• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.1
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• pp.73-83
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• 2008

For spatial analysis and decision-making based on territorial and urban information, technologies on 3D GIS with digital image data and photo-realistic 3D image models to visualize 3D modeling are being rapidly developed. Currently, satellite images, aerial images and aerial LiDAR data are mostly used to build 3D models and textures from oblique aerial photographs or terrestrial photographs are used to create 3D image models. However, we are in need of quality 3D image models as current models cannot express topographic and features most elaborately and realistically. Thus, this study analyzed techniques to use aerial photographs, aerial LiDAR, terrestrial photographs and terrestrial LiDAR to create a 3D image model with artificial features and special topographic that emphasize spatial accuracy, delicate depiction and photo-realistic imaging. A 3D image model with spatial accuracy and photographic texture was built to be served via 3D image map services systems on the Internet. As it was necessary to consider intended use and display scale when building 3D image models, in this study, we applied the concept of LoD(Level of Detail) to define 3D image model of buildings in five levels and established the models by following the levels.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.9
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• pp.794-806
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• 2017

It is essential to protect the national space assets and space environment safely as a space development country from the continuously increasing space debris. And Active Debris Removal(ADR) is the most active way to solve this problem. In this paper, we studied the Artificial Neural Network(ANN) for a stable recognition model of vision-based space debris tracking system. We obtained the simulated image of the space environment by the KARICAT which is the ground-based space debris clearing satellite testbed developed by the Korea Aerospace Research Institute, and created the vector which encodes structure and color-based features of each object after image segmentation by depth discontinuity. The Feature Vector consists of 3D surface area, principle vector of point cloud, 2D shape and color information. We designed artificial neural network model based on the separated Feature Vector. In order to improve the performance of the artificial neural network, the model is divided according to the categories of the input feature vectors, and the ensemble technique is applied to each model. As a result, we confirmed the performance improvement of recognition model by ensemble technique.

• Journal of Satellite, Information and Communications
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• v.12 no.1
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• pp.6-12
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• 2017

Recently, the demand for SAR imaging is growing to monitor natural disasters or military sites to foresee topographic changes, where optical sensing is not easily available. High-resolution SAR images are useful in exploring topography and monitoring artificial land objects in all weather conditions. In this paper,high resolution SAR images acquired from KOMPSAT-5 are exploited for the applications of change detection and classification. In order to detect change areas, amplitude change detection (ACD) and coherence change detection (CCD) algorithms are employed and their performances are compared in practical applications. For enhanced performance, the potential of small scaled change detection is explored by combining multi-temporary SAR images. The k-means and SVM methods are applied for land classifications and their performances are compared by applying to the real spaceborne SAR images.

• Journal of Korean Society for Geospatial Information Science
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• v.8 no.1 s.15
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• pp.105-110
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• 2000

Since the advent of high resolution satellite image, possibilities of applying various human interpretation mechanism to these images have increased. Also many studies about these possibilities in many fields such as computer vision, pattern recognition, artificial intellegence and remote sensing have been done. In this field of these studies, texture is defined as a kind of quantity related to spatial distribution of brightness and tone and also plays an important role for interpretation of images. Especially, methods of obtaining texture by statistical model have been studied intensively. Among these methods, texture measurement method based on cooccurrence matrix is highly estimated because it is easy to calculate texture features compared with other methods. In addition, these results in high classification accuracy when this is applied to satellite images and aerial photos. But in the existing studies using cooccurrence matrix, features have been chosen arbitrarily without considering feature variation. And not enough studies have been implemented for appropriate resolution selection in which cooccurrence matrix can extract texture. Therefore, this study reviews the concept of cooccurrence matrix as a texture measurement method, evaluates usefulness of several features obtained from cooccurrence matrix, and proposes appropriate resolution by investigating variance trend of several features.

• Atmosphere
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• v.29 no.5
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• pp.537-550
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• 2019

To analyze the observation environment of solar radiation stations operated by the Korea Meteorological Administration (KMA), we analyzed the skyline, Sky View Factor (SVF), and solar radiation due to the surrounding topography and artificial structures using a Digital Elevation Model (DEM), 3D camera, and solar radiation model. Solar energy shielding of 25 km around the station was analyzed using 10 m resolution DEM data and the skyline elevation and SVF were analyzed by the surrounding environment using the image captured by the 3D camera. The solar radiation model was used to assess the contribution of the environment to solar radiation. Because the skyline elevation retrieved from the DEM is different from the actual environment, it is compared with the results obtained from the 3D camera. From the skyline and SVF calculations, it was observed that some stations were shielded by the surrounding environment at sunrise and sunset. The topographic effect of 3D camera is therefore more than 20 times higher than that of DEM throughout the year for monthly accumulated solar radiation. Due to relatively low solar radiation in winter, the solar radiation shielding is large in winter. Also, for the annual accumulated solar radiation, the difference of the global solar radiation calculated using the 3D camera was 176.70 MJ (solar radiation with 7 days; suppose daily accumulated solar radiation 26 MJ) on an average and a maximum of 439.90 MJ (solar radiation with 17.5 days).

• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.607-616
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• 2014

This research is to observe the shoreline changes in Jinha beach over the 50 years with aerial photographs and satellite images. The shoreline image feature was retrieved from the corrected images using wet and dry techniques and analyzed by DSAS from the statistical point of view. From 1967 to 1992, the mouth of Hoeya River was severely blocked and the northern shoreline off Jinha beach was eroded. The blockade of river mouth seemed to have been eased along with the completion of the dike, but soil continued to be deposited along the high sea away from the river month. Compared to the past, a layer of sediment has been formed off the northern coastline while the southern coastline has eroded. At least in the region subject to this research, the construction of a training dike is to blame. On top of that, a mere combination of dredges and artificial nourishment is not enough to take under control the changing shorelines properly. Thus, it is necessary to devise a more fundamental solution by taking into account reasons behind sediment from the river area that could change the shorelines besides the costal environment.

• Journal of Korean Society of Forest Science
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• v.96 no.1
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• pp.107-114
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• 2007

Establishments of the seedlings inside the natural forest from adjacent artificial forests would be an important factor in forest stand dynamics. This study was conducted to see the invasion of Korean pine (Pinus koraiensis) seedlings which is not native in this region, into the natural deciduous broad-leaved forest in Gwangneung, Korea. There is no mother tree at the I ha study site while the number of naturally regenerated P. koraiensis seedlings was 345 trees and 56% of them were clumped with more than two seedlings at each point. Applying the image segmentation method to IKONOS satellite image of January, 2003, the distance from the center of 1 ha study site to the nearest mother tree and plantation of Korean pine were 200 m and 270 m, respectively. The average height and root-collar diameter of the seedlings were 34 em and 7 mm, respectively and the age of 207 seedlings (60%) were below 5 years old. Most abundant range of soil moisture gradient and LAl (leaf area index) were from 16 to 20% and those of LAI were from 3.1 to 3.5. To understand the dynamics and seed dispersal pattern of Korean pine in the Gwangneung natural deciduous broad-leaved forests, additional studies not only long-term monitoring of growth and mortality of naturally regenerated Korean pine seedlings but also application of stable isotope analysis and molecular genetic techniques was recommended.

• Korean Journal of Optics and Photonics
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• v.34 no.1
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• pp.22-30
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• 2023

The use of segmented mirrors is one of the ways to make the primary mirror of a spaceborne satellite larger, where several small mirrors are combined into a large monolithic mirror. To align multiple segmented mirrors as one large mirror, there must be no discontinuity in the x, y-axis (tilt) and axial alignment error (piston) between adjacent mirrors. When the tilt and piston are removed, we can collect the light in one direction and get an expected clear image. Therefore, we need a precise wavefront sensor that can measure the alignment error of the segmented mirrors in nm scale. The tilt error can be easily detected by the point spread image of the segmented mirrors, while the piston error is hard to detect because of the absence of apparent features, but makes a downgraded image. In this paper we used an optical testing interferometer such as a Fizeau interferometer, which has various advantages when aligning the segmented mirror on the ground, and focused on measuring the axial displacement error of a segmented mirror as the basic research of measuring the piston errors between adjacent mirrors. First, we calculated the relationship between the axial displacement error of the segmented mirror and the surface defocus error of the interferometer and verified the calculated formula through experiments. Using the experimental results, we analyzed the measurement uncertainty and obtained the limitation of the Fizeau interferometer in detecting axial displacement errors.

• Korean Journal of Remote Sensing
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• v.34 no.6_3
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• pp.1445-1456
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• 2018

The purpose of this study is to compare the quality and characteristics of matching DEMs by using KOMPSAT-3 stereo pair capture in in-track and cross-track. For this purpose, two stereo pairs of KOMPSAT-3 were collected that were taken in the same area. The two stereo pairs have similar stereo geometry elements such as B/H, convergence angle. Sensor modeling for DEM production was performed with RFM affine calibration using multiple GCPs. The GCPs used in the study were extracted from the 0.25 m ortho-image and 5 meter DEM provided by NGII. In addition, matching DEMs were produced at the same resolution as the reference DEMs for a comparison analysis. As a result of the experiment, the horizontal and vertical errors at the CPs indicated an accuracy of 1 to 3 pixels. In addition, the shapes and accuracy of two DEMs produced in areas where the effects of natural or artificial surface land were low were almost similar.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1874-1881
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• 2021

Black ice, which occurs mainly on the road, vehicle traffic bridges and tunnel entrances due to the sub-zero temperature due to the slip of the road due to heavy snow, is not recognized because the image of asphalt is transmitted in the driver's view, so the vehicle loses braking power because it causes serious loss of life and property. In this paper, we propose a method to identify the black ice by using infrared camera and to identify the road condition by using deep learning to compensate for the disadvantages of existing black ice detection methods (artificial satellite imaging, checking the pattern of slip by ultrasonic reception, measuring the temperature of the road surface, and checking the difference in friction force of the tire during vehicle driving) and to reduce the size of the sensor to detect black ice.