The purpose of the study is to develop a educational data in order for students to perform geologic field survey effectively by themselves. A area around the Duta Mountain is selected. which is located at the southeastern part of Eumsung sedimentary basin because various rock types and geologic structures are well shown in this area and also it is convenient to reach there. Thirteen stops for observation are chosen m a route f3r exercising field geologic investigation. Data for field research are given and described in detail from each stop for observation. To do this, students make their own route map using general or digital geographic map and aerial photo is added to know relationship between large-scale structure and different rock types regionally. Moreover, it is designed to minimize conflict factors that may be experienced from the real field survey by showing outcrop photographs and polarizing photomicrographs of rut samples related to each stop and geologic structures. The attitude of students is investigated with the data of field geologic survey for students of an Earth Science class in the College of Education in Chungbuk National University. The results indicate that the educational data for geologic field survey brought positive changes that greatly help students perform field survey in definitive side, especially formation of absolute concepts on earth science.
Journal of the Economic Geographical Society of Korea
/
v.23
no.1
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pp.35-55
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2020
The support policy of Micro manufacturers clusters should reflect the regional characteristics of Micro manufacturers clusters, but only similar policies are proposed based on the normal collection of information from related companies. Since the regional characteristics of Micro manufacturers clusters are not understood, they are not reflected in the support policy. Therefore, this study analyzed the characteristics of Micro manufacturers clusters as the formation factors of localization, networking/embeddedness, and innovation synergy/collective learning which are the characteristics of clusters, and applied the development stage based on the analyzed formation factors. Since regional characteristics may be different in the same industry, Micro manufacturers clusters in Changsin and Jangwi, which are representative clusters of apparel sewing industry in Seoul, were compared and studied in terms of regional characteristics and developmental stages. As a result of analyzing the characteristics of Apparel Sewing Micro manufacturers clusters, clusters of peers were found to be higher in Changsin than in Jangwi in localization. However, in the synergy and group learning, the Changsin area was mainly centered on designers and the Jangwi area was centered on Micro manufacturers, the Changsin area was active while the Jangwi area was passive in participating in fairs and seminars, and in sample and production. As a result of examining the two formation factors, the development stage of Micro manufacturers clusters in the two regions is progressing beyond the industrial district in the case of Micro manufacturers clusters in Changsin apparel sewing, and the Micro manufacturers clusters in the Jangwi apparel sewing are analyzed to stay in the industrial district. Innovative and long-established garment sewing clusters suggest that the government's support policy needs to reflect the characteristics and development stages of the two regions for sustainable growth.
This paper describes the development of an inquiry-based fieldwork program based on Yangdong village where students explore the ways that it can develop in a sustainable way. Important considerations in an inquiry-based fieldwork design include what the key inquiry questions should be, the geographical issues of fieldwork location, the potential roles of mobile technologies, design of learning activities and a final product, and the roles of a teacher. Student fieldwork activities, including mapping land-use changes at the building level, detecting what should be changed or remain the same, and conducting interview with residents to examine their perceptions of overall tourism impacts, are supported by mobile technologies (i.e., the Collector for ArcGIS and the Google Forms). Twenty one high school students participated in a field test of the program in February 2016, which allowed authors to evaluate the program. Students' pre-, in-, and post-fieldwork activities were observed and the data and final products which they gathered and producted were analyzed. The post-program survey indicated that the students deepened and expanded their understanding of Yangdong village and expressed their satisfaction with the program in general. Incorporating mobile technologies into inquiry-based geographical fieldwork can help students involved in collaborative problem solving and creative activities in real world settings and create a shareable multimodal product combining maps, photo, and text.
Film literacy comprises the process of producing a new creation through understanding the elements that make up a film, the content of a film, and a critical and creative thinking process. Film literacy is employed in fields such as composition, science, social studies, and geography, and, additionally, it is used to cultivate humanities literacy and critical thinking skills. Yet despite the large proportion of the film script in the movie, it is not easy to find literacy education cases that use film English as a teaching method. Film English is a practical and authentic material, and is suitable as an English learning material in an EFL context like Korea. However, the approach of using films to teach and learn differs according to the content and genre of a film. Thus, the teacher may have a difficult time organizing and preparing for class. This study suggests six class activities that can be commonly applied to English classes using films based on the areas of critical, cultural, and creative (3Cs) activities. Four hundred and five college students taking Movie English classes participated in the present study and frequency analysis was conducted to find out their preferences through a questionnaire survey. The results from conducting class activities in university liberal arts classes suggest that the most preferred activities of students are related to cultural, critical, and creative, in that order. Creative activities that are far beyond English instruction utilizing various digital tools or providing additional reading materials can be a burden on learners.
Water resources which is formed of surface and groundwater, are considered as one of the pivotal natural resources worldwide. Since last century, the rapid population growth as well as accelerated industrialization and explosive urbanization lead to boost demand for groundwater for domestic, industrial and agricultural use. In fact, better management of groundwater can play crucial role in sustainable development; therefore, determining accurate location of groundwater based groundwater potential mapping is indispensable. In recent years, integration of machine learning techniques, Geographical Information System (GIS) and Remote Sensing (RS) are popular and effective methods employed for groundwater potential mapping. For determining the status of the integrated approach, a systematic review of 94 directly relevant papers were carried out over the six previous years (2015-2020). According to the literature review, the number of studies published annually increased rapidly over time. The total study area spanned 15 countries, and 85.1% of studies focused on Iran, India, China, South Korea, and Iraq. 20 variables were found to be frequently involved in groundwater potential investigations, of which 9 factors are almost always present namely slope, lithology (geology), land use/land cover (LU/LC), drainage/river density, altitude (elevation), topographic wetness index (TWI), distance from river, rainfall, and aspect. The data integration was carried random forest, support vector machine and boost regression tree among the machine learning techniques. Our study shows that for optimal results, groundwater mapping must be used as a tool to complement field work, rather than a low-cost substitute. Consequently, more study should be conducted to enhance the generalization and precision of groundwater potential map.
Remotely sensed data have been used in various fields, such as disasters, agriculture, urban planning, and the military. Recently, the demand for the multitemporal dataset with the high-spatial-resolution has increased. This manuscript proposed an automatic image matching algorithm using a deep learning technique to utilize a multitemporal remotely sensed dataset. The proposed deep learning model was based on High Resolution Net (HRNet), widely used in image segmentation. In this manuscript, denseblock was added to calculate the correlation map between images effectively and to increase learning efficiency. The training of the proposed model was performed using the multitemporal orthophotos of the National Geographic Information Institute (NGII). In order to evaluate the performance of image matching using a deep learning model, a comparative evaluation was performed. As a result of the experiment, the average horizontal error of the proposed algorithm based on 80% of the image matching rate was 3 pixels. At the same time, that of the Zero Normalized Cross-Correlation (ZNCC) was 25 pixels. In particular, it was confirmed that the proposed method is effective even in mountainous and farmland areas where the image changes according to vegetation growth. Therefore, it is expected that the proposed deep learning algorithm can perform relative image registration and image matching of a multitemporal remote sensed dataset.
Journal of the Korean Association of Geographic Information Studies
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v.18
no.4
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pp.81-99
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2015
The acceleration of global warming has required better understanding of carbon cycles over local and regional areas such as the Korean peninsula. Since forests serve as a carbon sink, which stores a large amount of terrestrial carbon, there has been a demand to accurately estimate such forest carbon sequestration. In Korea, the National Forest Inventory(NFI) has been used to estimate the forest carbon stocks based on the amount of growing stocks per hectare measured at sampled location. However, as such data are based on point(i.e., plot) measurements, it is difficult to identify spatial distribution of forest carbon stocks. This study focuses on urban areas, which have limited number of NFI samples and have shown rapid land cover change, to estimate grid-based forest carbon stocks based on UNFCCC Approach 3 and Tier 3. Land cover change and forest carbon stocks were estimated using Landsat 5 TM data acquired in 1991, 1992, 2010, and 2011, high resolution airborne images, and the 3rd, 5th~6th NFI data. Machine learning techniques(i.e., random forest and support vector machines/regression) were used for land cover change classification and forest carbon stock estimation. Forest carbon stocks were estimated using reflectance, band ratios, vegetation indices, and topographical indices. Results showed that 33.23tonC/ha of carbon was sequestrated on the unchanged forest areas between 1991 and 2010, while 36.83 tonC/ha of carbon was sequestrated on the areas changed from other land-use types to forests. A total of 7.35 tonC/ha of carbon was released on the areas changed from forests to other land-use types. This study was a good chance to understand the quantitative forest carbon stock change according to the land cover change. Moreover the result of this study can contribute to the effective forest management.
Journal of the Korean Association of Geographic Information Studies
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v.23
no.3
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pp.120-131
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2020
Water body detection using remote sensing based on machine interpretation of satellite image is efficient for managing water resource, drought and flood monitoring. In this study, water body detection with SAR satellite image based on machine learning was performed. However, non water body area can be misclassified to water body because of shadow effect or objects that have similar scattering characteristic comparing to water body, such as roads. To decrease misclassifying, 8 combination of morphology open filtered band, DEM band, curvature band and Cosmo-SkyMed SAR satellite image band about Mokpo region were trained to semantic segmentation machine learning models, respectively. For 8 case of machine learning models, global accuracy that is final test result was computed. Furthermore, concordance rate between landcover data of Mokpo region was calculated. In conclusion, combination of SAR satellite image, morphology open filtered band, DEM band and curvature band showed best result in global accuracy and concordance rate with landcover data. In that case, global accuracy was 95.07% and concordance rate with landcover data was 89.93%.
Journal of the Korean association of regional geographers
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v.9
no.4
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pp.505-518
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2003
The purpose of this paper is to review Post-Fordist urban economic theories that have tackled the recent changes of urban economies in large cities in the world since 1980s, so that we can conceptualise the changes of urban economies in Korean cities. In the perspective of the Post-Fordist urban economic theories, the recent changes of urban economies in the world are deeply related to the transformation of capitalist world economic system from Fordism to Post-Fordism. To see these changes which can be called as the new urbanization process in the economic aspect, we will focus especially such theories as new industrial space (district) theory based on the flexible specialization paradigm, informational city theory based on the information and communication mode paradigm, and cluster and regional innovation theory based on the institution and network paradigm. Also we will consider the social polarization process and dual city phenomena that have been observed for the most part of big cities in the world.
Journal of the Korean Association of Geographic Information Studies
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v.9
no.2
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pp.194-205
/
2006
The purpose of this study is to develop a pedestrian multi-agent model and simulation system using multi-agent theory, which may be utilized as a planning support system for building a comfort and safe environment of pedestrian street. Differing from existing pedestrian models, however, every single pedestrian was regarded as an individual agent in the model. Multiple agents like multiple pedestrians in the street then maintain their own characteristics and respond to surrounding environment. In addition their moving behavior are made by their own decision rules that they have or had acquired through the interactive communications or learning between agents like real world. After verifying the model validation, as the $R^2$ between the predicted value and observed value was up to 0.781, the developed model was applied to Gazwa district within Gyeongsang university village. The simulation system was developed by Flash MX action scripts and the physical environment of the streets was configured with the digital map and ArcGis within computer virtual space. The attribute data of buildings such as type and size of commercial business were collected through the field survey and combined with physical features. Then the effect of the variation of building attractiveness and the occurrence of street events to pedestrian environment were simulated. Through the experiments this study could make suggestions to improve pedestrian environment.
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