• Journal of Korean Library and Information Science Society
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• v.34 no.4
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• pp.227-252
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• 2003

This study is to analyze the historical developments of references on cataloging rules. References is named cross reference on The Panizzi' and Jewett' Report and defined at Rules for a Dictionary Catalog by Charles A. Cutter. References is developed to “see reference”, “see-also reference”, “name-title reference”, and “explanatory reference” on AACR2. References have traditionally been regarded as syndetic devices, making it possible to retrieve and connect related works. Conclusionally, it functions as a tool which directly connect all the works related but in different formats of a same author name and a same title name. In online catalogues, it means that the role and function of references have increasingly become extended to be very important.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1449-1463
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• 2020

As recent global warming and climate changes become more serious, the importance of CO2 absorption by forests is increasing to cope with the greenhouse gas issues. According to the UN Framework Convention on Climate Change, it is required to calculate national CO2 absorptions at the local level in a more scientific and rigorous manner. This paper presents the gridded expansion of forest flux observations and mapping of daily CO2 absorption by the forests in Korea using numerical weather prediction data and satellite images. To consider the sensitive daily changes of plant photosynthesis, we built a machine learning model to retrieve the daily RACA (reference amount of CO2 absorption) by referring to the climax forest in Gwangneung and adopted the NIFoS (National Institute of Forest Science) lookup table for the CO2 absorption by forest type and age to produce the daily AACA (actual amount of CO2 absorption) raster data with the spatial variation of the forests in Korea. In the experiment for the 1,095 days between Jan 1, 2013 and Dec 31, 2015, our RACA retrieval model showed high accuracy with a correlation coefficient of 0.948. To achieve the tier 3 daily statistics for AACA, long-term and detailed forest surveying should be combined with the model in the future.