• Korean Journal of Remote Sensing
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• v.24 no.6
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• pp.535-549
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• 2008

Vicarious calibration for the satellite sensor relies on simulated TOA (Top-of-Atmosphere) radiances over various targets. In this study, TOA visible radiance was calculated over ocean targets which are located in five different regions over the Indian and Pacific ocean, and its possible use for the satellite sensor calibration was examined. TOA radiances are simulated with the 6S radiative transfer model for the comparison with MODIS/Terra and SeaWiFS measurements. Geometric angles and sensor characteristics of the reference satellites were taken into account for the simulation. AOT (Aerosol Optical Thickness) from MODIS/Terra, pigment concentrations from Sea WiFS, and ozone amount from OMI measurements were used as inputs to the model. Other atmospheric input parameters such as surface wind and total column water vapor were taken from NCEP/NCAR reanalysis data. The 5-day averaged radiances over all targets show that the percent differences between simulated and observed radiances are within about ${\pm}5%$ in year 2005, indicating that the calculated radiances are in good agreement with satellite measurements. It has also been shown that the algorithm can produce the SeaWiFS radiances within about ${\pm}5%$ uncertainty range. It has been suggested that the algorithm can be used as a tool for calibrating the VIS bands within about 5% uncertainty range.

• Korean Journal of Remote Sensing
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• v.33 no.5_3
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• pp.799-807
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• 2017

Environmental impact assessment is a regulation that is implemented to reduce harmful environmental impacts of development projects. However, The environmental value is difficult to quantify and the uncertainty, There is a problem of objectivity and reliability of the system is consistently pointed out. Therefore, the necessity of the data-based environmental impact assessment system is gradually increasing. Especially, environmental impact assessment is highly applicable to environmental spatial information because it contains about the development of a particular area. Also with the introduction of EIA Follow-up management system, there is a demand for a system for providing and utilizing environmental information in a time series. This study derives the necessity of information provision system and analyz existing environmental information utilization system based on the institutional characteristics of environmental impact assessment. And suggest ways to provide environmental spatial information to find policy implications for improving the limit of environmental impact assessment system.

• Korean Journal of Remote Sensing
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• v.16 no.4
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• pp.305-313
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• 2000

A vicarious calibration method was developed for the OSMI sensor calibration. Employing measured aerosol optical thickness by a sunphotometer and a sky radiometer and water leaving radiance by ship measurements as inputs, TOA (top of the atmosphere) radiance at each OSMI band was simulated in conjunction with a radiative transfer model (Rstar5b) by Nakajima and Tanaka (1988). As a case of examining the accuracy of this method, we simulated TOA radiance based on water leaving radiance measured at NASA/MOBY site and aerosol optical thickness estimated nearby at Lanai, and compared simulated results with SeaWiFS-estimated TOA radiances. The difference falls within about $\pm$5%, suggesting that OMSI sensor can be calibrated with the suggested accuracy. In order to apply this method for the OSMI sensor calibration, ground-based sun photometry and ship measurements were carried out off the east coast of Korean peninsula on May 31, 2000. Simulations of TOA radiance by using these measured data as input to the radiative transfer model show that there are substantial differences between simulated and OSMI-estimated radiances. Such a discrepancy appears to be mainly due to the cloud contamination because satellite image indicates optically thin clouds over the experimental area. Nevertheless results suggest that sensor calibration can be achieved within 5% uncertainty range if there are ground-based measurements of aerosol optical thickness, and water leaving radiances under clear-sky and optically thin atmospheric conditions.

• Korean Journal of Remote Sensing
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• v.37 no.1
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• pp.123-137
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• 2021

In this study, we performed cross calibration of KOMPSAT-3 AEISS imaging sensor with reference to normalized pixels in the Landsat 8 OLI scenes of homogenous ROI recorded by both sensors between January 2014 and December 2019 at the Libya 4 PICS. Cross calibration is using images from a stable and well-calibrated satellite sensor as references to harmonize measurements from other sensors and/or characterize other sensors. But cross calibration has two problems; RSR and temporal difference. The RSR of KOMPSAT-3 and Landsat 8 are similar at the blue and green bands. But the red and NIR bands have a large difference. So we calculate SBAF of each sensor. We compared the SBAF estimated from the TOA Radiance simulation with KOMPSAT-3 and Landsat 8, the results displayed a difference of about 2.07~2.92% and 0.96~1.21% in the VIS and NIR bands. Before SBAF, Reflectance and Radiance difference was 0.42~23.23%. Case of difference temporal, we simulated by 6S and Landsat 8 for alignment the same acquisition time. The SBAF-corrected cross calibration coefficients using KOMPSAT-3, 6S and simulated Landsat 8 compared to the initial cross calibration without correction demonstrated a percentage difference in the spectral bands of about 0.866~1.192%. KOMPSAT-3 maximum uncertainty was estimated at 3.26~3.89%; errors due to atmospheric condition minimized to less than 1% (via 6S); Maximum deviation of KOMPSAT-3 DN was less than 1%. As the result, the results affirm that SBAF and 6s simulation enhanced cross-calibration accuracy.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.99-99
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• 2022

Jeju island has a humid subtropical climate and this climate zone is expected to migrate northward toward the main land, Korea Peninsula, as temperature increases are accelerated. Vegetation type has been inevitably shifted along with the climatic change, having more subtropical species native in southeast Asia or even in Africa. With the forest composition shift, it becomes more important than ever to analyze the water balance of the forest wihth the ongoing as well as upcoming climate change. Here, we implemented the Ecosystem Demography Biosphere Model (ED2) by initializing the key variables using forest inventory data (diameter at breast height in 2012). Out of 10,000 parameter sets randomly generated from prior distribution distributions of each parameter (i.e., Monte-Carlo Method), we selected four behavioral parameter sets using remote-sensing data (LAI-MOD15A2H, GPP-MOD17A2H, and ET-MOD16A2, 8-days at 500-m during 2001-2005), and evaluated the performances using eddy-covariance carbon flux data (2012 Mar.-Sep. 30-min) and remote sensing data between 2006-2020. We simulated each of the four RCP scenarios (2.6, 4.5, 6.0, and 8.5) from four climate forcings (GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, and MIROC5 from ISIMIP2b). Based on those 64 simulation sets, we estimate the changes in water balance resulting from the forest composition shift, and also uncertainty in the estimates and the sensitivity of the estimates to the parameters, climate forcings, and RCP scenarios.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.10
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• pp.3873-3879
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• 2010

Home service robot are not working in the fixed task such as industrial robot, because they are together with human in the same indoor space, but have to do in much more flexible and various environments. Most of them are developed on the base of the wheel-base mobile robot in the same method as a vehicle robot for factory automation. In these days, for holonomic system characteristics, omni-directional wheels are used in the mobile robot. A holonomicrobot, using omni-directional wheels, is capable of driving in any direction. But trajectory control for omni-directional mobile robot is not easy. Especially, azimuth control which sensor uncertainty problem is included is much more difficult. This paper develops trajectory controller of 3-wheels omni-directional mobile robot using fuzzy azimuth estimator. A trajectory controller for an omni-directional mobile robot, which each motor is controlled by an individual PID law to follow the speed command from inverse kinematics, needs a precise sensing data of its azimuth and exact estimation of reference azimuth value. It has imprecision and uncertainty inherent to perception sensors for azimuth. In this paper, they are solved by using fuzzy logic inference which can be used straightforward to perform the control of the mobile robot by means of the fuzzy behavior-based scheme already existent in literature. Finally, the good performance of the developed mobile robot is confirmed through live tests of path control task.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.5
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• pp.398-406
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• 2003

In modular fixturing systems, a given part or a subassembly is fixed by placing fixture elements such as locators and clamps adequately on a plate with a lattice of holes. It is known that the minimal number of point contacts to restrict translational and rotational motions on a plane is four and the type of three locators and a clamp(3L/1C) is the minimal future. Brost and Goldberg developed the complete algorithm to automatically synthesize 3L/1C types of fixtures which satisfy the condition of form closure. Due to the nature of the fixture, the clearance between the fixture and the part is extremely small. It is hard to load the part repeatedly and accurately for human as well as for robot. However the condition of loadability has not been taken into account in the B&G algorithm. In this paper, a new method to decide a given fixture to be loadable by using configuration space is proposed. A method to plan for a part to be loaded by using compliance safely even in the presence of control and sensing uncertainty is proposed is well.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.178-181
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• 2005

The positioning accuracy of the Global Positioning System (GPS) has been improved considerably during the past two decades. The main error sources such as ionospheric refraction, orbital uncertainty, antenna phase center variation, signal multipath, and tropospheric delay have been reduced substantially, if not eliminated. In this study, the GPS data collected by the GPS receivers that were established as continuously operating reference stations by International GNSS Service (IGS), Ministry of the Interior (MOl), Central Weather Bureau (CWB), and Industrial Technology Research Institute (ITRI) Of Taiwan are utilized to investigate the impact of atmospheric water vapor on GPS positioning determination. The surface meteorological measurements that were concurrently acquired by instruments co-located with the GPS receivers include temperature, pressure and humidity data. To obtain the influence of the GPS height on the proposed impact study. A hydrodynamic ocean tide model (GOTOO.2 model) and solid earth tide were used to improve the GPS height. The surface meteorological data (pressure, temperature and humidity) were introduced to the data processing with 24 troposphere parameters. The results from the studies associated with different GPS height were compared for the cases with and without a priori knowledge of surface meteorological measurements. The finding based on the measurements in 2003 is that the surface meteorological measurements have an impact on the GPS height. The associated daily maximum of the differences is 1.07 cm for the KDNM station. The impact is reduced due to smoothing when the average of the GPS height for the whole year is considered.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.264-267
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• 2004

In identifying flood vulnerable areas, three methods are generally deployed: the geomorphology method which is based on topographic features; the past evidence method based on observed data of past actual floods; and, prediction of flood areas through hydrologic models. This study aims to improve the prediction model of the geomorphology method through the application of fuzzy method in GIS modeling. The generally used GIS method of superimposing thematic map layers assumes crisp boundaries of the layers, which results in either risk-averse solutions or risk-taking solutions. The introduction of fuzzy concepts to processing of evaluation criteria (DEM, slope, aspect) solves this problem. As the result of applying the fuzzy method to a test site in the west Nak-Dong river, similar flood vulnerable areas were predicted as when using the conventional Boolean criteria. The resulting map, however, showed varying degree of uncertainty of flooding in these areas. This extra information is deemed to be valuable in taking phased actions during flood response, leading to a more effective and timely decision-making.

• Proceedings of the KSRS Conference
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• v.1
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• pp.446-449
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• 2006

It is backscattering of solar radiation by water body that makes ocean color observable from above, either by airplanes or satellites. Given the very low direct contribution to backscattering by phytoplankton cells, it is curious why the retrieval of phytoplankton concentration from remotely observed ocean color is evidently successful. From semianalytical bio-optical models, a dataset is created of spectral absorption, scattering and backscattering coefficients as a function of chlorophyll concentration. Four scenarios are considered, 1) only molecular and no particle scattering, 2) random particle backscattering uncorrelated with chlorophyll concentration, 3) constrained random particle scattering with known backscattering ratio, and 4) constrained random scattering with random backscattering ratio. Scenario 1 only introduces moderate errors of -20% - 90%. And for scenarios 3 and 4, the errors are largely within 30% and 100%. Scenario 2 introduces the largest errors, with the retrieved chlorophyll concentration virtually uncorrelated with the true values, implying the backscattering must somehow be related to the trophic state. The results of the study suggested These 3 cases confirmed that while it is the absorption by phytoplankton that in large part decides the accuracy of chlorophyll concentration retrieval, for the success of monitoring of global ocean primary productivity we have to improve our knowledge on particle backscattering.