• Journal of Environmental Impact Assessment
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• v.18 no.6
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• pp.387-392
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• 2009

As Our society's environmental awareness and concern the significant increases, the importance of the legal system for environmental conservation such as the Prior Environmental Review System, Environmental Impact Assessment is growing increasingly. but, still critical issues are present such as reliability. Though there could be various causes such as the system or procedures etc. Above all, basically the environmental data problem is the critical cause. Therefore, this study was trying to improve the environmental data accuracy using the high-resolution color aerial photography, LiDAR data and Object Oriented Classification method. And in this study, classification based on coverage percentage of a particular species was attempted through the multi-resolution segmentation and multi-level classification method. The classification result was verified by comparison with 11 points local survey data. All 11 points were classified correctly. And even though the exact coverage percentage of the particular species did not be measured, It was confirmed that the species was occupied similar portion. It is important that the environmental data which can be used for the conservation value assessment could be acquired.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.856-858
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• 2003

Biotop map can be utilized in the urban area for nature conservation and impact assessment for the proposed activities. High resolution satellite data such as IKONOS and KOMPSAT1-EOS were used to classify land use activities in biotop mapping. After land use classification, field -check was done to survey the wildlife and vegetation. These maps were combined and the boundaries were delineated to produce the biotop map. Within the boundary the characteristics of each polygon were identified, and named. This study was carried out at Daedok Science Town in Taejeon Metropolitan Area. The purpose of this study is to produce the biotop map using high resolution remote sensing data together with other ground data.

• Korean Journal of Remote Sensing
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• v.20 no.5
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• pp.329-335
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• 2004

Biotop map can be utilized for nature conservation and assessment of environmental impact for human activities in urban area. High resolution satellite images such as IKONOS and KOMPSAT1-EOC were interpreted to classify land use, hydrology, impermeable pavement ratio and vegetation for biotop mapping. Wildlife habitat map and detailed vegetation map obtained from former study results were used as ground truth data. Vegetation was investigated directly for the area where the detailed vegetation map is not available. All these maps were combined and the boundaries were delineated to produce the biotop map. Within the boundary, the characteristics of each polygon were identified, and named. This study investigates the possibility of biotop mapping using high resolution satellite remote sensing data together with field data with the goal of contributing to nature conservation in urban area.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.6
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• pp.37-49
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• 2023

Rainfall data is one of the most important data in hydrologic modeling. In this study, the impacts of spatial resolution of precipitation data on hydrological responses were assessed using SWAT in the Santa Fe River Basin, Florida. High correlations were found between the FAWN and NLDAS rainfall data, which are observed weather data and simulated weather data based on observed data, respectively. FAWN-based scenarios had higher maximum rainfall and more rainfall days and events compared to NLDAS-based scenarios. Downstream areas showed lower correlations between rainfall and peak discharge than upstream areas due to the characteristics of study site. All scenarios did not show significant differences in base flow, and showed less than 5% of differences in high flows among NLDAS-based scenarios. The impact of resolution will appear differently depending on the characteristics of the watershed and topography and the applied model, and thus, is a process that must be considered in advance in runoff simulation research. The study suggests that applying the research method to watersheds in Korea may yield more pronounced results, and highlights the importance of considering data resolution in hydrologic modeling.

• Atmosphere
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• v.31 no.2
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• pp.185-198
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• 2021

In this study, we examined a spatial downscaling method based on Gradient and Inverse Distance Squared (GIDS) weighting to produce high-resolution grid data from a numerical weather prediction model over Korean Peninsula with complex terrain. The GIDS is a simple and effective geostatistical downscaling method using horizontal distance gradients and an elevation. The predicted meteorological variables (e.g., temperature and 3-hr accumulated rainfall amount) from the Limited-area ENsemble prediction System (LENS; horizontal grid spacing of 3 km) are used for the GIDS to produce a higher horizontal resolution (1.5 km) data set. The obtained results were compared to those from the bilinear interpolation. The GIDS effectively produced high-resolution gridded data for temperature with the continuous spatial distribution and high dependence on topography. The results showed a better agreement with the observation by increasing a searching radius from 10 to 30 km. However, the GIDS showed relatively lower performance for the precipitation variable. Although the GIDS has a significant efficiency in producing a higher resolution gridded temperature data, it requires further study to be applied for rainfall events.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.390-393
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• 2007

KOMPSAT-2, the first Korean high resolution earth observing satellite, continuously acquires high resolution images since July 2006. The quality of satellite images should be geometrically and radiometrically ensured before distribution to users. This study focused on absolute radiometric calibration which is a prerequisite procedure to ensure the radiometric quality of optical satellite images. In this study, we performed reflectance-based vicarious calibration methods on several uniform targets collected through several field campaigns in 2007. The radiative transfer model, MODTRAN, was used to estimate the amount of energy received at the sensor. The energy reached at the sensor are affected by several factors such as reflectance of targets, atmospheric condition, geometry condition between Sun and the sensor, etc. This study proposes the absolute radiometric calibration coefficients of KOMPSAT-2 MSC images combining several types of collected data through field works and tried to compare dynamic range of sensor-detected energy with other commercial high resolution sensors.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2343-2346
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• 2003

The spatial resolution of multispectral images can be improved by merging them with higher resolution image data. A fundamental problem frequently occurred in existing fusion processes, is the distortion of spectral information. This paper presents a spatially adaptive image fusion algorithm which produces visually natural images and retains the quality of local spectral information as well. High frequency information of the high resolution image to be inserted to the resampled multispectral images is controlled by adaptive gains to incorporate the difference of local spectral characteristics between the high and the low resolution images into the fusion. Each gain is estimated to minimize the l$_2$-norm of the error between the original and the estimated pixel values defined in a spatially adaptive window of which the weight are proportional to the spectral correlation measurements of the corresponding regions. This method is applied to a set of co-registered Landsat7 ETM＋ panchromatic and multispectral image data.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.725-728
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• 1988

Image restoration technique using dual sensor is presented in this paper. Digital Radiography image (1024xlO24) is obtained by conventional resolution sensor. We also obtain local DR image data by high resolution sensor. Two dimensional maximum entropy power spectrum estimation (2-D ME PSE) is applied to low resolution image and high resolution image for the purpose of the power spectrum estimation of each image. A class of linear algebraic restoration filter, parametric projection filter (PPF), is derived from the power spectrums of each image. It is shown that the noise energy may be considerably reduced through the PPF.

• Korean Journal of Remote Sensing
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• v.24 no.3
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• pp.257-266
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• 2008

This study presents an approach to synthesize multispectral images at a higher resolution by exploiting a high-resolution image acquired in panchromatic modality. The synthesized images should be similar to the multispectral images that would have been observed by the corresponding sensor at the same high resolution. The proposed scheme is designed to reconstruct the multispectral images at the higher resolution with as less color distortion as possible. It uses a regression model of the second order to fit panchromatic data to multispectral observations. Based on the regression model, the multispectral images at the higher spatial resolution of the panchromatic image are optimized by a quadratic programming. In this study, the new method was applied to the IKONOS 1m panchromatic and 4m multispectral data, and the results were compared with them of several current approaches. Experimental results demonstrate that the proposed scheme can achieve significant improvement over other methods.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.6_2
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• pp.653-663
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• 2012

Using soft classification, it is possible to obtain the land cover proportions from the remotely sensed image. These land cover proportions are then used as input data for a procedure called "super-resolution mapping" to produce the predicted hard land cover layers at higher resolution than the original remotely sensed image. Superresolution mapping can be implemented using a number of algorithms in which the Hopfield Neural Network (HNN) has showed some advantages. The HNN has improved the land cover classification through superresolution mapping greatly with the high resolution data. However, the super-resolution mapping is based on the spatial dependence assumption, therefore it is predicted that the accuracy of resulted land cover classes depends on the relative size of spatial features and the spatial resolution of the remotely sensed image. This research is to evaluate the capability of HNN to implement the super-resolution mapping for SPOT image to create higher resolution land cover classes with different zoom factor.