty space is called the lava caves. Those lava tubes on the Earth are formed mostly by volcanic activity. However, the lava tubes on satellite like Moon and planet like Mars without volcanic activity are mostly formed by the lava flow inside of the crater made by large meteorite impact. Some part of lava tube with collapsed ceiling appears as the entrance of the cave. Such area looks like a deep crater so called a pit crater. Four large pit craters with diameter of > 60 m and depth of > 40 m are found without difficulty from Kaguya and LRO mission image archives. However, those are too deep to use as easily accessible human frontier base. Therefore, now we are going to identify some smaller lunar caves with accessible entrances using LRO camera images of 0.5 m/pixel resolution. Earth's lava caves and their entrances are well photographed by surface and aerial camera in immense volume. Thus, if the image data are sorted and archived well, those images can be used in comparison with the less distinct lunar cave and entrance images due to its smaller size. Then, we can identify the regions on the Moon where there exist caves with accessible entrances. The database will be also useful in modeling geomorphology for lunar and Martian caves for future artificial intelligence investigation of the caves in any size.

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