• Aerospace Engineering and Technology
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• v.7 no.2
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• pp.82-87
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• 2008

In this study, the radiometric signal modeling is performed for the high resolution earth observation system in visible spectral range from space. The medeling includes solar radiation as a source of the radiometric energy, atmosphere and surface albedo of earth, and the spaceborne camera characteristics for the integrated modeling. The final output of the radiometric modeling is the number of electron produced by the detector of electro-optical camera.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.515-523
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• 2018

In order to obtain consistent change detection result for multi-temporal satellite images, preprocessing must be performed. In particular, the preprocessing related to the spectral values can be performed by the radiometric normalization, and relative radiometric normalization is generally utilized. However, most relative radiometric normalization methods assume a linear relationship between the two images, and nonlinear spectral characteristics such as phenological differences are not considered. Therefore, this study proposes a relative radiometric normalization which assumes nonlinear relationships that can perform compositive normalization of radiometric and phenological characteristics. The proposed method selects the subject and reference images, and then extracts the radiometric control set samples through the no-change method. In addition, spectral indexes as well as pixel values are extracted in order to consider sufficient information, and modeling of nonlinear relationships is performed through multilayer perceptron. Finally, the proposed method is compared with the conventional relative radiometric normalization methods, which shows that the proposed method is visually and quantitatively superior.

• Korean Journal of Remote Sensing
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• v.26 no.1
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• pp.9-20
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• 2010

The LIDAR data can be efficiently utilized for automatic reconstruction of 3D models of objects on the terrain and the terrain itself. In this paper, we attempted to generate simulated waveforms of FW (Full-Waveform) LIDAR (LIght Detection And Ranging). We performed the geometric modeling of the sensor and objects, and the radiometric modeling of the waveform intensity. First, we compute the origins and directions of the sub-beams by considering the divergence effects of a laser beam. We then searched for the locations at which the sub-beams intersected with the objects, such as ground, buildings and trees. Finally, we generate the individual waveforms of the reflected sub-beams and the waveform of the entire beam by summing the individual ones. With the experimental results, we confirmed the waveforms were reasonably generated, showing the characteristics of the surfaces the beam interacted with.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.191-196
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• 2002

From this year, KIGAM, one of Korean government-supported research institutes, has started new national program for digital geologic/natural resources infrastructure building. The goal of this program is to prepare digitally oriented infrastructure for practical digital database building, management, and public services of numerous types of paper maps related to geo-scientific resources or geologic thematic map sets: hydro-geologic map, applied geologic map, geo-chemical map, airborne radiometric/magnetic map, coal geologic map and off-shelf bathymetry map and so forth. As for digital infrastructure, several research issues in this topic are composed of: ISP (Information Strategy Planning), geo-framework modeling of each map set, pilot database building, cyber geo-mineral directory service system, and web based geologic information retrieval system upgrade which services Korean digital geologic maps scaled 1:50K. In this study, UML (Unified Modeling Language)-based data modeling of geo-data sets by and in KIGAM, among them, is mainly discussed, and its results are also presented in the viewpoint of digital geo-modeling ISP. It is expected this model is further progressed with the purpose of being a guidance or framework modeling for geologic thematic mapping and practical database building, as well as other types of national thematic map database building.

• Korean Journal of Optics and Photonics
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• v.25 no.5
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• pp.245-253
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• 2014

We report a realistic field-performance simulation for a new MWIR camera. It is designed for early detection of missile plumes over a distance range of a few hundred kilometers. Both imaging and radiometric performance of the camera are studied by using real-scale integrated ray tracing, including targets, atmosphere, and background scene models. The simulation results demonstrate that the camera would satisfy the imaging and radiometric performance requirements for field operation.

• Proceedings of the KSRS Conference
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• v.1
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• pp.274-277
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• 2006

KARI is currently developing a geostationary ocean color imager (GOCI) for COMS. We report the progress in integrated optical modeling and analysis for stray light suppression and the end-to-end instrument performance verification including in-orbit calibration. The Sun is modeled as the emitting light source and the selected area around Korean peninsular as the observation target that scatters the sun light towards GOCI in orbit. The optical ray tracing employing active geometric scaling was then used for precise characterization of the spatial and radiometric performance at the instrument focal plane. The analysis results show positive reduction in the simulated stray light level with the design improvement including baffles. It also indicates that the ray traced in-orbit radiometric performances are effective tools for the independent assessment of more traditional linear and quadratic equation based estimation of water leaving radiance. The concept of integrated GOCI optical model and the computational method are presented.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.5
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• pp.687-698
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• 2012

LADAR systems can rapidly acquire 3D point clouds by sampling the target surfaces using laser pulses. Such point clouds are widely used for diverse applications such as DSM/DTM generation, forest biomass estimation, target detection, wire avoidance and so on. Many kinds of LADAR systems have been developed with their respective purposes and applications. Particularly, Geiger mode imaging LADAR systems are increasingly utilized since they are energy efficient thank to extremely sensitive detectors incorporated into the systems. The purpose of this research is the performance assessment of a Geiger mode imaging LADAR system based on simulation with the real system parameters. We thus developed a simulation method of such a LADAR system by modeling its geometric, radiometric, optic and electronic aspects. Based on the simulation, we performed the performance assessment of a newly designed system to derive the outlier ratio and false alarm rate expected during its operation in almost real environment with reasonable system parameters. The proposed simulation and performance assessment method will be effectively utilized for system design and optimization, and test data generation.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.2
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• pp.47-54
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• 2012

Additional high resolution satellite images, other period or site, are essential for efficient city modeling and analysis. However, the same ground objects have a radiometric inconsistency in different satellite images and it debase the quality of image processing and analysis. Moreover, in an urban area, buildings, trees, bridges, and other artificial objects cause shadow effects, which lower the performance of relative radiometric normalization. Therefore, in this study, we exclude shadow areas and suggest the selective histogram matching methods for image based application without supplementary digital elevation model or geometric informations of sun and sensor. We extract the shadow objects first using adjacency informations with the building edge buffer and spatial and spectral attributes derived from the image segmentation. And, Outlier objects like a asphalt roads are removed. Finally, selective histogram matching is performed from the shadow masked multi-temporal Quickbird-2 images.

• Korean Journal of Geomatics
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• v.2 no.1
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• pp.37-46
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• 2002

Accurate classification of water area is an preliminary step to accurately analyze the flooded area and damages caused by flood. This step is especially useful for monitoring the region where annually repeating flood is a problem. The accurate estimation of flooded area can ultimately be utilized as a primary source of information for the policy decision. Although SAR (Synthetic Aperture Radar) imagery with its own energy source is sensitive to the water area, its shadow effect similar to the reflectance signature of the water area should be carefully checked before accurate classification. Especially when we want to identify small flood area with mountainous environment, the step for removing shadow effect turns out to be essential in order to accurately classify the water area from the SAR imagery. In this paper, the flood area was classified and monitored using multi-temporal RADARSAT SAR images of Ok-Chun and Bo-Eun located in Chung-Book Province taken in 12th (during the flood) and 19th (after the flood) of August, 1998. We applied several steps of geometric and radiometric calculations to the SAR imagery. First we reduced the speckle noise of two SAR images and then calculated the radar backscattering coefficient $(\sigma^0)$. After that we performed the ortho-rectification via satellite orbit modeling developed in this study using the ephemeris information of the satellite images and ground control points. We also corrected radiometric distortion caused by the terrain relief. Finally, the water area was identified from two images and the flood area is calculated accordingly. The identified flood area is analyzed by overlapping with the existing land use map.

• Proceedings of the KSRS Conference
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• v.2
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• pp.647-650
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• 2006

Compact Airborne Spectrographic Imager (CASI) hyperspectral imagery was acquired over the Little Miami River Watershed (1756 square miles) in Ohio, U.S.A., which is one of the largest hyperspectral image acquisition. For the development of a 4m-resolution land cover dataset, a hierarchical approach was employed using two different classification algorithms: 'Image Object Segmentation' for level-1 and 'Spectral Angle Mapper' for level-2. This classification scheme was developed to overcome the spectral inseparability of urban and rural features and to deal with radiometric distortions due to cross-track illumination. The land cover class members were lentic, lotic, forest, corn, soybean, wheat, dry herbaceous, grass, urban barren, rural barren, urban/built, and unclassified. The final phase of processing was completed after an extensive Quality Assurance and Quality Control (QA/QC) phase. With respect to the eleven land cover class members, the overall accuracy with a total of 902 reference points was 83.9% at 4m resolution. The dataset is available for public research, and applications of this product will represent an improvement over more commonly utilized data of coarser spatial resolution such as National Land Cover Data (NLCD).