• Asian Journal for Public Opinion Research
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• v.9 no.3
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• pp.240-265
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• 2021

Public services need to be evaluated regularly to identify areas that need further improvement. Data collection via Twitter is affordable and timely, so it has the potential to be utilized to evaluate the quality of public service. This study utilizes tweets mentioning three service units of the provincial government of Jakarta and applies both sentiment analysis and topic classification to predict a rating/score of public service quality. The research goal is to examine if the evaluation of public services based on social media data is possible. The findings indicate that the use of Twitter has an advantage in terms of sample size and variety of opinions. Tweets can be translated into scores as well. Nonetheless, the representativeness issue and the predominance of complaint tweets can affect the reliability of the results.

• Korean Journal of Agricultural and Forest Meteorology
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• v.6 no.1
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• pp.1-10
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• 2004

The climate of Minamiakikawa forest in Japan is similar to that of Mt. Jiri in South Korea. There is a large development plan for Minamiakikawa forest, and a change in the species composition is expected. This study was initiated to compare forest transition caused by artificial perturbations in Korea and Japan. Long-term field observations on species composition are reported. We found 98 families, 231 genera, 315 species, 29 varieties, and 8 races, making a total of 352 classification groups of higher plants in the Minamiakikawa forest area. Among them, 11 families, 12 species and 2 varieties are rare or endangered. The study area is dominated by Cryptomerica japonica and Chamaecyparis obtusa. The time and restoration effects on secondary and latent forestation consider the development of the Quercus mongolica community, the Quercus serrata community, and deciduous-broadleaved tree ascension. This indicates that the forest has been restored to Abies firma, Pinus densiflora or Cryptomeria japonica and Fagus japonica, which is considered latent natural forestation of the area in a natural transfer.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.295-305
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• 2021

In this study, we constructed using Random Forest(RF) by selecting the meteorological factors related to the occurrence of frost. As a result, when constructing a classification model for frost occurrence, even if the amount of data set is large, the imbalance in the data set for development of model has been analyzed to have a bad effect on the predictive power of the model. It was found that building a single integrated model by grouping meteorological factors related to frost occurrence by region is more efficient than building each model reflecting high-importance meteorological factors. Based on our results, it is expected that a high-accuracy frost occurrence prediction model will be able to be constructed as further studies meteorological factors for frost prediction.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.3
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• pp.132-140
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• 2006

Forest vegetation classification and species composition of Mt. Ilwol, Yeongyang-Gun, Korea, were studied combining the Braun-Blanquet approach with numerical syntaxonomical analyses (TWINSPAN). Vegetation types and various ecological characteristics such as flora, constancy classes, species ratio of life-form, species diversity and importance value were analyzed. Sixty-eight samples were taken from a $100m^2$ square plot each. Forest communities were identified as two great types: arid landform of mountainside (AM) and humid fertility of piedmont and valley (HP). The former was divided into 3 communities (Rhododendron mucronulatum, Quercus variabilis, Hosta capitat community) and 2groups, and the latter into 3 communities (Tilia amurensis, Vitis coignetiae, Philadelphus schrenckii community) and 2 groups. Vegetation was classified into 8 units. Floristically, the most represented family was Compositae with 26 species. Species with percentage constance degree of more than 61% was Quercus mongolica (72.1%, IV); Carex siderosticat (III) and Fraxinus rhynchophylla (III) were 50.0 and 41.1%, respectively. Life-forms species ratios for trees, subtrees, shrub, vines, grominoids, forbs and ferns were 18.5, 5.7, 14.9, 6.6, 8.8, 42.4 and 3.1%, respectively, PH type showed from $1.70{\pm}0.50\;to\;1.97{\pm}0.57$ and AM type was from $1.40{\pm}0.18\;to\;1.62{\pm}0.20$ in species diversity; therefore, the former type showed higher species diversity than the latter, According to importance value analysis, Pinus densiflora, Quercus mongolica and Q. variabilis were higher in the tree layer, Q. mongolica in the subtree layer, Fraxinus sieboldiana, R. schlippenbachii, etc. in the shrub layer and Carex siderosticta, Carex humilis, etc. in the herb layer.

• Korean Journal of Agricultural and Forest Meteorology
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• v.26 no.3
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• pp.175-190
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• 2024

In order to project changes in climate zones across the Korean Peninsula, the Trewartha's climate classification was applied to the SSP-RCP scenario data with a 1km resolution produced by the National Institute of Agricultural Sciences of the Rural Development Administration. Currently, most of the Korean Peninsula (92.3%) belongs to the temperate climate type (D), whereas only some areas (4.9%), such as Jeju Island, belongs to the subtropical climate type (C). According to SSP-RCP scenarios, the temperature is expected to gradually increase due to the influence of global warming during the 21st century, and the subtropical climate type is expected to expand to 14.1 to 48.6% of the total area of the Korean Peninsula in the far future. On the other hand, the temperate zone, which is currently most dominant on the Korean Peninsula, is expected to shrink by 85.8 to 51.4% in the late 21st century. If carbon dioxide emissions continue at the current rate, the entire Korean Peninsula will likely be dominated by subtropical and temperate regions in the distant future. In particular, the subtropical climate type is expected to dominate most of South Korea in the high-carbon scenario, except for highlands.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.337-345
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• 2023

Estimating the rice heading date is one of the most crucial agricultural tasks related to productivity. However, due to abnormal climates around the world, it is becoming increasingly challenging to estimate the rice heading date. Therefore, a more objective classification method for estimating the rice heading date is needed than the existing methods. This study, we aimed to classify the rice heading stage from various images using a CNN classification model. We collected top-view images taken from a drone and a phenotyping tower, as well as slanted-view images captured with a RGB camera. The collected images underwent preprocessing to prepare them as input data for the CNN model. The CNN architectures employed were ResNet50, InceptionV3, and VGG19, which are commonly used in image classification models. The accuracy of the models all showed an accuracy of 0.98 or higher regardless of each architecture and type of image. We also used Grad-CAM to visually check which features of the image the model looked at and classified. Then verified our model accurately measure the rice heading date in paddy fields. The rice heading date was estimated to be approximately one day apart on average in the four paddy fields. This method suggests that the water head can be estimated automatically and quantitatively when estimating the rice heading date from various paddy field monitoring images.

• The Korean Journal of Applied Statistics
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• v.33 no.3
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• pp.309-320
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• 2020

Bayesian networks, also known as directed acyclic graphs (DAG), are used in many areas of medicine, meteorology, and genetics because relationships between variables can be modeled with graphs and probabilities. In particular, Bayesian network classifiers, which are used to predict discrete data, have recently become a new method of data mining. Bayesian networks can be grouped into different models that depend on structured learning methods. In this study, Bayesian network models are learned with various properties of structure learning. The models are compared to the simplest method, the naïve Bayes model. Classification results are compared by applying learned models to various real data. This study also compares the relationships between variables in the data through graphs that appear in each model.

• Journal of Environmental Science International
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• v.17 no.6
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• pp.591-599
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• 2008

In order to support the development of wind farms in Jejudo, a wind resource database for Jejudo has been established using a meteor-statistical analysis of KIER(Korea Institute of Energy Research) met-mast measurements and KMA(Korea Meteorological Administration) weather data. The analysis included wind statistics, tower shading, an exposure category classification using satellite images, the effect of atmospheric stability on the wind profile exponent, and a correlation matrix of wind speed to gain an understanding of the meteorological correlation between long-term weather observation stations and short-term met-mast measurements. The wind resource database for Jejudo, is to be provided as an add-on to Google $Earth^{TM}$, which is expected to be utilized as a guideline for the selection of an appropriate reference site for long-term correction in the next wind farm development project.

• Journal of Korean Society for Atmospheric Environment
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• v.17 no.4
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• pp.331-345
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• 2001

The increase of carbon monoxide in the ambient air due to the emissions from point sources without control was estimated using three -dimensional numerical models. The target area was Ulsan where one of the largest industrial complexes was located. As a typical example using numerical models for air quality impact analysis of criteria pollutants that will determine whether the air quality standards would be exceeded or not, the following approaches were suggested. They include: (1) investigation of pre-existing atmospheric conditions, (2) identification of major factors causing high concentrations, (3) selection of episode days. (4) preparation of three-dimensional meteorological data, (5) confirmation of agreement between measured and predicted concentrations in the emission conditions of episode days, and (6) estimation of the impact due to changes of the emission conditions. In the present work, daily meteorological conditions for the specific period were classified into four clusters of distinctive features, and the episode days were selected individually from each cluster. Emphasis was placed on the selection of episodes representing meteorological conditions conducive to high concentrations especially for point sources that were sensitive to the wind direction variations.

• Journal of the Korean Institute of Landscape Architecture
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• v.29 no.6
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• pp.27-36
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• 2002

The objective of this study is to improve the quality of the atmospheric environment by incorporating the factors of meteorology and urban climate into the field of urban and environmental planning. To this end, we have conducted a study on CLIMATOP and the mapping of urban climate, which are basic data used to analyze changes in climatic factors and the stagnation and accumulation of air pollutants. In particular, we focused on understanding the formation and movement of cold fresh air and its influx into urban areas by measuring and analyzing climatic factors. As a study result, classification criteria far CLIMATOP and a urban climatic map were made. In addition, we analyzed a digital elevation model, climatic data, and isothermal curves. As a result, we identified the corridor through which cold fresh air moves. We also observed that the temperature of the fluxed cold fresh air increased as land use changed. When the results of this study are applied to urban re-development and re-building projects, which require preliminary environmental assessment and environmental impact assessment, the practice proposed by this study is expected to contribute to the natural purification of air pollution activating the movement of cold fresh air and its influx into urban areas.