• 한국해양학회지
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• v.11 no.1
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• pp.9-17
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• 1976

Multispectral scanner data collected by LANDSAT-1 over the mid West Sea of Korea were analyzed and interpreted for delineation of coastal features and turbidity distribution patterns during different portions of the tidal cycle. Imagery from two successful LANDSAT-1 overpasses of the area in October 1972 and in October 1973 had been used to prepare schematic maps of coastal features and turbidity distributions. Color composite imagery of LANDSAT MSS 4, 5 and 7 gave the best representation of shorelines, coastlines and tidal flats. MSS 5 imagery was most effective in differentiating relative turbidity levels through density slicing techniques. Referring to the tidal power development of Garolim Bay, the basin area measurements assuming dyke construction at the bay entrance, have been carried out on the coastal reature maps comiled from LANDSAT imagery, and those results were correlated with existing data. General areal patterns of surface turbidity distribution in the study area revealed close similarity with bathymetry of the area. Synoptic circulation patterns were also well discriminated from the LANDSAT imagery using the suspended sediment as a tracer.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.1
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• pp.141-151
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• 2020

This research aimed at studying the role of self-enhancing imagery and self goal-achievement emotion in the effect of characteristics perceived at advertisements using multisensory cues on purchase intention. Sports shoes advertisement was selected as an empirical research object. Questionnaire survey method was used to collect data. 'WenJuanXing' site was used to make the questionnaire in Chinese, and it was loaded on WeChat and QQ. 260 participants from different regions of China participated in online questionnaire survey. The results of testing the hypotheses by structural equation model in Amos 21.0 program are summarized as followings. The congruency between multisensory cues and self-discrepancy awareness positively evoked the self-enhancing imagery and the self goal-achievement emotion. The object relevance between the consumer and the product advertised did not induce the emotion, but evoked the self-enhancing imagery. Both of the self-enhancing imagery and the self goal-achievement emotion had positive effects on the product purchase intention. When developing advertisement, marketers should focus on multisensory cues' characteristics to enhance the self-enhancing imageries as well as to help feel the goal-achievement emotion. They should pay attention to the ways by which the multisensory cues' characteristics used to develop advertisement can be perceived to be congruent with each other by consumers.

• Korean Journal of Remote Sensing
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• v.33 no.1
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• pp.89-95
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• 2017

Ship detection in synthetic aperture radar(SAR)imagery has long been an active research topic and has many applications. In this paper,we propose an efficient method for detecting ships from SAR imagery using filtering. This method exploits ship masking using a median filter that considers maximum ship sizes and detects ships from the reference image, to which a Non-Local means (NL-means) filter is applied for speckle de-noising and a differential image created from the difference between the reference image and the median filtered image. As the pixels of the ship in the SAR imagery have sufficiently higher values than the surrounding sea, the ship detection process is composed primarily of filtering based on this characteristic. The performance test for this method is validated using KOMPSAT-5 (Korea Multi-Purpose Satellite-5) SAR imagery. According to the accuracy assessment, the overall accuracy of the region that does not include land is 76.79%, and user accuracy is 71.31%. It is demonstrated that the proposed detection method is suitable to detect ships in SAR imagery and enables us to detect ships more easily and efficiently.

• Women's Health Nursing
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• v.17 no.2
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• pp.178-186
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• 2011

Purpose: The purpose of this study was to identify effects of guided imagery on stress including cognitive, affective, marital and social, and anxiety among women receiving in vitro fertilization (IVF). Methods: Data were collected between April, 21 and June, 17, 2008. The participants in this study were 57 women (26 for the experimental group, 31 for the control group) receiving IVF for primary or secondary infertility in one of the outpatient infertility centers in Seoul. The guided imagery (Suk, 2001) was provided through audio CD to the experimental group by themselves 8 minutes per day for 2 weeks. Data were analyzed by SPSS 12.0 windows program. Results: After guided imagery, the experimental group showed significantly lower affective stress and total stress scores. Anxiety scores increased significantly in the control group, but not in the experimental group after treatment. Conclusion: The findings suggest that guided imagery is an effective nursing intervention for reducing stress especially affective stress and anxiety among infertile women receiving IVF in outpatient infertility center.

• Korean Journal of Remote Sensing
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• v.34 no.1
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• pp.141-150
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• 2018

Crop type classification is essential for supporting agricultural decisions and resource monitoring. Remote sensing techniques, especially using hyperspectral imagery, have been effective in agricultural applications. Hyperspectral imagery acquires contiguous and narrow spectral bands in a wide range. However, large dimensionality results in unreliable estimates of classifiers and high computational burdens. Therefore, reducing the dimensionality of hyperspectral imagery is necessary. In this study, the Random Forest (RF) classifier was utilized for dimensionality reduction as well as classification purpose. RF is an ensemble-learning algorithm created based on the Classification and Regression Tree (CART), which has gained attention due to its high classification accuracy and fast processing speed. The RF performance for crop classification with airborne hyperspectral imagery was assessed. The study area was the cultivated area in Chogye-myeon, Habcheon-gun, Gyeongsangnam-do, South Korea, where the main crops are garlic, onion, and wheat. Parameter optimization was conducted to maximize the classification accuracy. Then, the dimensionality reduction was conducted based on RF variable importance. The result shows that using the selected bands presents an excellent classification accuracy without using whole datasets. Moreover, a majority of selected bands are concentrated on visible (VIS) region, especially region related to chlorophyll content. Therefore, it can be inferred that the phenological status after the mature stage influences red-edge spectral reflectance.

• Korean Journal of Remote Sensing
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• v.19 no.5
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• pp.393-402
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• 2003

In times of the civil uses of commercialized high-resolution satellite imagery, applications of remote sensing have been widely extended to the new fields or the problem solving beyond traditional application domains. Transportation application of this sensor data, related to the automatic or semiautomatic road extraction, is regarded as one of the important issues in uses of remote sensing imagery. Related to these trends, this study focuses on automatic road extraction using Gradient Direction Profile Algorithm (GDPA) scheme, with IKONOS panchromatic imagery having 1 meter resolution. For this, the GDPA scheme and its main modules were reviewed with processing steps and implemented as a prototype software. Using the extracted bi-level image and ground truth coming from actual GIS layer, overall accuracy evaluation and ranking error-assessment were performed. As the processed results, road information can be automatically extracted; by the way, it is pointed out that some user-defined variables should be carefully determined in using high-resolution satellite imagery in the dense or low contrast areas. While, the GDPA method needs additional processing, because direct results using this method do not produce high overall accuracy or ranking value. The main advantage of the GDPA scheme on road features extraction can be noted as its performance and further applicability. This experiment study can be extended into practical application fields related to remote sensing.

• Korean Journal of Remote Sensing
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• v.15 no.3
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• pp.239-251
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• 1999

The elimination process of cloud-contaminated pixels is one of important steps before obtaining the accurate parameters of land and ocean surface from AVHRR imagery. We developed a 6step threshold method to detect the cloud-contaminated pixels from NOAA-14/AVHRR datime imagery over land using different combination of channels. This algorithm has two phases : the first is to make a cloud-free characteristic data of land surface using compositing techniques from channel 1 and 5 imagery and a dynamic threshold of brightness temperature, and the second is to identify the each pixel as a cloud-free or cloudy one through 4-step threshold tests. The merits of this method are its simplicity in input data and automation in determining threshold values. The threshold of infrared data is calculated through the combination of brightness temperature of land surface obtained from AVHRR imagery, spatial variance of them and temporal variance of observed land surface temperature. The method detected the could-comtaminated pixels successfully embedded inthe NOAA-14/AVHRR daytime imagery for the August 1 to November 30, 1996 and March 1 to July 30, 1997. This method was evaluated through the comparison with ground-based cloud observations and with the enhanced visible and infrared imagery.

• Korean Journal of Remote Sensing
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• v.33 no.5_2
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• pp.621-630
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• 2017

In this paper, a study on classification targeting a main production area of garlic and onion was carried out in order to figure out the applicability of multi-temporal high-resolution satellite imagery for field crop classification. After collecting satellite imagery in accordance with the growth cycle of garlic and onion, classifications using each sing date imagery and various combinations of multi-temporal dataset were conducted. In the case of single date imagery, high classification accuracy was obtained in December when the planting was completed and March when garlic and onion started to grow vigorously. Meanwhile, higher classification accuracy was obtained when using multi-temporal dataset rather than single date imagery. However, more images did not guarantee higher classification accuracy. Rather, the imagery at the planting season or right after planting reduced classification accuracy. The highest classification accuracy was obtained when using the combination of March, April and May data corresponding the growth season of garlic and onion. Therefore, it is recommended to secure imagery at main growth season in order to classify garlic and onion field using multi-temporal satellite imagery.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.755-770
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• 2023

Due to recent severe climate change, abnormal weather phenomena, and other factors, the frequency and magnitude of natural disasters are increasing. The need for disaster management using artificial satellites is growing, especially during large-scale disasters due to time and economic constraints. In this study, we have summarized the current status of next-generation medium-sized satellites and microsatellites in operation and under development, as well as trends in satellite imagery analysis techniques using a large volume of satellite imagery driven by the advancement of the space industry. Furthermore, by utilizing satellite imagery, particularly focusing on recent major disasters such as floods, landslides, droughts, and wildfires, we have confirmed how satellite imagery can be employed for damage analysis, thereby establishing its potential for disaster management. Through this study, we have presented satellite development and operational statuses, recent trends in satellite imagery analysis technology, and proposed disaster response strategies that utilize various types of satellite imagery. It was observed that during the stages of disaster progression, the utilization of satellite imagery is more prominent in the response and recovery stages than in the prevention and preparedness stages. In the future, with the availability of diverse imagery, we plan to research the fusion of cutting-edge technologies like artificial intelligence and deep learning, and their applicability for effective disaster management.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.1
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• pp.80-89
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• 2008

Mapping applications using satellite imagery have been possible to quantitative analysis since SPOT satellite with stereo image was launched. Especially, high resolution satellite imagery was efficiently used in the field of digital mapping for the areas which are difficult to produce large-scale maps by aerial photogrammetry or carry out ground control point surveying due to unaccessibility. This study extracted the geospatial information out of consideration for topographic characteristic from ortho imagery of the National Geospatial-intelligence Agency(NGA) in the United States of America and analyzed the accuracy of plane coordinate for ortho imagery. For this purpose, the accuracy according to topographic character by comparison between both extraction data from ortho imagery and the digital topographic maps of 1:5000 scale which were produced by Korea National Geographic Information Institute(NGI) was evaluated. It is expected that the results of this study will be fully used as basic information for ground control point acquisition or digital mapping in unaccessible area.