• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.337-350
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• 2006

The characteristics of neighborhood correlation images for change detection were explored at different spatial resolution scales. Bi-temporal QuickBird datasets of Las Vegas, NV were used for the high spatial resolution image analysis, while bi-temporal Landsat $TM/ETM^{+}$ datasets of Suwon, South Korea were used for the mid spatial resolution analysis. The neighborhood correlation images consisting of three variables (correlation, slope, and intercept) were evaluated and compared between the two scales for change detection. The neighborhood correlation images created using the Landsat datasets resulted in somewhat different patterns from those using the QuickBird high spatial resolution imagery due to several reasons such as the impact of mixed pixels. Then, automated binary change detection was also performed using the single and multiple neighborhood correlation image variables for both spatial resolution image scales.

• Journal of the Korean Mathematical Society
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• v.44 no.6
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• pp.1383-1396
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• 2007

The aim of this paper is to study L-fuzzy uniformizable spaces. A new kind of topological fuzzy remote neighborhood system is defined and used for investigating the relationship between L-fuzzy co-topology and L-fuzzy (quasi-)uniformity. It is showed that this fuzzy remote neighborhood system is different from that in [23] when $\mathcal{U}$ is an L-fuzzy quasi-uniformity and they will be coincident when $\mathcal{U}$ is an L-fuzzy uniformity. It is also showed that each L-fuzzy co-topological space is L-fuzzy quasi-uniformizable.

• Honam Mathematical Journal
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• v.33 no.1
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• pp.27-41
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• 2011

This paper studies the relationship between L-fuzzy proximities and L-fuzzy topologies by topological fuzzy remote neigh-borhood systems. We will prove that the category of L-fuzzy topo- logical spaces can be embedded in the category of L-fuzzy quasi-proximity spaces as a core ective full subcategory.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.529-532
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• 2004

This study aims at examining the environment of waterfronts by applying satellite remote sensing technique. In doing so we have selected Inchon International Airport, Korea as a case. As a method of the study, Normalized Difference Vegetation Index (NDVI) and land cover changes are estimated in and around Inchon International Airport. As a result of the study, we have found vegetation's change in the Airport and variation of neighborhood city by building of waterfront.

• Journal of the Korean Mathematical Society
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• v.44 no.1
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• pp.129-137
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• 2007

It is known that connectedness is one of the important notions in topology. In this paper, a new notion of connectedness is introduced in L-topological spaces, which is called PS-connectedness. It contains some nice properties. Especially, the famous K. Fan's Theorem holds for PS-connectedness in L-topological spaces.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.92-94
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• 2007

This paper considers an optimal control problem for a remote control to an electrical drive system with a DC motor. Since it is a linear control system with time-delay subject to unknown but bounded disturbance, we construct a worst-case feedback control policy. This policy can guarantee that, for all admissible uncertain disturbances, the real system state should be in a prescribed neighborhood of a desired value, and the cost functional takes the best guarantee value. The worst-case feedback control policy is allowed to be corrected at one correction point between the initial to the final time, which is equivalent to solving a 1-level min-max problem. Since the min-max problem at the stage does not yield a simple analytical solution, we consider an approximate control policy, which is equivalent and can be solved explicitly m the numerical experiments.

• Journal of Information Processing Systems
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• v.18 no.4
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• pp.587-598
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• 2022

To increase building change recognition accuracy, we present a deep learning-based building change detection using remote sensing images. In the proposed approach, by merging pixel-level and object-level information of multitemporal remote sensing images, we create the difference image (DI), and the frequency-domain significance technique is used to generate the DI saliency map. The fuzzy C-means clustering technique pre-classifies the coarse change detection map by defining the DI saliency map threshold. We then extract the neighborhood features of the unchanged pixels and the changed (buildings) from pixel-level and object-level feature images, which are then used as valid deep neural network (DNN) training samples. The trained DNNs are then utilized to identify changes in DI. The suggested strategy was evaluated and compared to current detection methods using two datasets. The results suggest that our proposed technique can detect more building change information and improve change detection accuracy.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.625-628
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• 2010

This paper proposes a novel feature extraction method for unsupervised multispectral image segmentation based in one dimensional combined neighborhood differences (1D CND). In contrast with the original CND, which is applied with traditional image, 1D CND is computed on a single pixel with various bands. The proposed algorithm utilizes the sign of differences between bands of the pixel. The difference values are thresholded to form a binary codeword. A binomial factor is assigned to these codeword to form another unique value. These values are then grouped to construct the 1D CND feature image where is used in the unsupervised image segmentation. Various experiments using two LANDSAT multispectral images have been performed to evaluate the segmentation and classification accuracy of the proposed method. The result shows that 1D CND feature outperforms the spectral feature, with average classification accuracy of 87.55% whereas that of spectral feature is 55.81%.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.163-168
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• 1998

Extracting a Digital Elevation Model (DEM) from spaceborne imagery is important for cartographic applications of remote sensing data. The procedure for such DEM generation can be divided into stereo matching, sensor modelling and DEM interpolation. Among these, DEM interpolation contributes significantly to the completeness and accuracy of a DEM and, yet, this technique is often considered "trivial". However, na\ulcornere DEM interpolation may result in a less accurate and sometimes meaningless DEM. This paper reports the performance analysis of various DEM interpolation techniques. Using a manually derived DEM as reference, a number of sample points were created randomly. Different interpolation techniques were applied to the sample points to generate DEMs. The performance of interpolation was assessed by the accuracy of such DEMs. The results showed that kriging gave the best results at all times whereas nearest neighborhood interpolation provided a fast solution with moderate accuracy when sample points were large enough.

• Korean Journal of Remote Sensing
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• v.26 no.6
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• pp.675-680
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• 2010

Temperature is one of the main issues in climate change, and the urban heat island effect in highly developed urban areas is an important issue that we need to deal with. This study analyzed the extent of the cooling effects of urban green spaces. The study used a surface temperature map of Seoul. It found that the cooling effects of green space was observed within limited distances, although it varied a little depending on the parks investigated. The cooling effect distance ranged from 240m to 360m, averaging about 300m. It also found the size of an urban green space does not make much difference in cooling the surrounding areas. Although further investigation with diverse urban areas should be conducted on this matter, the results did imply that many small green spaces in the neighborhood are more effective than a single big green space in mitigating the heat island effects of cities.