• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.3
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• pp.339-344
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• 2016

This study is conducted for analysis of distribution of macrobenthic by using satellite image and in-situ data in the intertidal zone of Suncheon bay. The satellite images on low tide on July 7, 2010 and high tide on Sept. 25, 2010, respectively, are classified into sea water, tidal flat and land. It is to extract for intertidal zone overlaying at low tide and high tide image from previously classified image. Total number of species emergence are 196 species in the intertidal zone, and most species are emergence in the right part of the subtidal zone. The Sigambra tentaculata is the dominant species and emergence the Mediomastus californiensis, Magelona japonica, etc. It is noticed that many kind of macrobenthic distribution in the subtidal zone more than the supralittoral zone. It find out that contamination due to organic through the macrobenthic distribution with a strong resistance to organic in the subtidal zone of Suncheon Bay.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.2 s.36
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• pp.3-13
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• 2006

Extraction of man-made objects from high resolution satellite images has been studied by many researchers. In order to reconstruct accurate 3D building structures most of previous approaches assumed 3D information obtained by stereo analysis. For this, they need the process of sensor modeling, etc. We argue that a single image itself contains many clues of 3D information. The algorithm we propose projects virtual shadow on the image. When the shadow matches against the actual shadow, the height of a building can be determined. If the height of a building is determined, the algorithm draws vertical lines of sides of the building onto the building in the image. Then the roof boundary moves along vertical lines and the footprint of the building is extracted. The algorithm proposed can use the shadow cast onto the ground surface and onto facades of another building. This study compared the building heights determined by the algorithm proposed and those calculated by stereo analysis. As the results of verification, root mean square errors of building heights were about 1.5m.

• Journal of Korean Society for Geospatial Information Science
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• v.10 no.3 s.21
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• pp.115-122
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• 2002

The mainly used technique to rectify satellite images with distortion is to develop a mathematical relationship between the pixel coordinates on the image and the corresponding points on the ground. By defining the relationship between two coordinate systems, a polynomial model is designed and various linear transformations are used. These GCP based geometric correction has performed overall plane to plane mapping. In the overall plane mapping, overall structure of a scene is considered, but local variation is discarded. The highly variant height of region is resampled with distortion in the rectified image. To solve this problem, this paper proposed the TIN-based rectification on a satellite image. The TIN based rectification is good to correct local distortion, but insufficient to reflect overall structure of one scene. So, this paper shows the experimental result and the analysis of each rectification model. It also describes the relationship GCP distribution and rectification model. We can choose a geometric correction model as the structural characteristic of a satellite image and the acquired GCP distribution.

• Journal of Korean Society on Water Environment
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• v.35 no.1
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• pp.1-8
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• 2019

The purpose of this study is to evaluate the nutritional status of Lake Jinyang using Landsat 8 satellite image band correlated with chlorophyll-a, which is also related to algae proliferation. We selected 20 Landsat 8 images dating from 2013 to 2017, taken close to water quality measurement date when the cloud cover was less than 20 %. Based on the results of the previous studies, analyzing the correlation between chlorophyll-a, and Landsat 8 satellite image band, we selected near infrared wavelength, band 5 which is closely related to the population of algae. The nutritional status was classified using the Aizaki trophic state index (TSIm). The results of the regression equation between band 5 and the observed chlorophyll-a data was used to calculate chlorophyll-a for the image data from 2013 to 2017. The concentration of chlorophyll-a ranged from 3 to $16.1mg/m^3$. To illustrate the spatial distribution of chlorophyll-a within the lake, the chlorophyll-a concentration was divided into five grades. The images on October 14, 2014 and April 10, 2016 showed relatively high value of chlorophyll-a, while January 18, 2015 and December 6, 2016 chlorophyll-a value were below 5. The images on October 14, 2014 and April 10, 2016 were rated as eutrophic status in most areas. The results of simulating water quality for the day when the water quality was not measured resulted to an approximate value for the Panmun station while the Naedong station needed some corrections.

• Journal of Environmental Science International
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• v.31 no.10
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• pp.815-824
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• 2022

It is necessary to understand the amount of snowfall and area of snow cover of Mt. Halla to ensure the safety of mountaineers and to protect the ecosystem of Mt. Halla against climate change. However, there are not enough related studies and observation posts for monitoring snow load. Therefore, to supplement the insufficient data, this study proposes an analysis of snow load and snow cover using normalized-difference snow index. Using the images obtained from the Sentinel2 satellite, the normalized-difference snow index image of Mt. Halla could be acquired. This was examined together with the meteorological data obtained from the existing observatory to analyze the change in snow cover for the years 2020 and 2021. The normalized-difference snow index images showed a smaller snow pixel number in 2021 than that in 2020. This study concluded that 2021 may have been warmer than 2020. In the future, it will be necessary to continuously monitor the amount of snow and the snow-covered area of Mt. Halla using the normalized-difference snow index image analysis method.

• Journal of Advanced Navigation Technology
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• v.27 no.6
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• pp.877-883
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• 2023

For safe operation of ships and management of marine fisheries farms, the data set that extracts the boundaries of marine fisheries farms can provide information on obstacles in the vessel's navigation path in advance by examining whether it matches the fishing ground permit area. In addition, it can be used to determine whether fish farms are operating to compensate for damage caused by marine accidents, and the relevant local government can use it to manage fishing grounds. It is also highly utilized as basic data to identify obstacles for safe navigation of ships. In this study, Sentinel-2 satellite image data from the European Space Agency (ESA) was used to extract the boundaries of fish farms. From the video image, the fish farm's status data by cycle was divided into five zones: Busan-Ulsan area, Geoje-Changwon area, Goseong-Tongyeong area, and Namhae-Sacheon area. Through the image highlighting process, the farm boundary data and meta data were processed and extracted.

• Aerospace Engineering and Technology
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• v.13 no.2
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• pp.99-107
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• 2014

There are two types of Physical Model and RFM (Rational Function Model) is to determinate ground coordinates using KOMPSAT-2 and KOMPSAT-3 satellite data. Generally, RPCs(Rational Polynomial Coefficients) based on RFM is provided for users. This RPCs is to compute the ground coordinates to the image coordinates. If users produce ortho-image with provided RPCs is useful, directly compute the ground coordinates corresponding to image coordinates and check location accuracy etc. are difficult. In this study, a basic algorithm of inverse RPCs that calculates the image coordinates to ground coordinates, compute based on provided RPCs and evaluation of determinated ground coordinates using developed inverse RPCs were proposed.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.19 no.3
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• pp.291-300
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• 2001

In this paper, we developed a Satellite Image Processing System for obtaining 3-D positional information which is composed of five process modules. As a procedure of them, the Data Process module is the procedure that reads and processes the header file to generate data files. and then calculates orbital parameters and sensor attitudes for obtaining of 3-D positional information with them. The 3D Process module is to calculate 3-D positional information and the Dialog Process module is to correct the time of image frame center using the single image or stereo images for implementing the 3D Process module. We expect to obtain 3-D positional information with the header file and minimum GCPs(1∼2 points) using this system efficiently and economically in comparison with existing commercial software packages.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.182-187
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• 1999

Stereo matching is one of the most crucial parts in DEM generation. Naive stereo matching algorithms often create many holes and blunders in a DEM and therefore a carefully designed strategy must be employed to guide stereo matching algorithms to produce “good” 3D information. In this paper, we describe one such a strategy designed by the use of scene geometry, in particular, the epipolarity for generation of a DEM from linear pushbroom images. The epipolarity for perspective images is a well-known property, i.e., in a stereo image pair, a point in the reference image will map to a line in the search image uniquely defined by sensor models of the image pair. This concept has been utilized in stereo matching by applying epipolar resampling prior to matching. However, the epipolar matching for linear pushbroom images is rather complicated. It was found that the epipolarity can only be described by a Hyperbola- shaped curve and that epipolar resampling cannot be applied to linear pushbroom images. Instead, we have developed an algorithm of incorporating such epipolarity directly in least squares correlation matching. Experiments showed that this approach could improve the quality of a DEM.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.359-362
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• 2004

In multi-dimensional image, ICA-based feature extraction algorithm, which is proposed in this paper, is for the purpose of detecting target feature about pixel assumed as a linear mixed spectrum sphere, which is consisted of each different type of material object (target feature and background feature) in spectrum sphere of reflectance of each pixel. Landsat ETM+ satellite image is consisted of multi-dimensional data structure and, there is target feature, which is purposed to extract and various background image is mixed. In this paper, in order to eliminate background features (tidal flat, seawater and etc) around target feature (laver farm) effectively, pixel spectrum sphere of target feature is projected onto the orthogonal spectrum sphere of background feature. The rest amount of spectrum sphere of target feature in the pixel can be presumed to remove spectrum sphere of background feature. In order to make sure the excellence of feature extraction method based on ICA, which is proposed in this paper, laver farm feature extraction from Landsat ETM+ satellite image is applied. Also, In the side of feature extraction accuracy and the noise level, which is still remaining not to remove after feature extraction, we have conducted a comparing test with traditionally most popular method, maximum-likelihood. As a consequence, the proposed method from this paper can effectively eliminate background features around mixed spectrum sphere to extract target feature. So, we found that it had excellent detection efficiency.