• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.81-81
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• 2022

Recently, many studies on big data based smart farming have been conducted. Research to quantify morphological characteristics using image data from various crops in smart farming is underway. Rice is one of the most important food crops in the world. Much research has been done to predict and model rice crop yield production. The number of productive tillers per plant is one of the important agronomic traits associated with the grain yield of rice crop. However, modeling the basic growth characteristics of rice requires accurate data measurements. The existing method of measurement by humans is not only labor intensive but also prone to human error. Therefore, conversion to digital data is necessary to obtain accurate and phenotyping quickly. In this study, we present an image-based method to predict leaf number and evaluate tiller number of individual rice crop using YOLOv5 deep learning network. We performed using various network of the YOLOv5 model and compared them to determine higher prediction accuracy. We ako performed data augmentation, a method we use to complement small datasets. Based on the number of leaves and tiller actually measured in rice crop, the number of leaves predicted by the model from the image data and the existing regression equation were used to evaluate the number of tillers using the image data.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.42-42
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• 2017

Prediction of rice yield during a growing season would be very helpful to magnify rice yield as it also allows better farm practices to maximize yield with greater profit and lesser costs. UAV imagery based automatic detection of rice can be a relevant solution for early prediction of yield. So, we propose an image processing technique to predict rice yield using low altitude UAV images. We proposed $L^*a^*b^*$ color space based image segmentation algorithm. All images were captured using UAV mounted RGB camera. The proposed algorithm was developed to find out rice grain area from the image background. We took RGB image and applied filter to remove noise and converted RGB image to $L^*a^*b^*$ color space. All color information contain in both $a^*$ and $b^*$ layers and by using k-mean clustering classification of these colors were executed. Variation between two colors can be measured and labelling of pixels was completed by cluster index. Image was finally segmented using color. The proposed method showed that rice grain could be segmented and we can recognize rice grains from the UAV images. We can analyze grain areas and by estimating area and volume we could predict rice yield.

• Journal of the Korean Institute of Rural Architecture
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• v.24 no.2
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• pp.1-11
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• 2022

Purpose: The purpose of this study is to analyze image factors of places located in natural and humanistically superior geographical locations. It aims to analyze image recognition and spatiality of scenically historical Sahmyook University, located northeast of Gangneung, through standardization. Method: The analysis method of landscape is composed of data investigation and research, and elements of how students, faculty, and visitors recognize a place's beautiful image will be examined. Result: A phenomenological approach was applied to how the images of beautiful place were set by FGI group meeting, and how such factors affect beautiful place's perception from the user's point of view. When looking at comprehensive ranking of image factors in recognition of beautiful landscapes, factors corresponding to forest landscapes appear at the top rank. In determining factors for its recognition, shared space with natural elements such as water, trees, flowers, etc. has been analyzed to have the biggest influence. Among factors corresponding to urban landscape, 'streets and pedestrian paths' is of medium importance and are recognized for it is artificial structure coexisting with natural elements shared with humans. The image corresponding to 'city area' and 'architecture' was analyzed to have insignificant influence on beautiful places' image recognition for artificial element was prioritized.

• Korean Journal of Remote Sensing
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• v.23 no.1
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• pp.15-20
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• 2007

This study is to apply QuickBird satellite image for the simulation of storm runoff in a small rural watershed. For a $1.05km^2$ watershed located in Goesan-Gun of Chungbuk Province, the land use from the QuickBird image was produced by on-screening digitising after ortho-rectifying using 2 m DEM. For 3 cases of land use, soil and elevation scale (1:5,000, 1:25,000 and 1:50,000), SCS-CN and the watershed physical parameters were prepared for the storm runoff model, HEC-HMS (Hydrologic Modelling System). The model was evaluated for each case and compared the simulated results with couple of selected storm events.

• Journal of muscle and joint health
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• v.24 no.2
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• pp.110-118
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• 2017

Purpose: The purpose of this study was to examine the relationship among perceived health status, body image, and self-esteem of women in rural area. Methods: This cross-sectional descriptive design was used. A total of 90 women in the K rural area completed a questionnaire, including perceived health status, body image, and self-esteem. Data were analyzed with independent t-test, ANOVA, Pearson's correlation coefficients. Results: The mean score of perceived health status was 3.00 out of 5.00, body image was 2.50 out of 4.00, and self-esteem was 2.80 out of 4.00. There were statistically positive correlations between perceived health status and body image (r=.41, p<.001), perceived health status and self-esteem (r=.34, p=.001), and body image and self-esteem (r=.48, p<.001). Conclusion: It is necessary to develop educational and manageable program regarding to body image and self-esteem to improve perceived health status of women in rural area.

• Journal of Korean Society of Rural Planning
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• v.25 no.4
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• pp.13-26
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• 2019

The rural areas in South Korea have changed rapidly in the process of national land development. Rural landscapes have become discoloured, and their attractiveness has decreased as cities have expanded. But the attractiveness or multifunctional values of rural areas has become more important in contemporary society around the world. According to this social demand, the efforts of conserving the rural landscape are of high priority and the recovery of ruralism in the area is required. This study has tried to understand how the public image of ruralism in South Korea has been influenced by the news media. The study retrieved news articles using the web searching portal site from the six keywords, commonly used to refer to ruralism, including 'rural landscape', 'rural community', 'rural tourism', 'rural life', 'rural amenity', and 'rural environment'. News data from the six keywords were also collected respectively from within the year-period of 2004-05, 2007-08, 2012-13, and 2016-17. In the text mining analysis, the nouns with high Degree Centrality were figured out, and the changes by year-period were identified. Then, LDA topic analysis was performed for text datasets of six keywords. As a result, the study found that the news articles gave an informed focus on only a handful of issues such as 'poor rural living condition', 'regional or village improvement projects', 'rural tourism promotion projects', and 'other government support projects'. On the other hand, nouns related to virtues and values in the rural landscape were less shown in news articles. These results have become more apparent in recent years. In the topic analysis, 35 topics were identified. 'village development projects', 'rural tourism', and 'urban-rural exchange projects' were appeared repeatedly in several keywords. Among the topics, there are also topics closely related to ruralism such as 'rural landscape conservation', 'eco-friendly rural areas', 'local amenity resources', 'public interest values of agriculture', and 'rural life and communities'. The study presented an image map showing ruralism in South Korea using a network map between all topics and keywords. At the end of the study, implications for Korean rural area policy and research directions were discussed.

• Journal of Korean Society of Rural Planning
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• v.22 no.3
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• pp.63-70
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• 2016

Due to the Korea's topographic characteristic, there are a lot of marine bridges to connect between islands and mainland. In addition, marine bridges play an important role in a regional landscape. For these reasons, landscape design of bridge is necessary in order to improve beautification of region. So, this studies analyzed image and landscape preference of marine bridges in rural area. The main results were summarized as follows: When rating the image of the background in sea and mountain image, 'stable' and 'natural' were rated highly. When rating the image of the arch bridge in sea and mountain image, 'beautiful', and 'attractive' were rated highly. When rating the image of the cable-stayed bridge in sea and mountain image, 'splendid', and 'attractive' were rated highly. When rating the image of the suspension bridge in sea and mountain image, 'beautiful', and 'splendid' were rated highly. Next, When rating the image of the background in sea and building image, 'stable' and 'natural' were rated highly. When rating the image of the arch bridge in sea and building image, 'beautiful', and 'splendid' were rated highly. When rating the image of the cable-stayed bridge in sea and building image, 'beautiful', and 'attractive' were rated highly. When rating the image of the suspension bridge in sea and building image, 'beautiful', and 'attractive' were rated highly. And, The image of suspension bridges in sea and mountain image is more highly preferred than other image. The background in sea and mountain image is landscape of the lowest preference. In the mountain and sea image, the preference of suspension bridge landscape has the highest rating. In the sea and building image, the preference of arch bridge landscape has the highest rating. In conclusion, the results illustrate that the marine bridge's shape and its background in rural area are important elements of a visual preference. When designing the marine bridge, designer have to choose a proper bridge shape for its background. However, this research's limitation is that this research consider only bridge shape and background to analyze landscape preference of marine bridges. Therefore, further research is necessary to consider various elements.

• Journal of the Korean Institute of Rural Architecture
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• v.18 no.2
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• pp.55-62
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• 2016

The goal of this study is to recreate the identification of landscape image through the Agricultural Architecture in rural area. Most of them are not kept with houses in traditional village and the other structures in garden area of Korea, because they are located in the isolated field or placed near along the local street, are designed as a very heavily designed building, and are covered by different materials and color against village architecture. I researched cattle barns in both Korea and Germany of what they have had images in a distance-view points of local area, so that I might find a suitable image of Barn Architecture with topography of rural areas. I surveyed rural agricultural buildings with different point of views on landscape structure, architectural form and materials, and conditions animal welfare. There are three results from this paper as follows: First, the placement of animal barn in garden area is isolated to village so that it may keep a clean environment of village, which it makes non appropriate to land using and village view. Second, the architectural form makes a different image to the village building, because it has an oversize against houses in village or has no rhythm and dividing form of simple gable barm. Third, the barn architecture is better to consider of eco-friendly materials with animal welfare concept design, when it starts to design the barn in the field.

• Journal of the Korean Institute of Rural Architecture
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• v.18 no.3
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• pp.17-24
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• 2016

The aim of this study is to build an architectural landscaping design ways of vulnerable community in rural area. I surveyed scenery structures, public buildings and single home forms, and fence types of house in twelve villages which have undertaken improving environment of rural community in four provinces. They all have an inferior surroundings to live in rural village, because they were isolated from the city, located on the mountain or island, and made a living under the slate materials of roof. The central government has been driving to reform the conditions with local office, so that they may increase their living qualities and village environment to get to the general level of rural area. There are three results of this study as follows: First, the scenery of the village surveyed has a remarkable views of locality and hierarchy of layers between field and mountain, which is very identified as a typical image of Korean rural topology. Second, the public buildings and single homes and outside wall of houses were personally designed or reformed as a various types like a flat slab style and different architectural structure, because they followed only to keep the architectural code rather than to make a harmony with other traditional style buildings. When they have to remodel it again through SaethulMaul project, they are needed to consider of both architectural code and design guideline for the local landscape design image. Third, to make a different landscape view of each village and improve housing conditions, it should be taken a people participation design way.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.3
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• pp.55-65
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• 2019

Although crack on concrete exists from its early formation, crack requires attention as it affects stiffness of structure and can lead demolition of structure as it grows. Detecting cracks on concrete is needed to take action prior to performance degradation of structure, and deep learning can be utilized for it. In this study, transfer learning, one of the deep learning techniques, was used to detect the crack, as the amount of crack's image data was limited. Pre-trained Inception-v3 was applied as a base model for the transfer learning. Web scrapping was utilized to fetch images of concrete wall with or without crack from web. In the recognition of crack, image post-process including changing size or removing color were applied. In the visualization of crack, source images divided into 30px, 50px or 100px size were used as input data, and different numbers of input data per category were applied for each case. With the results of visualized crack image, false positive and false negative errors were examined. Highest accuracy for the recognizing crack was achieved when the source images were adjusted into 224px size under gray-scale. In visualization, the result using 50 data per category under 100px interval size showed the smallest error. With regard to the false positive error, the best result was obtained using 400 data per category, and regarding to the false negative error, the case using 50 data per category showed the best result.