• Proceedings of the KSR Conference
• /
• 2004.10a
• /
• pp.892-899
• /
• 2004

Recently remote sensing technology is applied for construction projects planning and design areas by use of remote sensed satellite images according to engineering application technology in the various experimental tasks. In this study, It was applied for 3 dimensional terrain analysis and basic design by comparing to present railway and new expand doble-tract railway route of forest sites on the new construction site of 15km at national railway lines,. and then showed 3-D perspective images and fly simulation images to possibility for various application as terrain analysis modeling and running simulation at the course. As a results of its applied, It gained the results not only improvement of present methods but also real various application possibilities.

• Korean Journal of Remote Sensing
• /
• v.32 no.2
• /
• pp.87-96
• /
• 2016

Red tide, causes aquaculture industry the damages in Korea every summer, was usually detected by using satellite, aquaculture information was difficult to detect by using satellite. Therefore, we suggests the method for detecting the red tide using the coastal observation and the product from the unmanned aerial Vehicle. As a result, we obtained the high resolution unmanned aerial Vehicle images, detected the red tide by using the unsupervised classification from the true color images and the simple algorithm from the RGB color images. Compared the previous color images, unmanned aerial Vehicle images were clearly classified the ocean color, we were able to identify the red tide distribution in sea surface. These methods were determined to accurately monitor the red tide distribution on the aquaculture fields in the coastal waters where is established the aquaculture.

• Korean Journal of Remote Sensing
• /
• v.35 no.6_4
• /
• pp.1363-1372
• /
• 2019

In this study, we tried to analyze the fusion parameters required to produce a high-resolution multispectral image using an image fusion technique and to suggest global fusion parameters. We analyzed the linear regression coefficients that can simulate the panchromatic image, and the fusion coefficients required for producing the fusion image. When the fusion images were produced using the representative fusion parameters, it was confirmed that the difference in DN value between each fusion image was quantitatively smaller than when the optimal fusion parameters were used. Therefore, this study can minimize the regional characteristics reflected in the fused image.

• Korean Journal of Remote Sensing
• /
• v.33 no.6_3
• /
• pp.1215-1221
• /
• 2017

SeNtinel's Application Platform (SNAP) is an open source software developed by the European Space Agency and consists of several toolboxes that process data from Sentinel satellite series, including SAR (Synthetic Aperture Radar) and optical satellites. Among them, S1TBX (Sentinel-1 ToolBoX)is mainly used to process Sentinel-1A/BSAR images and interferometric techniques. It provides flowchart processing method such as Graph Builder, and has convenient functions including automatic downloading of DEM (Digital Elevation Model) and image mosaicking. Therefore, if computer memory is sufficient, InSAR (Interferometric SAR) and DInSAR (Differential InSAR) perform smoothly and are widely used recently in the world through rapid upgrades. S1TBX also includes existing SAR data processing functions, and since version 5, the processing capability of KOMPSAT-5 has been added. This paper shows an example of processing the interference technique of KOMPSAT-5 SAR image using S1TBX of SNAP. In the open mine of Tavan Tolgoi in Mongolia, the difference between DEM obtained in KOMPSAT-5 in 2015 and SRTM 1sec DEM obtained in 2000 was analyzed. It was found that the maximum depth of 130 meters was excavated and the height of the accumulated ore is over 70 meters during 15 years. Tidal and topographic InSAR signals were observed in the glacier area near Jangbogo Antarctic Research Station, but SNAP was not able to treat it due to orbit error and DEM error. In addition, several DInSAR images were made in the Iraqi desert region, but many lines appearing in systematic errors were found on coherence images. Stacking for StaMPS application was not possible due to orbit error or program bug. It is expected that SNAP can resolve the problem owing to a surge in users and a very fast upgrade of the software.

• Korean Journal of Remote Sensing
• /
• v.37 no.5_1
• /
• pp.1215-1227
• /
• 2021

Surface reflectance, as a product of the absolute atmospheric correction process of low-orbit satellite imagery, is the basic data required for accurate vegetation analysis. The Commission on Earth Observation Satellite (CEOS) has conducted research and guidance to produce analysis-ready data (ARD) on surface reflectance products for immediate use by users. However, this trend is still in the early stages of research dealing with ARD for high-resolution multispectral images such as KOMPSAT-3A and CAS-500, as it targets medium- to low-resolution satellite images. This study first summarizes the types of distribution of ARD data according to existing cases. The link between Open Data Cube (ODC), the cloud-based satellite image application platforms, and ARD data was also explained. As a result, we present practical ARD deployment steps for high-resolution satellite images and several types of application models in the conceptual level for high-resolution satellite images deployed in ODC and cloud environments. In addition, data pricing policies, accuracy quality issue, platform applicability, cloud environment issues, and international cooperation regarding the proposed implementation and application model were discussed. International organizations related to Earth observation satellites, such as Group on Earth Observations (GEO) and Committee on Earth Observation Satellites (CEOS), are continuing to develop system technologies and standards for the spread of ARD and ODC, and these achievements are expanding to the private sector. Therefore, a satellite-holder country looking for worldwide markets for satellite images must develop a strategy to respond to this international trend.

• Korean Journal of Remote Sensing
• /
• v.36 no.6_2
• /
• pp.1493-1507
• /
• 2020

The LEOP Cal/Val (Launch and Early Operation Phase Calibration/Validation) was carried out during 6 months after KOMPSAT-3A (KOMPSAT-3A Korea Multi-Purpose Satellite-3A) was launched in March 2015. After LEOP Cal/Val was successfully completed, high resolution KOMPSAT-3A has been successfully distributing to users over the past 8 years. The sub-meter high-resolution satellite image data obtained from KOMPSAT-3A is used as basic data for qualitative and quantitative information extraction in various fields such as mapping, GIS (Geographic Information System), and national land management, etc. The KARI (Korea Aerospace Research Institute) periodically checks and manages the quality of KOMPSAT-3A's product and the characteristics of satellite hardware to ensure the accuracy and reliability of information extracted from satellite data of KOMPSAT-3A. To minimize the deterioration of image quality due to aging of satellite hardware, payload and attitude sensors of KOMPSAT-3A, continuous improvement of image quality has been carried out. In this paper, the Cal/Val work-flow defined in the KOMPSAT-3A development phase was illustrated for the period of before and after the launch. The MTF, SNR, and location accuracy are the key parameters to estimate image quality and the methods of the measurements of each parameter are also described in this work. On the basis of defined quality parameters, the performance was evaluated and measured during the period of after LEOP Cal/Val. The current status and characteristics of MTF, SNR, and location accuracy of KOMPSAT-3A from 2016 to May 2020 were described as well.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.1071-1076
• /
• 2003

In this work, we propose a new framework of robot control for a variety of applications to our unstructured everyday environments. Programming robots can be a very time-consuming process and seems almost impossible for ordinary end users. To cope with this, this work is to provide a software framework for building robot application programs automatically, where we have robots learn how to accomplish a commanded task from the object. An integrated sensing and computing tag is embedded into every single object in the environment. In the robot controller, only the basic software libraries for low-level robot motion control are provided from the robot manufacturer. The main contributions of this work is to develop a server platform that we call Omniscient Server that generates the application programs and send them to the robot controller through the network. The object-related information from the object server merges into robot control software to generate a detailed application program based on the task commands from the human. We have built a test bed and demonstrated that a robot can perform a common household task within the proposed framework.

• Proceedings of the KSRS Conference
• /
• v.1
• /
• pp.301-304
• /
• 2006

For the purpose of investigating the contributions of various gases to climate change, the thermal radiation associated with greenhouse gases are extracted from AIRS (Atmospheric Infrared Sounder) infrared radiances over the tropical pacific region. AIRS instrument which was launched on the EOS-Aqua satellite in May 2002 covers the spectral range from 650 cm-1 to 2700 cm-1 with a spectral resolution of between 0.4 cm-1 and 1 cm-1. In order to extract the thermal radiation absorbed by individual gases, the interfering background radiances at the top of the atmosphere are simulated using the radiative transfer code MODTRAN (MODerate spectral resolution atmospheric TRANsmittance). The simulations incorporated the temperature and water vapor profiles taken from NCEP (National Centers for Environmental Prediction) reanalyses. The differences between the simulated background radiance and AIRS-measured radiance result in the absorption of upward longwave radiation by atmospheric gases (i.e. greenhouse effect). The extracted absorption bands of individual gases will allow us to quantify the radiative forcing of individual greenhouse gases and thus those data will be useful for climate change studies and for the validation of radiative transfer codes used in general circulation models.

• Korean Journal of Remote Sensing
• /
• v.33 no.4
• /
• pp.445-454
• /
• 2017

The performance of spatial downscaling models depends on the quality of input coarse scale products. Thus, the impact of intrinsic errors contained in coarse scale satellite products on predictive performance should be properly assessed in parallel with the development of advanced downscaling models. Such an assessment is the main objective of this paper. Based on a synthetic satellite precipitation product at a coarse scale generated from rain gauge data, two synthetic precipitation products with different amounts of error were generated and used as inputs for spatial downscaling. Geographically weighted regression, which typically has very high explanatory power, was selected as the trend component estimation model, and area-to-point kriging was applied for residual correction in the spatial downscaling experiment. When errors in the coarse scale product were greater, the trend component estimates were much more susceptible to errors. But residual correction could reduce the impact of the erroneous trend component estimates, which improved the predictive performance. However, residual correction could not improve predictive performance significantly when substantial errors were contained in the input coarse scale data. Therefore, the development of advanced spatial downscaling models should be focused on correction of intrinsic errors in the coarse scale satellite product if a priori error information could be available, rather than on the application of advanced regression models with high explanatory power.

• Journal of the Korean institute of surface engineering
• /
• v.49 no.4
• /
• pp.382-388
• /
• 2016

NiO nanoparticles were synthesized by hydrothermal method for the application to ethanol gas sensor. They were composited with $Co_3O_4$ nanoparticles to improve the sensitivity to ethanol gas. Scanning electron microscopy revealed that the synthesized NiO nanoparticles were plate-shaped with the approximate size and thickness of 60 - 120 nm and 20 nm, respectively. On the other hand, $Co_3O_4$ nanoparticles mixed with NiO was observed to be spherical with the size range of 30 - 50 nm. The sensitivities of NiO sensors composited with $Co_3O_4$ nanoparticles at an optimal ratio of 8 : 2 were enhanced to approximately 1.44 - 1.79 times as high as those of as-synthesized NiO sensors for the ethanol concentration of 10 - 200 ppm at $200^{\circ}C$. The mechanism of the improved ethanol gas sensing of the NiO sensors composited with $Co_3O_4$ nanoparticles was discussed.