• Journal of Korean Society for Geospatial Information Science
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• v.21 no.2
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• pp.93-98
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• 2013

Multi-temporal high resolution satellite images are essential data for efficient city analysis and monitoring. Yet even when acquired from the same location, identical sensors as well as different sensors, these multi-temporal images have a geometric inconsistency. Matching points between images, therefore, must be extracted to match the images. With images of an urban area, however, it is difficult to extract matching points accurately because buildings, trees, bridges, and other artificial objects cause shadows over a wide area, which have different intensities and directions in multi-temporal images. In this study, we analyze a shadow effect on image matching of high resolution satellite images in urban area using Scale-Invariant Feature Transform(SIFT), the representative matching points extraction method, and automatic shadow extraction method. The shadow segments are extracted using spatial and spectral attributes derived from the image segmentation. Also, we consider information of shadow adjacency with the building edge buffer. SIFT matching points extracted from shadow segments are eliminated from matching point pairs and then image matching is performed. Finally, we evaluate the quality of matching points and image matching results, visually and quantitatively, for the analysis of shadow effect on image matching of high resolution satellite image.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.1105-1110
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• 2009

To assess the clinical value of time resolved imaging of contrast kinetics(TRICKS) MRA by comparison with conventional time of flight(TOF) MR angiography. Both TOF-MRA and TRICKS-MRA were performed in 17 patients with cerebrovascular disease and in 6 patients with brain tumor. Among 17 cerebraovascular patients, digital subtraction angiography(DSA) data were also obtained in 11 patients. TOF-MRA showed good spatial resolution but short in temporal resolution. Although TRICKS-MRA showed somewhat low spatial resolution, it showed superior temporal resolution by distinguishing vessel and tumor in all patients. Also, from the analysis of vessel-tumor relationship, TRICKS-MRA showed better performance than TOF-MRA. TRICKS-MRA makes it possible to image arterial, capillary and venous phase sequentially with very speedy manner and therefore, the clinical use of this method is highly suggestive for future use.

• Korean Journal of Remote Sensing
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• v.35 no.4
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• pp.517-534
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• 2019

In abrupt fire disturbances, high quality images suitable for wildfire damage assessment can be difficult to acquire. Quantifying wildfire burn area and severity are essential measures for quick short-term disaster response and efficient long-term disaster restoration. Planetscope (PS) imagery offers 3 m spatial and daily temporal resolution, which can overcome the spatio-temporal resolution tradeoff of conventional satellites, albeit at the cost of spectral resolution. This study investigated the potential of augmenting PS imagery by integrating the spectral information from Sentinel-2 (S2) differenced Normalized Burn Ratio (dNBR) to PS differenced Normalized Difference Vegetation Index (dNDVI) using histogram matching,specifically for wildfire burn area and severity assessment of the Okgye wildfire which occurred on April 4th, 2019. Due to the difficulty in acquiring reference data, the results of the study were compared to the wildfire burn area reported by Ministry of the Interior and Safety. The burn area estimates from this study demonstrated that the histogram-matched (HM) PS dNDVI image produced more accurate burn area estimates and more descriptive burn severity intervals in contrast to conventional methods using S2. The HM PS dNDVI image returned an error of only 0.691% whereas the S2 dNDVI and dNBR images overestimated the wildfire burn area by 5.32% and 106%, respectively. These improvements using PS were largely due to the higher spatial resolution, allowing for the detection of sparsely distributed patches of land and narrow roads, which were indistinguishable using S2 dNBR. In addition, the integration of spectral information from S2 in the PS image resolved saturation effects in areas of low and high burn severity.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.9 no.6
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• pp.1-12
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• 2006

Remote sensing cannot provide a direct measurement of vegetation index (VI) but it can provide a reasonably good estimate of vegetation index, defined as the ratio of satellite bands. The monitoring of vegetation in nearby urban regions is made difficult by the low spatial resolution and temporal resolution image captures. In this study, enhancing spatial resolution method is adapted as to improve a low spatial resolution. Recent studies have successfully estimated normalized difference vegetation index (NDVI) using improved resolution method such as from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard EOS Terra satellite. Image enhancing spatial resolution is an important tool in remote sensing, as many Earth observation satellites provide both high-resolution and low-resolution multi-spectral images. Examples of enhancement of a MODIS multi-spectral image and a MODIS NDVI image of Cheongju using a Landsat TM high-resolution multi-spectral image are presented. The results are compared with that of the IHS technique is presented for enhancing spatial resolution of multi-spectral bands using a higher resolution data set. To provide a continuous monitoring capability for NDVI, in situ measurements of NDVI from paddy field was carried out in 2004 for comparison with remotely sensed MODIS data. We compare and discuss NDVI estimates from MODIS sensors and in-situ spectroradiometer data over Ochang plain region. These results indicate that the MODIS NDVI is underestimated by approximately 50%.

• Journal of the Korean Data and Information Science Society
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• v.27 no.3
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• pp.803-814
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• 2016

Recent times have seen an exponential increase in the amount of spatial data, which is in many cases associated with temporal data. Recent advances in computer technology and computation of hierarchical Bayesian models have enabled to analyze complex spatio-temporal data. Our work aims at modeling data of daily average nitrogen dioxide (NO2) levels obtained from 25 air monitoring sites in Seoul between 2003 and 2010. We considered an independent Gaussian process model and an auto-regressive model and carried out estimation within a hierarchical Bayesian framework with Markov chain Monte Carlo techniques. A Gaussian predictive process approximation has shown the better prediction performance rather than a Hierarchical auto-regressive model for the illustrative NO2 concentration levels at any unmonitored location.

• Journal of Ship and Ocean Technology
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• v.8 no.2
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• pp.20-28
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• 2004

A dynamic-thermodynamic sea ice model with 50-km spatial and 24-hour temporal resolution is used to investigate the spatial and long-term temporal variability of the sea ice cover the Arctic Basin. The model satisfactorily reproduces the averaged main characteristics of the sea ice and the sea ice extent in the Arctic Basin and its decrease in early 1990th. At times model allows to suppose partial recovery of sea ice cover in the last years of twenty century. The employment of explicit form for description of ridging gives opportunity to assume that the observed thinning is the result of reduction the intensity of ridging processes and to estimate long-term variability of probability the ridge free navigation in the different parts of the Arctic Ocean including the North Sea Route area.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.76-79
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• 2008

This study presents the use of multi-temporal JERS-1 SAR images to the land cover classification. So far, land cover classified by high resolution aerial photo and field survey and so on. The study site was located in Non-san area. This study developed on multi-temporal land cover status monitoring and coherence information mapping can be processing by L band SAR image. From July, 1997 to October, 1998 JERS SAR images (9 scenes) coherence values are analyzed and then classified land cover. This technique which forms the basis of what is called SAR Interferometry or InSAR for short has also been employed in spaceborne systems. In such systems the separation of the antennas, called the baseline is obtained by utilizing a single antenna in a repeat pass

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.475-478
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• 2007

This study presents the use of multi-temporal JERS-1 SAR images to extract the land cover information and possibility. So far, land cover information extracted by high resolution aerial photo and field survey. The study site was located in Non-san area. This study developed on multi-temporal land cover status monitoring and coherence information mapping can be processing by L band SAR image. From July, 1997 to October, 1998 JERS SAR images (9 scenes) coherence values are analyzed and then extracted land cover information factors, so on. This technique which forms the basis of what is called SAR Interferometry or InSAR for short has also been employed in spaceborne systems. In such systems the separation of the antennas, called the baseline is obtained by utilizing a single antenna in a repeat pass

• Proceedings of the Korean Vacuum Society Conference
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• 2014.02a
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• pp.403.1-403.1
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• 2014

In conventional far-field microscopy, two objects separated closer than approximately half of an emission wavelength cannot be resolved, because of the fundamental limitation known as Abbe's diffraction limit. During the last decade, several super-resolution methods have been developed to overcome the diffraction limit in optical imaging. Among them, super-resolution optical fluctuation imaging (SOFI) developed by Dertinger et al [1], employs the statistical analysis of temporal fluorescence fluctuations induced by blinking phenomena in fluorophores. SOFI is a simple and versatile method for super-resolution imaging. However, due to the uncontrollable blinking of fluorophores, there are some limitations to using SOFI for several applications, including the limitations of available blinking fluorophores for SOFI, a requirement of using a high-speed camera, and a low signal-to-noise ratio. To solve these limitations, we present a new approach combining SOFI with speckle pattern illumination to create illumination-induced optical fluctuation instead of blinking fluctuation of fluorophore.. This technique effectively overcome the limitations of the conventional SOFI since illumination-induced optical fluctuation is possible to control unlike blinking phenomena of fluorophore. And we present the sub-diffraction resolution image using SOFI with speckle illumination.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.2
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• pp.90-95
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• 2012

Remotely sensed data provide valuable information on land monitoring due to multi-temporal observation over large areas. Especially, high resolution imagery with 0.6~1.0 m spatial resolutions contain a wealth of information and therefore are very useful for thematic mapping and monitoring change in urban areas. Recently, remote sensing technology has been successfully utilized for natural disaster monitoring such as forest fire, earthquake, and floods. In this paper, an efficient change detection method based on texture differences observed from high resolution multi-temporal data sets is proposed for mapping disaster damage and extracting damage information. It is composed of two parts: feature extraction and detection process. Timely and accurate information on disaster damage can provide an effective decision making and response related to damage.