• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.593-596
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• 2005

The MSC is a remote sensing instrument with very high performance that is to be installed on KOMPSAT2 satellite. The MSC consists of EOS (Electro-Optic Subsystem), PMU (Payload Management Unit) and PDTS (Payload Data Transmission Subsystem). PMU controls and monitors all the other payload units by sending commands and collecting telemetry. PMU is in charge of interfacing between payload system and satellite bus system. PMU gets commands from ground-station via OBC (On-Board Computer) that is a main controller of the satellite bus system and sends telemetry to the ground-station via OBC. There is a processor module, called SBC (Single Board Computer) in the PMU. The SBC is a main controller of the MSC system. The main roles of the SBC are payload mission management, command validation and execution, telemetry collection and monitoring, ancillary data handling, event reporting, power control of payload sub-units and communication with these units. Intel's 80486DX2 processor has been used for the SBC. Due to the fact that the SBC plays important roles for imaging mission execution and handles a lot of control data that is required for payload operation, it is required to make analysis of the CPU load when it is in maximum operation mode. In this paper, the analysis and measurement results of the SBC throughput in the maximum operation mode.

• Korean Journal of Remote Sensing
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• v.33 no.4
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• pp.359-375
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• 2017

We developed fog detection algorithm (KNU_FDA) based on the optical and textural properties of fog using satellite (COMS) and ground observation data. The optical properties are dual channel difference (DCD: BT3.7 - BT11) and albedo, and the textural properties are normalized local standard deviation of IR1 and visible channels. Temperature difference between air temperature and BT11 is applied to discriminate the fog from other clouds. Fog detection is performed according to the solar zenith angle of pixel because of the different availability of satellite data: day, night and dawn/dusk. Post-processing is also performed to increase the probability of detection (POD), in particular, at the edge of main fog area. The fog probability is calculated by the weighted sum of threshold tests. The initial threshold and weighting values are optimized using sensitivity tests for the varying threshold values using receiver operating characteristic analysis. The validation results with ground visibility data for the validation cases showed that the performance of KNU_FDA show relatively consistent detection skills but it clearly depends on the fog types and time of day. The average POD and FAR (False Alarm Ratio) for the training and validation cases are ranged from 0.76 to 0.90 and from 0.41 to 0.63, respectively. In general, the performance is relatively good for the fog without high cloud and strong fog but that is significantly decreased for the weak fog. In order to improve the detection skills and stability, optimization of threshold and weighting values are needed through the various training cases.

• Korean Journal of Remote Sensing
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• v.29 no.4
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• pp.351-360
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• 2013

Harmonic analysis enables to characterize patterns of variation in MODIS NDVI time series data and track changes in ground vegetation cover. In harmonic analysis, a periodic phenomenon of time series data is decomposed into the sum of a series of sinusoidal waves and an additive term. Each wave is defined by an amplitude and a phase angle and accounts for the portion of variance of complex curve. In this study, harmonic analysis was explored to tract ground vegetation variation through time for land-cover vegetation change detection. The process also enables to reconstruct observed time series data including various noise components. Harmonic model was tested with simulation data to validate its performance. Then, the suggested change detection method was applied to MODIS NDVI time series data over the study period (2006-2012) for a selected test area located in the northern plateau of Korean peninsula. The results show that the proposed approach is potentially an effective way to understand the pattern of NDVI variation and detect the change for long-term monitoring of land cover.

• Korean Journal of Remote Sensing
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• v.33 no.1
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• pp.1-13
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• 2017

This study investigates the geometric and spatial image quality analysis of KOMPSAT-3A stereo pair. KOMPSAT-3A is, the latest satellite of KOMPSAT family, a Korean earth observation satellite operating in optical bands. A KOMPSAT-3A stereo pair was taken on 23 November, 2015 with 0.55 m ground sampling distance over Terrassa area of Spain. The convergence angle of KOMPSAT-3A stereo pair was estimated as $58.68^{\circ}$. The investigation was assessed through the evaluation of the geopositioning analysis, image quality estimation and the accuracy of automatic Digital Surface Model (DSM) generation and compared with those of KOMPSAT-3 stereo pair with the convergence angle of $44.80^{\circ}$ over the same area. First, geopositioning accuracy was tested with initial rational polynomial coefficients (RPCs) and after compensating the biases of the initial RPCs by manually collected ground control points. Then, regarding image quality, relative edge response was estimated for manually selected points visible from two stereo pairs. Both of the initial and bias-compensated positioning accuracy and the quality assessment result expressed that KOMPSAT-3A images showed higher performance than those of KOMPSAT-3 images. Finally, the accuracy of DSMs generated from KOMPSAT-3A and KOMPSAT-3 stereo pairs were examined with respect to the reference LiDAR-derived DSM. The various DSMs were generated over the whole coverage of individual stereo pairs with different grid spacing and over three types of terrain; flat, mountainous and urban area. Root mean square errors of DSM from KOMPSAT-3A pair were larger than those for KOMPSAT-3. This seems due to larger convergence angle of the KOMPSAT-3A stereo pair.

• Korean Journal of Remote Sensing
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• v.33 no.2
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• pp.159-169
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• 2017

The Satellite Electro-Optic Payload System needsspecial requirements with the conditions of limited power consumption and the space environment of solar radiation. The acquired image quality should be mainly depend on the GSD (Ground Sampled Distance), SNR (Signal to Noise Ratio), and MTF (Modulation Transfer Function). On the well-manufactured sensor level, the thermal noise is removed on ASP (Analog Signal Processing) using the CDS (Corrective Double Sampling); the noise signal from the image sensor can be reduced from the offset signals based on the pre-pixels and the dark-pixels. The non-uniformity shall be corrected with gain, offset, and correction parameter of the image sensor pixel characteristic on the sensor control system. This paper describes the SNR enhancement method of the satellite EOS payload using the mentioned noise remove processes on the system design and operation, which is verified by tests and simulations.

• Journal of Korean Society for Atmospheric Environment
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• v.22 no.6
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• pp.851-862
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• 2006

Satellites have been valuable tool for global/regional scale atmospheric environment monitoring as well as emission source detection. In this study, we present the results of application of satellite remote sensing data for air quality forecast in Seoul metropolitan area. AOT (Aerosol Optical Thickness) data from TERRA/MODIS (Moderate Resolution Imaging Spectre-radiometer) satellite were compared to ground based $PM_{10}$ mass concentrations, and used to estimate the possibility of the aerosol forecasting in Seoul metropolitan area. Although correlation coefficient (${\sim}0.37$) between MODIS AOT products and surface $PM_{10}$ concentration data was relatively low, there was good correlation between MODIS AOT and surface PM concentration under certain atmospheric conditions, which supports the feasibility of using the high-resolution MODIS AOT for air quality forecasting. The MODIS AOT data with trajectory forecasts also can provide information on aerosol concentration trend. The success rate of the 24 hour aerosol concentration trend forecast result was about 75% in this study. Finally, application of satellite remote sensing data with ground-based air quality observations could provide promising results for air quality monitoring and more exact trend forecast methodology by high resolution satellite data and verification with long term measurement dataset.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.1
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• pp.265-276
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• 2018

Observation and data analysis techniques have been developed for observational blind areas in the lower atmosphere that are difficult to be monitored with fixed equipment on the ground. The vertical data of temperature and relative humidity are remotely collected by the UHF radiosonde installed on UAV and compared with the data measured in the 10 m weather tower. From the validated vertical profile, extrapolated surface temperature and the bulk transfer method were used to estimate the sensible heat flux depending on the atmospheric stability. Compared with the sensible heat flux measured by the 3-dimensional ultrasonic anemometer on the ground, the error of the sensible heat flux estimated was 23% that is less than the range of 30% allowed in the remote sensing. Estimated atmospheric boundary layer height from UAV sensible heat fluxes can provide useful data for air pollution diffusion models in real time and economically.

• Korean Journal of Remote Sensing
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• v.24 no.6
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• pp.591-603
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• 2008

Satellite performance can be evaluated by image quality. MTF(Modulation Transfer Fuction), SNR(Signal To Noise Ratio), GSD(Ground Sample Distance) etc. are important bias parameters to analyze image quality. It is necessary to estimate quality of satellite image in design stage. In this paper, the simulating method of satellite image quality, considering design, manufacturing, and operation, is proposed. The proposed method shall be used to estimate and restore quality of satellite image.

• Korean Journal of Remote Sensing
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• v.26 no.3
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• pp.347-359
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• 2010

Ortho-photos provide valuable spatial and spectral information for various Geographic Information System (GIS) and mapping applications. The absence of relief displacement and the uniform scale in ortho-photos enable interested users to measure distances, compute areas, derive geographic locations, and quantify changes. Differential rectification has traditionally been used for ortho-photo generation. However, differential rectification produces serious problems (in the form of ghost images) when dealing with large scale imagery over urban areas. To avoid these artifacts, true ortho-photo generation techniques have been devised to remove ghost images through visibility analysis and occlusion detection. So far, the Z-buffer method has been one of the most popular methods for true ortho-photo generation. However, it is quite sensitive to the relationship between the cell size of the Digital Surface Model (DSM) and the Ground Sampling Distance (GSD) of the imaging sensor. Another critical issue of true ortho-photo generation using high resolution satellite imagery is the scan line search. In other words, the perspective center corresponding to each ground point should be identified since we are dealing with a line camera. This paper introduces alternative methodology for true ortho-photo generation that circumvents the drawbacks of the Z-buffer technique and the existing scan line search methods. The experiments using real data are carried out while comparing the performance of the proposed and the existing methods through qualitative and quantitative evaluations and computational efficiency. The experimental analysis proved that the proposed method provided the best success ratio of the occlusion detection and had reasonable processing time compared to all other true ortho-photo generation methods tested in this paper.

• Korean Journal of Remote Sensing
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• v.18 no.4
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• pp.233-242
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• 2002

In this paper, an epipolar model without the ephemeris data is proposed. Also, various epipolar models such as the epipolar geometry of perspective sensor, the one proposed by Gupta and Hartley and the one based on the Orun and Natarajan's sensor model are reviewed and their accuracy are quantitatively analyzed using devised measure. Modeling data from ground control points, ground control points, ephemeris data and independent checking points are selected on SPOT over Taejon and Boryung area and KOMPSAT over Taejon and Nonsan area. Based on the results, the epipolar model of perspective sensor and the one by Gupta and Hartley have the average accuracy within 1 pixel but show high errors in several checking points. The proposed epipolarity model provides better results than that of perspective sensor and by Gupta and Hartley. Also, it shows the accuracy similar to the one based on Orun and Natarajan's sensor model.