• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1053-1066
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• 2020

Sulfur dioxide (SO₂) is primarily released through industrial, residential, and transportation activities, and creates secondary air pollutants through chemical reactions in the atmosphere. Long-term exposure to SO₂ can result in a negative effect on the human body causing respiratory or cardiovascular disease, which makes the effective and continuous monitoring of SO₂ crucial. In South Korea, SO₂ monitoring at ground stations has been performed, but this does not provide spatially continuous information of SO₂ concentrations. Thus, this research estimated spatially continuous ground-level SO₂ concentrations at 1 km resolution over South Korea through the synergistic use of satellite data and numerical models. A stacking ensemble approach, fusing multiple machine learning algorithms at two levels (i.e., base and meta), was adopted for ground-level SO₂ estimation using data from January 2015 to April 2019. Random forest and extreme gradient boosting were used as based models and multiple linear regression was adopted for the meta-model. The cross-validation results showed that the meta-model produced the improved performance by 25% compared to the base models, resulting in the correlation coefficient of 0.48 and root-mean-square-error of 0.0032 ppm. In addition, the temporal transferability of the approach was evaluated for one-year data which were not used in the model development. The spatial distribution of ground-level SO₂ concentrations based on the proposed model agreed with the general seasonality of SO₂ and the temporal patterns of emission sources.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.250-260
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• 2019

This study assessed clove germination, shoot growth, photosynthesis and bulb development of southern-type garlic (Allium sativum L.) in a temperature gradient tunnel (TGT), to examine the impacts of increases in temperature on the growth of garlic and find a way to minimize them. The temperatures in the middle and outlet of the TGT were 3.2℃ and 5.8℃ higher, respectively, than the ambient temperature at the tunnel inlet. The germination of garlic cloves was late at temperatures of ambient+3℃ (in the middle of the TGT) and ambient+6℃ (at the outlet) than at ambient temperature (at the inlet). However, bolting and the timing of maximum leaf number per plant were faster at ambient+3℃ or +6℃ than at ambient temperature. Shoot growth was generally greater at ambient temperature. Bulb growth did not significantly differ according to cultivation temperatures, but fresh and dry weights were slightly higher at ambient temperature and ambient+3℃ in the late growth stage. The photosynthesis rate (A), stomatal conductance (g_s), and transpiration rate (E) were higher at ambient+3℃ than at ambient temperature. Furthermore, at ambient+3℃, the net photosynthetic rate (A_max) was high, while the dark respiration rate (R_d) was low. At ambient temperature and ambient+3℃, bulb development was healthier, resulting in better productivity and more commercial bulbs, while at ambient+6℃, the bulbs were small and secondary cloves developed, resulting in low commercial value. Therefore, at elevated temperatures caused by global warming, it is necessary to meet the low-temperature requirements before clove sowing, or to delay the sowing time, to improve germination rate and increase yield. The harvest should also be advanced to escape high-temperature stress in the bulb development stage.

• Korean Journal of Agricultural and Forest Meteorology
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• v.1 no.1
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• pp.1-11
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• 1999

Rice yield and primary productivity (NPP) are dependent upon the variability of climate and soil. The variability and regionality of the rice yield and net primary productivity were evaluated with the meteorological data collected from Korea Meteorology Administration and the actual rice yield data from the Ministration of Agriculture and Forestry, Korea. The estimated NPP using the three models, dependent upon temperature(NPP-T), precipitation(NPP-P) and net radiation(NPP-R), ranged from 10.87 to 17.52 Mg ha$^{-1}$ with average of 14.69 Mg ha$^{-1}$ in the South Korea and was ranged 6.47 to 15.58 Mg ha$^{-1}$ with average of 12.59 Mg ha$^{-1}$ in the North Korea. The primary limiting factor of NPP in Korea was net radiation, and the secondary limiting factor was temperature. Spectral analysis on the long term change in air temperature in July and August showed periodicity. The short periodicity was 3 to 7 years and the long periodicity was 15 to 43 years. The coefficient of variances, CV, of the rice yield from 1989 to 1998 ranged 3.23 percents to 12.37 percents which were lower than past decades. The CV's in Kangwon and Kyeongbuk were high while that in Chonbuk was the lowest. The prediction model based on th e yield index and yield response to temperature obtain ed from the field crop situation showed reasonable results and thus the spatial distributions of rice yield and predicted yield could be expressed in the maps. The predicted yields was well fitted with the actual yield except Kyungbuk. For better prediction, modification should be made considering radiation factor in further development.

• Korean Journal of Agricultural and Forest Meteorology
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• v.4 no.3
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• pp.151-158
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• 2002

In Korean high yielding varieties developed by crosses between indica and japonica rice, the most limiting factor for yield increase may be attributed to the less number of tillers per unit area. The goal of this study is to find out the effect of the environmental factors as well as cultivation practice on the development and increase of tillers of Dasanbyeo, the high yielding indica / japonica hybrid cultivar. The effect of temperature was examined with 3 different light intensity, 220,600, and 1220 $\mu$㏖/s/$m^2$, respectively. For all the experiments, the leading japonica variety in Korea, Hwaseongbyeo, was used fur the check cultivar for the comparison with Dasanbyeo. The increase of the tillers was more prominent in Dasanbyeo than in Hwaseongbyeo at 220 $\mu$㏖/s/$m^2$ of light intensity, while the similar increase of tiller no. was found at 600 $\mu$㏖/s/$m^2$ of light intensity treatment. However, Hwaseongbyeo showed more rapid increase of tiller at 1220 $\mu$㏖/s/$m^2$ of light intensity. The mean number of the primary tiller ranged 5 to 7 in Dasanbyeo, and 2 to 7 in Hwaseongbyeo, showing greater variation in the latter case. However, the secondary tiller number ranged from 2 to 13 for the former, and 2 to 12 for the latter. The earliest initiation of tiller node of Dasanbyeo and Hwaseongbyeo was observed on 6 and 4 days after transplanting(DAT), respectively, at 600 $\mu$㏖/s/$m^2$ of light intensity, while 10, and 7 DAT, respectively, at 1,220 $\mu$㏖/s/$m^2$. No cultivar difference was observed at 600 $\mu$㏖/s/$m^2$ with the 18 DAT. The ratio of effective tiller was lower in Dasanbyeo, ranging from 47 to 55% than in Hwaseongbyeo, ranging from 72 to 100%.

• Korean Journal of Agricultural and Forest Meteorology
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• v.11 no.4
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• pp.162-173
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• 2009

Information on the expected geographical shift of suitable zones for growing crops under future climate is a starting point of adaptation planning in agriculture and is attracting much concern from policy makers as well as researchers. Few practical schemes have been developed, however, because of the difficulty in implementing the site-selection concept at an analytical level. In this study, we suggest site-selection criteria for quality Fuji apple production and integrate geospatial data and information available in public domains (e.g., digital elevation model, digital soil maps, digital climate maps, and predictive models for agroclimate and fruit quality) to implement this concept on a GIS platform. Primary criterion for selecting sites suitable for Fuji apple production includes land cover, topography, and soil texture. When the primary criterion is satisfied, climatic conditions such as the length of frost free season, freezing risk during the overwintering period, and the late frost risk in spring are tested as the secondary criterion. Finally, the third criterion checks for fruit quality such as color and shape. Land attributes related to these factors in each criterion were implemented in ArcGIS environment as relevant raster layers for spatial analysis, and retrieval procedures were automated by writing programs compatible with ArcGIS. This scheme was applied to the A1B projected climates for South Korea in the future normal years (2011-2040, 2041-2070, and 2071-2100) as well as the current climate condition observed in 1971-2000 for selecting the sites suitable for quality Fuji apple production in each period. Results showed that this scheme can figure out the geographical shift of suitable zones at landscape scales as well as the latitudinal shift of northern limit for cultivation at national or regional scales.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2014.10a
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• pp.1-24
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• 2014

This study uses geo-spatial crop modeling to quantify the biophysical impact of weather extremes. More specifically, the study analyzes the weather extreme which affected maize production in the USA in 2012; it also estimates the effect of a similar weather extreme in 2050, using future climate scenarios. The secondary impact of the weather extreme on food security in the developing world is also assessed using trend analysis. Many studies have reported on the significant reduction in maize production in the USA due to the extreme weather event (combined heat wave and drought) that occurred in 2012. However, most of these studies focused on yield and did not assess the potential effect of weather extremes on food prices and security. The overall goal of this study was to use geo-spatial crop modeling and trend analysis to quantify the impact of weather extremes on both yield and, followed food security in the developing world. We used historical weather data for severe extreme events that have occurred in the USA. The data were obtained from the National Climatic Data Center (NCDC) of the National Oceanic and Atmospheric Administration (NOAA). In addition we used five climate scenarios: the baseline climate which is typical of the late 20th century (2000s) and four future climate scenarios which involve a combination of two emission scenarios (A1B and B1) and two global circulation models (CSIRO-Mk3.0 and MIROC 3.2). DSSAT 4.5 was combined with GRASS GIS for geo-spatial crop modeling. Simulated maize grain yield across all affected regions in the USA indicates that average grain yield across the USA Corn Belt would decrease by 29% when the weather extremes occur using the baseline climate. If the weather extreme were to occur under the A1B emission scenario in the 2050s, average grain yields would decrease by 38% and 57%, under the CSIRO-Mk3.0 and MIROC 3.2 global climate models, respectively. The weather extremes that occurred in the USA in 2012 resulted in a sharp increase in the world maize price. In addition, it likely played a role in the reduction in world maize consumption and trade in 2012/13, compared to 2011/12. The most vulnerable countries to the weather extremes are poor countries with high maize import dependency ratios including those countries in the Caribbean, northern Africa and western Asia. Other vulnerable countries include low-income countries with low import dependency ratios but which cannot afford highly-priced maize. The study also highlighted the pathways through which a weather extreme would affect food security, were it to occur in 2050 under climate change. Some of the policies which could help vulnerable countries counter the negative effects of weather extremes consist of social protection and safety net programs. Medium- to long-term adaptation strategies include increasing world food reserves to a level where they can be used to cover the production losses brought by weather extremes.

• Korean Journal of Ecology and Environment
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• v.52 no.3
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• pp.245-265
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• 2019

Biotope, which represents the characteristic habitats of living organisms, need to be identified as essential for the efficient creation and sustainable management of urban ecosystems. This study was carried out to provide the basic information for ecological urban planning by analyzing types and attributes of the biotop established throughout the whole area of the Pohang city, a representative industrial city in Korea. The biotop established in Pohang city is composed of 12 types including forests (coniferous, deciduous, and mixed forests), agricultural fields (rice paddy and upland field), green facilities, river, reservoir, bare ground, residential area, public facilities, commercial area, industrial area, roads, and schools. As a result of analyzing the properties according to biotop types, industrial, commercial and residential areas, which represent urban areas, was dominated by introduced vegetation. Moreover the introduced vegetation is usually composed of exotic plants or modified forms for landscape architecture and horticulture rather than native plants, which reflects ecological property of both region and site. As the distance from the urban center increases, the agricultural field showed a form of typical farmland, whereas the closer it is, the more form of greenhouse farming. Natural green spaces were divided into riparian vegetation established along the stream and forest vegetation. Forest vegetation is consisted of secondary forests (seven communities) and plantations (three communities). The urban landscape of Pohang city is dominated by the industrial area. Among them, the steel industry, which occurs large amounts of heat pollution and carbon dioxide, occupies a large proportion. On the other hand, green space is very insufficient in quantity and inferior in quality. This study proposed several restoration plans and further, a green network, which ties the existing green spaces and the green space to be restored as a strategy to improve the environmental quality in this area.

• Korean Journal of Heritage: History & Science
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• v.53 no.4
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• pp.188-197
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• 2020

Termites play an important role as decomposers of the forest ecosystem, while simultaneously causing enormous damage to wooden structures. Currently, two species of subterranean termites have been reported in Korea, and termite damage to historical wooden buildings is occurring nationwide due to climate change, forest fertility, and the locational characteristics of historical wooden buildings. Subterranean termites make their nests underground or inside timber. Termites move underground and access wooden structures through the lower parts of the buildings, adjacent to the ground. Once termites attack the wooden structures, it not only spoils the authenticity of cultural heritage structure, but also hampers structural stability due to the decrease in the strength of the material. Therefore, it is important to prevent termite damage before it occurs. Chemical treatments are mainly used in Korea to control and prevent the damage. In foreign countries, physical barriers are also used to prevent entry to wooden buildings, along with chemical treatments. Physical barriers involve installing nets or particles that termites cannot pass through in the lower part of the building, around the pipes, and between the edges of the building or exterior walls and interior materials. Advantages of a physical barrier are that it is an eco-friendly method, maintains long-term effect after installation, and does not require the use of chemical treatments. Prior to applying physical barriers, studies into the characteristics of termite species must be undertaken. In this study, we evaluated the minimum passage size that each caste of Reticulitermes speratus kyushuensis can move through. We found that workers, soldiers, and secondary reproductive termites were able to pass through diameters of 0.7mm, 0.9mm, and 1.1mm respectively. Head height of termites was an important factor in determining the minimum passing size. Results from the current study will be used as a basis to design the mesh size for physical barriers to prevent damage by termites in historical wooden buildings in Korea.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.3
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• pp.145-154
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• 2022

Due to abnormal weather conditions caused by climate change, natural disasters and damages are gradually increasing around the world. Global climate change as accompanied by warming is projected to exert adverse impact on production of potato, which is known as cool season crop. Even though, role of potato as a food security crop is expected to increase in the future, the climate change impacts on potato and adaption strategies are not sufficiently established. Therefore, this study was conducted to analyze the damage pattern of potatoes due to high temperature treatment and to evaluate the response of cultivars. T he high temperature treatment (35~38℃) induced heat stress by sealing the plastic house in midsummer (July), and the quantity and quality characteristics of potatoes were compared with the control group. T otal yield, marketable yield (>80 g) and the number of tubers per plants decreased when heat treatment was performed, and statistical significance was evident. In the heat treatment, 'Jayoung' cultivar suffered a high heat damage with an 84% reduction in yield of >80 g compared to the control group. However, in Jopung cultivar, the decrease was relatively small at 26%. Tuber physiological disturbances (Secondary growth, Tuber cracking, Malformation) tended to increase in the heat stress. Under heat conditions, the tubers were elongated overall, which means that the marketability of potatoes was lowered. T he tuber firmness and dry matter content tended to decrease significantly in the heat-treated group. T herefore, the yield and quality of tubers were damaged when growing potatoes in heat conditions. T he cultivar with high heat adaptability was 'Jopung'. T his result can be used as basic data for potato growers and breeding of heat-resistant cultivars.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1413-1425
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• 2023

The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.