• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.807-810
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• 2003

This research uses high-resolution satellite images as a source of collecting farmland information. For effectively extract the paddy area, we use texture information and different classify methods to assist the satellite image classification. First, using maximum likelihood classifier to extract paddy information from images. The results show that User Accuracy and Procedure Accuracy of the paddy area can increase from 80.60% to 95.45% and 84.38% to 95.45%. Second, establishing a paddy Knowledge Base and using Knowledge Base Classifier to extract paddy area, and result shows the User Accuracy and Producer Accuracy to be 92.16% and 90.06%. Finally, The result shows we can effectively contribute to the paddy field information extraction from high-resolution satellite images.

• Korean Journal of Environmental Agriculture
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• v.30 no.4
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• pp.367-376
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• 2011

BACKGROUND: In order to develop effective assessment method for Korean paddy soil microbial community structure, reliable genomic DNA extraction method from paddy soil and quantitative real-time PCR (qRT-PCR) method are needed to establish METHODS AND RESULTS: Out of six conventional soil genomic DNA extraction methods, anion exchange resin purification method was turn to be the most reliable. Various PCR primers for distinguishing five bacterial phylum (${\alpha}$-Proteobacteria, ${\beta}$-Proteobacteria, Actinobacteria, Bacteroidetes, Firmicutes), all bacteria, and all fungi were tested. Various qRT-PCR temperature conditions were also tested by repeating experiment. Finally, both genomic DNA extraction and qRT-PCR methods for paddy soil were well established. CONCLUSION: Quantitative real-time PCR (qRT-PCR) method to assess paddy soil microbial community was established.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.5
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• pp.443-450
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• 2014

To fulfill the recent increasement in the public and private demands for various spatial data, the central and local governments started to produce those data. The low-level land cover map has been produced since 2000, yet the production of high-level land covered map has started later in 2010, and recently, a few regions was completed recently. Although many studies have been carried to improve the quality of land that covered in the map, most of them have been focused on the low-level and mid-level classifications. For that reason, the study for high-level classification is still insufficient. Therefore, in this study, we suggested the automatic extraction of land readjustment for paddy land that updated in the mid-level land mapping. At the study, the RapidEye satellite images, which consider efficient to apply in the agricultural field, were used, and the high pass filtering emphasized the outline of paddy field. Also, the binary images of the paddy outlines were generated from the Otsu thresholding. The boundary information of paddy field was extracted from the image-to-map registrations and masking of paddy land cover. Lastly, the snapped edges were linked, as well as the linear features of paddy outlines were extracted by the regional Hough line extraction. The start and end points that were close to each other were linked to complete the paddy field outlines. In fact, the boundary of readjusted paddy fields was able to be extracted efficiently. We could conclude in that this study contributed to the automatic production of a high-level land cover map for paddy fields.

• Journal of The Korean Society of Agricultural Engineers
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• v.56 no.3
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• pp.55-64
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• 2014

While utilizing high resolution satellite image for land use classification has been popularized, object-oriented classification has been adapted as an affordable classification method rather than conventional statistical classification. The aim of this study is to extract the paddy field area using object-oriented classification with time series NDVI from high-resolution satellite images, and the RapidEye satellite images of Jaeryung-gun in North Korea were used. For the implementation of object-oriented classification, creating objects by setting of scale and color factors was conducted, then 3 different land use categories including paddy field, forest and water bodies were extracted from the objects applying the variation of time-series NDVI. The unclassified objects which were not involved into the previous extraction classified into 6 categories using unsupervised classification by clustering analysis. Finally, the unsuitable paddy field area were assorted from the topographic factors such as elevation and slope. As the results, about 33.6 % of the total area (32313.1 ha) were classified to the paddy field (10847.9 ha) and 851.0 ha was classified to the unsuitable paddy field based on the topographic factors. The user accuracy of paddy field classification was calculated to 83.3 %, and among those, about 60.0 % of total paddy fields were classified from the time-series NDVI before the unsupervised classification. Other land covers were classified as to upland(5255.2 ha), forest (10961.0 ha), residential area and bare land (3309.6 ha), and lake and river (1784.4 ha) from this object-oriented classification.

• Journal of Korean Society of Rural Planning
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• v.8 no.1 s.15
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• pp.60-68
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• 2002

A Modified CREAMS model, CREAMS-PADDY was developed to simulate the hydrology and nutrient transport at an irrigated rice paddy. The hydrology at a paddy was simulated by a daily water balance routine which reflects daily inflow, outflow, and water level changes. The soil erosion was simulated using modified USLE. The nutrient transport for total nitrogen and phosphorus were depicted for various phases of each constitute such as extraction, percolation, mineralization, and plant uptakes. Field monitoring was conducted to investigate the water quality changes at a paddy field at three times a week during the growing season of 1996. The proposed model simulates the water quality of the paddy reasonably well, and is found to be applicable to field conditions.

• The Journal of Korea Robotics Society
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• v.11 no.1
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• pp.1-8
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• 2016

In this paper, we propose a new algorithm of the guidance line extraction for autonomous agricultural robot based on vision camera in paddy field. It is the important process for guidance line extraction which finds the central point or area of rice row. We are trying to use the central region data of crop that the direction of rice leaves have convergence to central area of rice row in order to improve accuracy of the guidance line. The guidance line is extracted from the intersection points of extended virtual lines using the modified robust regression. The extended virtual lines are represented as the extended line from each segmented straight line created on the edges of the rice plants in the image using the Hough transform. We also have verified an accuracy of the proposed algorithm by experiments in the real wet paddy.

• The Journal of Korea Robotics Society
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• v.9 no.3
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• pp.147-153
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• 2014

In this paper, we proposed a new algorithm of the guidance line extraction for autonomous weeding robot based on infrared vision sensor in wet paddy. It is the critical process for guidance line extraction which finds the central point or area of rice row. In order to improve accuracy of the guidance line, we are trying to use the morphological characteristics of rice that the direction of rice leaves have convergence to central area of rice row. Using Hough transform, we were represented the curved leaves as a combination of segmented straight lines on binary image that has been skeletonized and segmented object. A slope of the guidance line was gotten as calculate the average slope of all segmented lines. An initial point of the guidance line was determined that is the maximum pixel value of the accumulated white columns of a binary image which is rotated the slope of guidance line in the opposite direction. We also have verified an accuracy of the proposed algorithm by experiments in the real wet paddy.

• Journal of Applied Biological Chemistry
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• v.56 no.2
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• pp.95-100
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• 2013

Soil microbes are important integral components of soil ecosystem which have significant and diverse role in organic matter decomposition, nitrogen cycling, and nitrogen fixation. In this study an effective denaturing gradient gel electrophoresis (DGGE) method was employed for paddy soil microbial diversity survey. For optimum paddy soil microbial DNA extraction, different methods such as Lysis buffer, skim milk bead, sodium phosphate buffer, Epicentre Soil Master DNA extraction kit (Epicentre, USA) and Mo Bio Power Soil DNA kit (MO BIO, USA) methods were utilized. Among all the method, using Mo Bio Power Soil kit was most effective. DGGE analysis of Bacteria was carried out at 6% polyacylamide gel and 45-60% denaturing gradient in the optimal conditions. Whereas DGGE analysis of fungi was done at 6% polyacrylamide gel and 45-80% denaturing gradient in the optimal conditions. By applying the above assay, it was found that variation within the microbial community of paddy soil occurs by a factor of time. DGGE assay used in this study through for a variety of soil microbial analysis suggests the potential use of this method.

• Journal of Soil and Groundwater Environment
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• v.24 no.6
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• pp.1-8
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• 2019

This study evaluated the relative extraction ratio (RER) of As and heavy metals (Cd, Cu and Pb) in paddy soils using the two types extractant, 0.05 M EDTA and 0.43 M HNO₃. The RER was calculated by dividing the concentrations of metals obtained by 0.05 M EDTA or 0.43 M HNO₃ extraction by those obtained by aqua regia extraction. The RER of 0.43 M HNO₃ was larger than that of 0.05 M EDTA. Correlation analysis indicated there was statistically significant correlation (p<0.001) between the concentration in aqua regia and 0.05 M EDTA or 0.43 M HNO₃. Especially, Cd showed the higher correlation than other metals. Stepwise multiple linear regression analyses indicated soil pH, CEC, organic matter content, and soil texture all influenced the metal extraction rates and bioavailability of the metals.

• Korean Journal of Soil Science and Fertilizer
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• v.28 no.3
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• pp.207-217
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• 1995

Extracting efficiencies of seven extracting solutions currently employed in extracting heavy metals from soils were compared and the functional relationships among them were calculated by regression analysis for Cd, Zn, Cu, and Pb. Extracting solutions employed were 0.1M HCl, 0.1M $HNO_3$, 0.05M EDTA, 0.001M DTPA(pH 7.3), 1M $NH_4OAc$ (pH 7.0), 0.1M $NH_4Ox$, and 4M $HNO_3$ respectively. Soil samples were collected from rice paddy fields near old zinc mining sites and from rice paddy fields near agro-industry complexes. Soils sampled from old zinc mining sites were also extracted using a sequential extraction method. Extraction by 4M $HNO_3$ and sequential extraction were performed on the samples collected both in 1979 and in 1991 to investigate the change in content and in chemical form of heavy metals. Functional relationships among the extracting solutions were highly correlated for Cd and Zn, whereas those for Cu and Pb were not. The predominant chemical form of Cd. Zn, Cu, and Pb in soils from old zinc mining sites was found to be of sulfide/residue form. The exchangeable form of Cd, the organically bound form of Cu, and the carbonate form of Pb were relatively high, while the sulfide/residue form of Zn was very high(> 79%). Although transformation among the extracted forms was not clear during those 12 years, a decrease in total content of Cd, Zn, Cu, and Pb was clearly observed.