• Korea Trade Review
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• v.45 no.1
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• pp.301-319
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• 2020

This study aims to explore the positive impact of Korean drama watching satisfaction on purchase intention for Korean products by considering the mediating roles of social distance to Korea, national image of Korea, and Korean product image. This study identified that Korean drama reduced the social distance to Korea while increasing the positive image of Koreas and Korean products. However, the reduced social distance was not positively associated with Korean product image and Korean product purchase intention. This implies that Korean dramas directly affect Korean product purchase intension and indirectly affect Korean national image and product image. This study supplies guidance to international marketers who aims to enter the Myanmar market. To use the Korean wave as a Korean product marketing tool, marketing strategies need to cover Korean culture-relevant materials such as cultural background, cultural characteristics, exposed products, and so on.

• Spatial Information Research
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• v.4 no.1
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• pp.13-20
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• 1996

This study has been on detection of land-cover change on Korean peninsula (including the area of north Korean territory) between May of 1990 year and that of 1995 year using NOAA AVHRR data. It was necessary that imagery data should be registered to each other and should not be deviated much in seasonal variation in order to recognize land - cover change. Atmosphic effect such as clould and dirt was erased by maximum NDVI(Normalized Difference Vegetation Index) method the equation of which was as following $$NDVI(i,j,d)=\frac{ch2(j,j,d)-ch1(i,j,d)}{ch2(i,j,d)+ch1(i.j,d)}$$ Each image of maximum NDVI of '90 year and '95 year was c1assifed onto 8 categories ,using iso-clustering method each of which was water, wet barren and urban, crop field, field, mixed vegetation, shrub, forest and evergreen.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.386-389
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• 1999

In this study, visible and near infrared channels of NOAA/AVHRR data were used to classify land use and vegetation types over Korean peninsula. Analyzing forest stand structures and prediction of forest productivity using satellite data were also reviewed. Land use and land cover classification was made by unsupervised clustering methods. After monthly Normalized Difference Vegetation Index (NDVI) composite images were derived from April to November 1998, the derived composite images were used as temporal feature vector's in this clustering analysis. Visually interpreted, the classification result was satisfactory in overall for it matched well with the general land cover patterns. But subclassification of forests into coniferous, deciduous, and mixed forests were much confused due to the effects of low ground resolution of AVHRR data and without defined classification scheme. To investigate into the forest stand structures, digital forest type maps were used as an ancillary data. Forest type maps, which were compiled and digitalized by Forestry Research Institute, were registered to AVHRR image coordinates. Two data sets were compared and percent forest cover over whole region was estimated by multiple regression analysis. Using this method, other forest stand structure characteristics within the primary data pixels are expected to be extracted and estimated.

• Journal of Korean Society of Rural Planning
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• v.19 no.2
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• pp.121-128
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• 2013

The greenhouse gas emission according to the energy consumption is the cause of global warming. With various climates, it is occurs the direct problems to ecosystem. The various studies are being to reduce the carbon dioxide, which accounts for more than 80% of the total greenhouse gas emissions. In this study, estimate the carbon usage using potential biomass extracted from forest type map according to land-use by satellite image, and estimate the amount of carbon dioxide, according to the energy consumption of urban area. The $CO_2$ adsorption is extracted by the amount of forest based on the direct absorption of tree, the other used investigated value. The $CO_2$ emission in Jecheon was 3,985,900 $TCO_2$ by energy consumption. At the land cover classification, the forest is analyzed as 624,085ha and the farmland is 148,700ha. The carbon dioxide absorption was estimated at 1,834,850 Tons from analyzed forest. In case of farmland, it was also estimated at 706,658 Tons.

• ETRI Journal
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• v.21 no.4
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• pp.41-51
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• 1999

This research is an attempt to obtain more accurate land cover information from LANDSAT images. Canonical correlation analysis, which has not been widely used in the image classification community, was applied to the classification of a LANDSAT images. It was found that it is easy to select training areas on the classification using canonical correlation analysis in comparison with the maximum likelihood classifier of $ERDAS^{(R)}$ software. In other words, the selected positions of training areas hardly affect the classification results using canonical correlation analysis. when the same training areas are used, the mapping accuracy of the canonical correlation classification results compared with the ground truth data is not lower than that of the maximum likelihood classifier. The kappa analysis for the canonical correlation classifier and the maximum likelihood classifier showed that the two methods are alike in classification accuracy. However, the canonical correlation classifier has better points than the maximum likelihood classifier in classification characteristics. Therefore, the classification using canonical correlation analysis applied in this research is effective for the extraction of land cover information from LANDSAT images and will be able to be put to practical use.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.341-344
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• 2007

A major obstacle to classify and validate Land Cover maps is the high cost of generating reference data or multiple thematic maps for subsequent comparative analysis. In case of inaccessible area such as North Korea, the high resolution satellite imagery may be used as in situ data so as to overcome the lack of reliable reference data. The objective of this paper is to investigate the possibility of utilizing QuickBird (0.6m) of North Korea obtained from Google Earth data provided thru internet. Monthly NDVI images of nine months from the summer of 2004 were classified into L=54 cluster using ISODATA algorithm, and these L clusters were assigned to 7 classes; coniferous forest, deciduous forest, mixed forest, paddy field, dry field, water and built-up area. The overall accuracy and Kappa index were 85.98% and 0.82, respectively, which represents about 10% point increase of classification accuracy than our previous study based on GCP point data around North Korea. Thus we can conclude that Google Earth may be used to substitute the traditional in situ data collection on the site where the accessibility is severely limited.

• Weed & Turfgrass Science
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• v.5 no.2
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• pp.88-94
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• 2016

Vehicular traffic on turf results in loss of green cover due to direct tearing of shoots and indirect long-term soil compaction. Protection of turfgrass crowns from wear could increase the ability of turf to recover from heavy traffic. Plastic turfpavers have been installed in trafficked areas to reduce soil compaction and to protect turfgrass crowns from wear. The objectives of this study were to evaluate traffic performance of turfgrasses (Zoysia matrella and Axonopus compressus) and soil mixture (high, medium and low sand mix) combinations on turf-paver complex. The traffic performance of turf and recovery was evaluated based on percent green cover determined by digital image analysis and spectral reflectance responses by NDVI-meter. Bulk density cores indicated significant increase in soil compaction from medium and low sand mixtures compared to high sand mixture. Higher reduction of percent green cover was observed from A. compressus (30-40%) than Z. matrella (10-20%) across soil mixtures. Both turf species displayed higher wear tolerance when established on higher sand (>50% sand) than low sand mixture. Positive turf recovery was also supported by complementary spectral responses. Establishment of Zoysia matrella turf on turfpaver complex using high sand mixture will result in improved wear tolerance.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.5
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• pp.435-441
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• 2020

Sentinel-2A satellite imagery provides VNIR (Visible Near InfraRed) and SWIR (ShortWave InfraRed) wavelength bands, and it is known to be effective for land cover classification, cloud detection, and environmental monitoring. Greenhouse is one of the middle classification classes for land cover map provided by the Ministry of Environment of the Republic of Korea. Since greenhouse is a class that has a lot of changes due to natural disasters such as storm and flood damage, there is a limit to updating the greenhouse at a rapid cycle in the land cover map. In the present study, we utilized Sentinel-2A satellite images that provide both VNIR and SWIR bands for the detection of greenhouse. To utilize Sentinel-2A satellite images for the detection of greenhouse, we produced high-resolution SWIR bands applying to the fusion technique performed in two stages and carried out the detection of greenhouse using SVM (Support Vector Machine) supervised classification technique. In order to analyze the applicability of SWIR bands to greenhouse detection, comparative evaluation was performed using the detection results applying only VNIR bands. As a results of quantitative and qualitative evaluation, the result of detection by additionally applying SWIR bands was found to be superior to the result of applying only VNIR bands.

• Korean Journal of Remote Sensing
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• v.37 no.4
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• pp.763-776
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• 2021

This paper introduces a method of selecting priority update areas for subdivided land cover maps by training orthoimages and serial cadastral maps in a deep learning model. For the experiment, orthoimages and serial cadastral maps were obtained from the National Spatial Data Infrastructure Portal. Based on the VGG-16 model, 51,470 images were trained on 33 subdivided classifications within the experimental area and an accuracy evaluation was conducted. The overall accuracy was 61.42%. In addition, using the differences in the classification prediction probability of the misclassified polygon and the cosine similarity that numerically expresses the similarity of the land category features with the original subdivided land cover class, the cases were classified and the areas in which the boundary setting was incorrect and in which the image itself was determined to have a problem were identified as the priority update polygons that should be checked by operators.

• Korean Journal of Optics and Photonics
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• v.19 no.4
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• pp.262-269
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• 2008

In this paper, we propose an image watermark method using multiple decoding keys. The advantages of this method are that the multiple original images are reconstructed by using multiple decoding keys in the same watermark image, and that the quality of reconstructed images is clearly enhanced based on the idea of Walsh code without any side lobe components in the decoding process. The zero-padded original images, multiplied with random-phase pattern to each other, are Fourier transformed. Encoded images are then obtained by taking the real-valued data from these Fourier transformed images. The embedding images are obtained by the product of independent Walsh codes, and these spreaded phase-encoded images which are multiplied with new random-phase images. Also we obtain the decoding keys by multiplying these random-phase images with the same Walsh code images used in the embedding images. A watermark image is then made from the linear superposition of the weighted embedding images and a cover image, which is multiplied with a new independent Walsh code. The original image is simply reconstructed by the inverse-Fourier transform of the despreaded image of the multiplication between the watermark image and the decoding key. Computer simulations demonstrate the efficiency of the proposed watermark method with multiple decoding keys and a good robustness to the external attacks such as cropping and compression.