• Title/Summary/Keyword: ecological learning center

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Effectiveness of Environmental Play Teaching Program using the Plant in Neighborhood Learning Gardens (교재원 식물을 활용한 환경놀이 프로그램 개발 및 적용)

  • Choi, Don-Hyung;Yim, Eun-Young;Cho, Seong-Hoa
    • Hwankyungkyoyuk
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    • v.24 no.2
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    • pp.35-53
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    • 2011
  • The purpose of this research is placed on the development and application of environmental play programs for elementary school students their utilizing the neighborhood learning gardens in their districts to find its effectiveness. The research questions drawn to attain the purpose of the research are as follows. Initially, analyze the contents related to the plant appearing in the textbooks of wise life, science and practical arts of the 7th elementary school curriculum. Secondly, develop a plant utilizing environmental play program targeted towards the 4th grade elementary school students with the results of the textbook analysis as the foundation. Third, apply the plant utilizing environmental play program into the classroom to verify its effectiveness. Based on the conclusion of this research, the following is to be proposed. First, the revitalization of regional environmental education utilizing the various surroundings of the region is essential. Also, the current method of education, which is focused on theoretical knowledge, and being operated in most of the schools need to be changed over to diverse environmental education programs that are linked with the region. For this, an internet based database, information sharing and exchange program centralized around the regional environmental education center needs to be prepared. Moreover, since this research had developed an environmental play program utilizing plants that focused on the 4th grade elementary school students to verify its effectiveness, the development for environmental play programs dealing with various themes for each grades is required. Lastly, although this research has verified the effectiveness in the variables of ecological knowledge, environmental susceptibility, environmental attitude, environmental concern, environmental function and responsible environmental behavior amongst the variables of environmental literacy but there requires a succeeding research considering the variables that haven't been included in this research.

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A Study on the Preference for Green Roof Operators of Community Rehabilitation Center (장애인복지관 프로그램 운영자의 옥상녹화 구성요소 선호도)

  • Yun, Ji-Young;Kang, Eun-Jee;Kang, Hyun-Kyung
    • Korean Journal of Environment and Ecology
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    • v.26 no.3
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    • pp.454-462
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    • 2012
  • This study was to research the effective use of green rooftop space, facilities and gardening, targeting members from community rehabilitation centers with disabilities. The three community rehabilitation centers studied were, Namyangju Center located in a rural area, Seoul Center located in a urban area and Siheung Center located in both a rural and urban area. We analyzed the difference in preference on the basis of each local community area. In fact, it indicated that 50% of each center knew about the green rooftop at their facilities and its use as a place for taking walks and conversation. It also showed that there was the high preference for priority objects such as a bench, pergola and trash can. Also the preference for natural visualizations like herbal or ornamental plants. The study showed a high preference to a small vegetable plot, hands on gardening and ecological wetland. It also indicated that there was a high preference for experience in nature programs on the rooftops (28.9 %) versus the rate of horticultural programs (27%). Therefore, it proves that the composition of a green rooftop at a community rehabilitation center should be differentiated so that the green rooftop can be a place not only for resting, but also great for a natural learning experience and gardening therapy for people with disabilities.

Ecotourism Resource Planning for Mulwang Reservoir in Siheung (시흥시 물왕저수지 생태관광 자원화 계획)

  • Lee, Gwan-Gyu
    • Journal of the Korean Institute of Landscape Architecture
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    • v.34 no.4 s.117
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    • pp.37-47
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    • 2006
  • The city of Siheung in the Kyunggi-do Province has various natural resources such as the ocean, mountains, wide farmland, various types of wetlands, streams and rivers. In addition, the city has a big greenbelt, which consists of two-thirds of the area, where development has been regulated. Since the city has a relatively well-preserved natural environment, it offers a great potential for regional development. The purpose of this study is to create an eco-tourism resource plan for the Mulwang reservoir, which offers many opportunities for ecotourism in the city of Siheung. This study includes a literature review for planning elements and suggests a comprehensive plan that includes conservation, eco-restoration, route program and practice program for ecotourism in and around the site. The plan also includes eco-farming, a visitor center, an ecovillage, the chance to experience livestock farming, opportunities to learn about and experience the forest, tracking, eco-learning, an environmental interpretation facility, fishing and aquatic-oriented leisure activities. This study's process and results show possibilities that can be applied to other areas where eco-tourism using natural resources is used for regional development.

A Culture Society and the Ecosystem (문화사회와 에코시스템)

  • Kim, Hwa Im
    • Cross-Cultural Studies
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    • v.26
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    • pp.73-94
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    • 2012
  • In the present context of systemic global crisis, this paper focuses on a sustainable society. Throughout the World there are vast members of the unemployes. A secure job lasting a lifetime has become more and more rare. Nowadays majority of jobs are part-time or temporary. $Andr{\acute{e}}$ Gorz found a solution in a policy of the progessive reduction in labor time. This is the potential which automated production opens up for a culture society. Nevertheless, Gorz's proposal is based on utopion ideals. This paper focuses on a dynamic force for a culture society, especially art, learning and the third sector. Adrienne Goehler underlines that a culture in the broad sense of the word produces economical and social productivity. In this connection Goehler give attention to 'Cultrual Creatives' and the Creative Class. Cultural creatives are comprised of people who have participated in the process of creating a new culture with enlightened creativity. The Creative Class is a class of workers whose job is to create economic growth through innovation. Creativity is important for a sustainable society. Gore and Rifkin both come close to the ecological thinking. Gore claims that ecosystem of nature have a self-organizing capacity. In this context tried to prove this article that ecosystem is closely connected with a creative environment.

Predicting Forest Gross Primary Production Using Machine Learning Algorithms (머신러닝 기법의 산림 총일차생산성 예측 모델 비교)

  • Lee, Bora;Jang, Keunchang;Kim, Eunsook;Kang, Minseok;Chun, Jung-Hwa;Lim, Jong-Hwan
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.21 no.1
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    • pp.29-41
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    • 2019
  • Terrestrial Gross Primary Production (GPP) is the largest global carbon flux, and forest ecosystems are important because of the ability to store much more significant amounts of carbon than other terrestrial ecosystems. There have been several attempts to estimate GPP using mechanism-based models. However, mechanism-based models including biological, chemical, and physical processes are limited due to a lack of flexibility in predicting non-stationary ecological processes, which are caused by a local and global change. Instead mechanism-free methods are strongly recommended to estimate nonlinear dynamics that occur in nature like GPP. Therefore, we used the mechanism-free machine learning techniques to estimate the daily GPP. In this study, support vector machine (SVM), random forest (RF) and artificial neural network (ANN) were used and compared with the traditional multiple linear regression model (LM). MODIS products and meteorological parameters from eddy covariance data were employed to train the machine learning and LM models from 2006 to 2013. GPP prediction models were compared with daily GPP from eddy covariance measurement in a deciduous forest in South Korea in 2014 and 2015. Statistical analysis including correlation coefficient (R), root mean square error (RMSE) and mean squared error (MSE) were used to evaluate the performance of models. In general, the models from machine-learning algorithms (R = 0.85 - 0.93, MSE = 1.00 - 2.05, p < 0.001) showed better performance than linear regression model (R = 0.82 - 0.92, MSE = 1.24 - 2.45, p < 0.001). These results provide insight into high predictability and the possibility of expansion through the use of the mechanism-free machine-learning models and remote sensing for predicting non-stationary ecological processes such as seasonal GPP.

Comparison of the National Park Ecosystem Health Assessment and an Advanced Assessment System (국립공원 생태계 건강성 평가 시스템 개선 연구)

  • Myeong, Hyeon Ho;Kim, Jeong Eun;Kim, Hye Ri;Oh, Jang Geun
    • Ecology and Resilient Infrastructure
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    • v.8 no.2
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    • pp.112-119
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    • 2021
  • In 2012, the National Park Service conducted an ecological health assessment to efficiently preserve and manage the ecosystem. The need for improving pre-existing management indicators was recognized from the revised Natural Park Act because, while the indicators of the existing evaluation system focused on endangered species, ecosystem disturbance, diversity, water quality (BOD, DO), and habitat fragmentation, they did not reflect the lack of indicators for marine ecological assessment, policy changes, and the time demands. The evaluation results comprised a five-point grading system, which made the analysis of immediate changes, difficult. Therefore, the benthic pollution index (BPI) and habitat restoration indicators were added to improve the evaluation system. The National Park was assessed using 10 classifications, however, only four classifications were evaluated. The ratings were divided into five states, and ten classes were presented as pictograms. The assessment results showed a similar trend as the indicators were improved, increasing from level 3 to level 5. However, the results of the Wolaksan National Park after improvement in the indicators were lower than that before the improvement, whereas, for the Juwangsan National Park, it was higher. This study aims at contributing to the scientific and systematic management of the national park ecosystem by improving the ecological health assessment system.

Development of Artificial Neural Network Model for Predicting the Optimal Setback Application of the Heating Systems (난방시스템 최적 셋백온도 적용시점 예측을 위한 인공신경망모델 개발)

  • Baik, Yong Kyu;Yoon, younju;Moon, Jin Woo
    • KIEAE Journal
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    • v.16 no.3
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    • pp.89-94
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    • 2016
  • Purpose: This study aimed at developing an artificial neural network (ANN) model to predict the optimal start moment of the setback temperature during the normal occupied period of a building. Method: For achieving this objective, three major steps were conducted: the development of an initial ANN model, optimization of the initial model, and performance tests of the optimized model. The development and performance testing of the ANN model were conducted through numerical simulation methods using transient systems simulation (TRNSYS) and matrix laboratory (MATLAB) software. Result: The results analysis in the development and test processes revealed that the indoor temperature, outdoor temperature, and temperature difference from the setback temperature presented strong relationship with the optimal start moment of the setback temperature; thus, these variables were used as input neurons in the ANN model. The optimal values for the number of hidden layers, number of hidden neurons, learning rate, and moment were found to be 4, 9, 0.6, and 0.9, respectively, and these values were applied to the optimized ANN model. The optimized model proved its prediction accuracy with the very storing statistical correlation between the predicted values from the ANN model and the simulated values in the TRNSYS model. Thus, the optimized model showed its potential to be applied in the control algorithm.

Application of Machine Learning Algorithm and Remote-sensed Data to Estimate Forest Gross Primary Production at Multi-sites Level (산림 총일차생산량 예측의 공간적 확장을 위한 인공위성 자료와 기계학습 알고리즘의 활용)

  • Lee, Bora;Kim, Eunsook;Lim, Jong-Hwan;Kang, Minseok;Kim, Joon
    • Korean Journal of Remote Sensing
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    • v.35 no.6_2
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    • pp.1117-1132
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    • 2019
  • Forest covers 30% of the Earth's land area and plays an important role in global carbon flux through its ability to store much greater amounts of carbon than other terrestrial ecosystems. The Gross Primary Production (GPP) represents the productivity of forest ecosystems according to climate change and its effect on the phenology, health, and carbon cycle. In this study, we estimated the daily GPP for a forest ecosystem using remote-sensed data from Moderate Resolution Imaging Spectroradiometer (MODIS) and machine learning algorithms Support Vector Machine (SVM). MODIS products were employed to train the SVM model from 75% to 80% data of the total study period and validated using eddy covariance measurement (EC) data at the six flux tower sites. We also compare the GPP derived from EC and MODIS (MYD17). The MODIS products made use of two data sets: one for Processed MODIS that included calculated by combined products (e.g., Vapor Pressure Deficit), another one for Unprocessed MODIS that used MODIS products without any combined calculation. Statistical analyses, including Pearson correlation coefficient (R), mean squared error (MSE), and root mean square error (RMSE) were used to evaluate the outcomes of the model. In general, the SVM model trained by the Unprocessed MODIS (R = 0.77 - 0.94, p < 0.001) derived from the multi-sites outperformed those trained at a single-site (R = 0.75 - 0.95, p < 0.001). These results show better performance trained by the data including various events and suggest the possibility of using remote-sensed data without complex processes to estimate GPP such as non-stationary ecological processes.

Geo-educational Values of the Jebudo Geosite in the Hwaseong Geopark, Korea (화성 지질공원 제부도 지질명소의 지질교육적 가치)

  • Ha, Sujin;Chae, Yong-Un;Kang, Hee-Cheol;Kim, Jong-Sun;Park, Jeong-Woong;Shin, Seungwon;Lim, Hyoun Soo;Cho, Hyeongseong
    • Journal of the Korean earth science society
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    • v.42 no.3
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    • pp.311-324
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    • 2021
  • Recently, ten geosites have been considered in Hwaseong for endorsement as national geoparks, including the Jebudo, Gojeongri Dinosaur Egg Fossils, and Ueumdo geosites. The Jebudo geosite in the southern part of the Seoul metropolitan area has great potential for development as a new geoscience educational site because it has geological, geographical (landscape), and ecological significance. In this study, we described the geological characteristics through field surveys in the Jebudo geosite. We evaluated its potential as a geo-education site based on comparative analysis with other geosites in Hwaseong Geopark. In addition, we reviewed the practical effect of field education at geosites on the essential concepts and critical competence-oriented education emphasized in the current 2015 revised science curriculum. The Jebudo Geosite is geologically diverse, with various metamorphic rocks belonging to the Precambrian Seosan Group, such as quartzite, schist, and phyllite. Various geological structures, such as clastic dikes, faults, joints, foliation, and schistosity have also been recorded. Moreover, coastal geological features have been observed, including depositional landforms (gravel and sand beaches, dunes, and mudflats), sedimentary structures (ripples), erosional landforms (sea cliffs, sea caves, and sea stacks), and sea parting. The Jebudo geosite has considerable value as a new geo-education site with geological and geomorphological distinction from the Gojeongri Dinosaur Egg Fossils and Ueumdo geosites. The Jebudo geosite also has opportunities for geo-education and geo-tourism, such as mudflat experiences and infrastructures, such as coastal trails and viewing points. This geosite can help develop diverse geo-education programs that improve key competencies in the science curriculum, such as critical thinking, inquiry, and problem-solving. Furthermore, by conducting optimized geo-education focused on the characteristics of each geosite, the following can be established: (1) the expansion of learning space from school to geopark, (2) the improvement of understanding of specific content elements and linkage between essential concepts, and (3) the extension of the education scope throughout the earth system. There will be positive impacts on communication, participation, and lifelong learning skills through geopark education.

Overview and Prospective of Satellite Chlorophyll-a Concentration Retrieval Algorithms Suitable for Coastal Turbid Sea Waters (연안 혼탁 해수에 적합한 위성 클로로필-a 농도 산출 알고리즘 개관과 전망)

  • Park, Ji-Eun;Park, Kyung-Ae;Lee, Ji-Hyun
    • Journal of the Korean earth science society
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    • v.42 no.3
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    • pp.247-263
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    • 2021
  • Climate change has been accelerating in coastal waters recently; therefore, the importance of coastal environmental monitoring is also increasing. Chlorophyll-a concentration, an important marine variable, in the surface layer of the global ocean has been retrieved for decades through various ocean color satellites and utilized in various research fields. However, the commonly used chlorophyll-a concentration algorithm is only suitable for application in clear water and cannot be applied to turbid waters because significant errors are caused by differences in their distinct components and optical properties. In addition, designing a standard algorithm for coastal waters is difficult because of differences in various optical characteristics depending on the coastal area. To overcome this problem, various algorithms have been developed and used considering the components and the variations in the optical properties of coastal waters with high turbidity. Chlorophyll-a concentration retrieval algorithms can be categorized into empirical algorithms, semi-analytic algorithms, and machine learning algorithms. These algorithms mainly use the blue-green band ratio based on the reflective spectrum of sea water as the basic form. In constrast, algorithms developed for turbid water utilizes the green-red band ratio, the red-near-infrared band ratio, and the inherent optical properties to compensate for the effect of dissolved organisms and suspended sediments in coastal area. Reliable retrieval of satellite chlorophyll-a concentration from turbid waters is essential for monitoring the coastal environment and understanding changes in the marine ecosystem. Therefore, this study summarizes the pre-existing algorithms that have been utilized for monitoring turbid Case 2 water and presents the problems associated with the mornitoring and study of seas around the Korean Peninsula. We also summarize the prospective for future ocean color satellites, which can yield more accurate and diverse results regarding the ecological environment with the development of multi-spectral and hyperspectral sensors.