• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.1
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• pp.54-61
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• 2009

This paper presents a new electromyogram (EMG) pattern recognition method based on the Hierarchical Temporal Memory (HTM) algorithm which is originally devised for image pattern recognition. In the modified HTM algorithm, a simplified two-level structure with spatial pooler, temporal pooler, and supervised mapper is proposed for efficient learning and classification of the EMG signals. To enhance the recognition performance, the category information is utilized not only in the supervised mapper but also in the temporal pooler. The experimental results show that the ten kinds of hand motion are successfully recognized.

• Journal of Forest and Environmental Science
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• v.29 no.2
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• pp.131-137
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• 2013

This study attempts to classify forest species using hyperspectral data for supporting resources management. The primary dataset used was AISA sensor. The sensor was mounted onboard the NOMAD GAF-27 aircraft at 2,000 m altitude creating a 2 m spatial resolution on the ground. Pre-processing was carried out with CALIGEO software, which automatically corrects for both geometric and radiometric distortions of the raw image data. The radiance data set was then converted to at-sensor reflectance derived from the FODIS sensor. Spectral Angle Mapper (SAM) technique was used for image classification. The spectra libraries for tree species were established after confirming the appropriate match between field spectra and pixel spectra. Results showed that the highest spectral signature in NIR range were Kembang Semangkok (Scaphium macropodum), followed by Meranti Sarang Punai (Shorea parvifolia) and Chengal (Neobalanocarpus hemii). Meanwhile, the lowest spectral response were Kasai (Pometia pinnata), Kelat (Eugenia spp.) and Merawan (Hopea beccariana), respectively. The overall accuracy obtained was 79%. Although the accuracy of SAM techniques is below the expectation level, SAM classifier was able to classify tropical tree species. In future it is believe that the most effective way of ground data collection is to use the ground object that has the strongest response to sensor for more significant tree signatures.

• Korean Journal of Remote Sensing
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• v.1 no.1
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• pp.63-87
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• 1985

Considerable experience has been reported on the use of spectral data to measure the canopy biomass of dryland grain crops and the use of these estimates to forecast subsequent grain yield. These basic procedures were retested to assess the use of the general process to forecasting grain yield for paddy rice. The use of the ratio of a multiband radiometer simulation of Thematic Mapper band 4(.76 to .90 .mu.m) divided by band 3 (.63 to .69 .mu.m) was tested to estimate the canopy biomass of paddy rice as a function of the stage of development of the rice. The correlation was found to be greatest (R = .94) at panicle differentiation about midway through the development cycle of the rice canopy. The use of this ratio of two spectral bands as a surrogate for canopy biomass was then tested for its correlation against final grain yield. These spectral estimates of canopy biomass produced the highest correlations with final grain yield (R = .87) when measured at the canopy development stages of panicle differentiation and heading. The impact of varying the amounts of supplemental nitrogen on the use of spectral measuremants of canopy biomass to estimate grain yield was also determined. The effect of the development of a significant amount of weed biomass in the rice canopy was also clearly detected.

• Journal of Environmental Science International
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• v.30 no.2
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• pp.173-184
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• 2021

Ecological disturbance plants distributed throughout the country are causing a lot of damage to us directly or indirectly in terms of ecology, economy and health. These plants are not easy to manage and remove because they have a strong fertility, and it is very difficult to express them quantitatively. In this study, drone hyperspectral sensor data and Field spectroradiometer were acquired around the experimental area. In order to secure the quality accuracy of the drone hyperspectral image, GPS survey was performed, and a location accuracy of about 17cm was secured. Spectroscopic libraries were constructed for 7 kinds of plants in the experimental area using a Field spectroradiometer, and drone hyperspectral sensors were acquired in August and October, respectively. Spectral data for each plant were calculated from the acquired hyperspectral data, and spectral angles of 0.08 to 0.36 were derived. In most cases, good values of less than 0.5 were obtained, and Ambrosia trifida and Lactuca scariola, which are common in the experimental area, were extracted. As a result, it was found that about 29.6% of Ambrosia trifida and 31.5% of Lactuca scariola spread in October than in August. In the future, it is expected that better results can be obtained for the detection of ecosystem distribution plants if standardized indicators are calculated by constructing a precise spectral angle standard library based on more data.

• Journal of the Korean association of regional geographers
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• v.9 no.4
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• pp.519-533
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• 2003

The U.S. Conservation Reserve Program (CRP) resulted in the conversion of approximately 14.8 million ha(36.5 million acres) of cropland to grassland, woodland, and other conservation uses throughout the U.S. between 1986 and 1992. One of the major results of CRP has been the addition of millions of hectares of potential wildlife habitat. primarily as grassland. In this study, we examined regional changes in landscape structure caused by the introduction of CRP. Utilizing multi-seasonal Landsat Thematic Mapper imagery, we produced maps of cropland and grassland for the pre- and post- CRP enrollment periods for a six-county region in southwest Kansas. We then applied post-classification differencing to identify regions of cropland that had been converted to CRP. Using the FRAGSTATS spatial pattern analysis program, we calculated a variety of spatial statistics to analyze changes in landscape structure due to CRP. The major impact of CRP in the six-county study area has been the reversal of an overall trend of grassland habitat fragmentation. From the standpoint of potential wildlife habitat, the introduction of CRP has greatly increased the number of patches, mean patch size, and the interior or core area of grassland patches. In addition, CRP has increased connectivity and aggregation between grassland patches, potentially important factors for species of conservation interest, particularly those that require larger expanses of unbroken habitat. Finally, the distance between neighboring patches of grassland has decreased, reducing travel distance between patches. Clearly, the introduction of CRP has substantially modified the spatial structure of the southwest Kansas landscape, with important implications for wildlife habitat.

• Korean Journal of Remote Sensing
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• v.36 no.5_2
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• pp.975-988
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• 2020

Change detection is the process of identifying changes by observing the multi-temporal images at different times, and it is an important technique in remote sensing using satellite images. Among the change detection methods, the unsupervised change detection technique has the advantage of extracting rapidly the change area as a binary image. However, it is difficult to understand the changing pattern of land cover in binary images. This study used grid points generated from seamless digital map to evaluate the satellite image change detection results. The land cover change results were extracted using multi-temporal KOMPSAT-3A (K3A) data taken by Gimje Free Trade Zone and change detection algorithm used Spectral Angle Mapper (SAM). Change detection results were presented as binary images using the methods Otsu, Kittler, Kapur, and Tsai among the automated threshold selection algorithms. To consider the seasonal change of vegetation in the change detection process, we used the threshold of Differenced Normalized Difference Vegetation Index (dNDVI) through the probability density function. The experimental results showed the accuracy of the Otsu and Kapur was the highest at 58.16%, and the accuracy improved to 85.47% when the seasonal effects were removed through dNDVI. The algorithm generated based on this research is considered to be an effective method for accuracy assessment and identifying changes pattern when applied to unsupervised change detection.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.4
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• pp.195-205
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• 2014

The ultra-high definition television (UHDTV) has been considered as a next generation broadcsating service. However the conventional digital terrestrial transmission system cannot afford the required transmission data rate of UHDTV, and thus adopting ultra-high order constellation, such as 4096-QAM, into the conventional DTT systems has been studied. In particular, when the ultra-high order constellation is adopted into the digital video broadcasting-2nd generation terrestrial (DVB-T2) unequal-error protection (UEP) properties of a codeword of an error correction coding and ultra-high order constellations should be properly matched by bit mapper in order to enhance the decoding performance. Because long codeword results in a heavy computational complexity to design the bit mapper, the DVB-T2 divided it into cascaded blocks, the bit interleaver and the bit-to-cell DEMUX, and there have been many researches related to each block. However, there are few published study related to design methodology of bit interleaver. In this respect, this paper proposes a design methodology of the bit interleaver and presents bit interleavers of 1024-QAM and 4096-QAM according to the proposed design algorithm. The newly designed interleavers improved the decoding performance of the error correction coding by maximally 0.6 dB SNR over both of AWGN and random fading channel.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.2
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• pp.88-100
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• 2013

Urban green space is one of most important aspects of urban infrastructure for improving the quality of life of city dwellers as it reduces the heat island effect and is used for recreation and relaxation. However, no systematic management of urban green space has been introduced in Korea as past practices focused on efficient development. A way to calculate the amount of green space needed to complement an urban area must be developed to preserve urban green space and to determine 'regulations determining the total amount of greenery'. In recent years, various studies have quantified urban green space and infrastructure using remotely sensed data. However, it is difficult to detect a myriad small green spaces in a city effectively when considering the spatial resolution of the data used in existing research. In this paper, we quantified small urban green spaces using CASI-1500 hyperspectral imagery. We calculated MCARI, a vegetation index for hyperspectral imagery, to evaluate the greenness of small green spaces. In addition, we applied image-classification methods, including the ISODATA algorithm and Spectral Angle Mapper, to detect small green spaces using supervised and unsupervised classifications. This could be used to categorize land-cover into four classes: unclassified, impervious, suspected green, and vegetation green.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.3
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• pp.203-209
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• 2021

With the recent development of satellite sensor technology, high-spatial-resolution imagery of various spectral wavelength bands have become possible. Worldview-3 satellite sensor provides panchromatic images with high-spatial-resolution and VNIR (Visible Near InfraRed) and SWIR (ShortWave InfraRed) bands with low-spatial-resolution, so it can be used in various fields such as defense, environment, and surveying. In this study, mineral detection was performed using Worldview-3 satellite imagery. In order to effectively utilize the VNIR and SWIR bands of the Worldview-3 satellite image, the sharpening technique was applied to the spatial resolution of the panchromatic image. To confirm the utility of SWIR bands for mineral detection, mineral detection using only VNIR bands was performed and comparatively evaluated. As the mineral detection technique, SAM (Spectral Angle Mapper), a representative similarity technique, was applied, and the pixels detected as minerals were selected by applying an empirical threshold to the analysis result. Quantitative evaluation was performed using reference data on the results of similarity analysis to evaluate the accuracy of mineral detection. As a result of the accuracy evaluation, the detection rate and false detection rate of mineral detecting using SWIR bands were calculated to be 0.882 and 0.011, respectively, and the results using only VNIR bands were 0.891 and 0.037, respectively. It was found that the detection rate when the SWIR bands were additionally used was lower than that when only the VNIR bands were used. However, it was found that the false detection rate was significantly reduced, and through this, it was possible to confirm the applicability of SWIR bands in mineral detection.

• The Journal of Engineering Geology
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• v.2 no.2
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• pp.141-146
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• 1992

Synthetic stereo-pair of Landsat TM(Thematic Mapper) and shaded relief image from DEM(Digital Elevation Model) were digitally produced. They are very useful in optimizing the geological interpretability of the remotely sensed data.