Lee, Min-Boo;Kim, Nam-Shin;Kang, Chul-Sung;Shin, Keun-Ha;Choe, Han-Sung;Han, Uk
Journal of the Korean association of regional geographers
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v.9
no.3
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pp.373-384
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2003
This study analyses the soil loss due to cropland increase in the Hoeryeung area of northeast Korea, using Landsat images of 1987 TM and 2001 ETM, together with DTED, soil and geological maps, and rainfall data of 20 years. Items of land cover and land use were categorized as cropland, settlement, forest, river zone, and sand deposit by supervised classification with spectral bands 1, 2 and 3. RUSLE model is used for estimation of soil loss, and AML language for calculation of soil loss volumes. Fourier transformation method is used for unification of the geographical grids between Landsat images and DTED. GTD was selected from 1:50,000 topographic map. Main sources of soil losses over 100 ton/year may be the river zone and settlement in the both times of 1987 and 2001, but the image of the 2001 shows that sources areas have developed up to the higher mountain slopes. In the cropland average, increases of hight and gradient are 24m and $0.8^{\circ}$ from 1987 to 2001. In the case of new developed cropland, average increases are 75m and $2.5^{\circ}$, and highest soil loss has occurred at the elevation between 300 and 500m. The soil loss 57 ton of 1987 year increased 85 ton of 2001 year. Soil loss is highest in $30{\sim}50^{\circ}$ slope zones in both years, but in 2001 year, soil loss increased under $30^{\circ}$ zones. The size of area over 200 ton/year, indicating higher risk of landslides, have increased from $28.6km^2$ of 1987 year to $48.8km^2$ of 2001 year.
Korean Journal of Agricultural and Forest Meteorology
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v.21
no.4
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pp.327-336
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2019
Soybean is one of the most important crops of which the grains contain high protein content and has been consumed in various forms of food. Soybean plants are generally cultivated on the field and their yield and quality are strongly affected by climate change. Recently, the abnormal climate conditions, including heat wave and heavy rainfall, frequently occurs which would increase the risk of the farm management. The real-time assessment techniques for quality and growth of soybean would reduce the losses of the crop in terms of quantity and quality. The objective of this work was to develop a simple model to estimate the growth of soybean plant using a multispectral sensor mounted on a rotor-wing unmanned aerial vehicle(UAV). The soybean growth model was developed by using simple linear regression analysis with three phenotypic data (fresh weight, dry weight, leaf area index) and two types of vegetation indices (VIs). It was found that the accuracy and precision of LAI model using GNDVI (R2= 0.789, RMSE=0.73 ㎡/㎡, RE=34.91%) was greater than those of the model using NDVI (R2= 0.587, RMSE=1.01 ㎡/㎡, RE=48.98%). The accuracy and precision based on the simple ratio indices were better than those based on the normalized vegetation indices, such as RRVI (R2= 0.760, RMSE=0.78 ㎡/㎡, RE=37.26%) and GRVI (R2= 0.828, RMSE=0.66 ㎡/㎡, RE=31.59%). The outcome of this study could aid the production of soybeans with high and uniform quality when a variable rate fertilization system is introduced to cope with the adverse climate conditions.
Journal of the Korean Society of Marine Environment & Safety
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v.18
no.2
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pp.95-100
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2012
This study was determined to analysis marine environmental and phytoplankton monitoring in Wando coastal waters in August during the period of 2009-2010 and provided the basic environmental data against Southwest Sea of Korea. In August, 2009, the distribution of water temperature and salinity showed an unique characteristics for all of stations, which was associated with a long duration of rainfall after July, 2009 and a lack of sunshine. In the lower of August, 2010, the stratification of water temperature and salinity was shown, which was caused by an intensive sunshine after the middle of August, 2010. Gangjin Bay and Gogeundo waters showed a highly different water temperature and transparency. It is thought that two regions have a distinct water mass and characteristics. In dissolved oxygen and oxygen saturation were higher according to higher water depth regardless of stations. In August, 2009, different dominant species occurred that Gangjin Bay showed a higher cell density of diatom, but Gonyaulax polygramma played an important role in dominant species in Gogeundo waters. It is associated with the introduction red tide water of G. polygramma occurring to southern coastal water in August, 2009. In August, 2010, diatom was extremely higher cell density compared with that of dinoflagellate that regarded as adaptive microrganism against higher quantity of suspended solid in Wando waters. Although Wando has a record of Cochlodinium red tide, this species may be difficult to grow and persist. Dominant species, diatom, play an important role in food organism for shellfish and forming a ecological lineage.
The measured soil data are analyzed to the descriptive statistics and classified into the four models of uncorrelated-normal (UNNO), uncorrelated-nonnormal (VNNN), correlatedonnormal(CONN), and correlated-nonnormal(CONN) . This paper presents the comparisons of reliability index and check points using the advanced first-order second-moment method with respect to the four models as well as BASIC Program. A sin91e-mode Performance function is consisted of the basic design variables of bearing capacity and settlements on shallow foundations and input the above analyzed soil informations. The main conclusions obtained in this study are summarized as follows: 1. In the bearing capacity mode, cohesion and bearing-capacity factors by C-U test are accepted for normal and lognormal distribution, respectively, and negatively low correlated to each other. Since the reliability index of the CONN model is the lowest one of the four model, which could be recommended a reliability.based design, whereas the other model might overestimate the geotechnical conditions. 2. In the case of settlements mode, the virgin compression ratio and preccnsolidation pressure are fitted for normal and lognormal distribution, respectively. Constraining settlements to the lower ones computed by deterministic method, The CONN model is the lowest reliability of the four models.
Korean Journal of Agricultural and Forest Meteorology
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v.18
no.4
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pp.221-232
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2016
Models to estimate solar radiation have been used because solar radiation is measured at a smaller number of weather stations than other variables including temperature and rainfall. For example, solar radiation has been estimated using the Angstrom-Prescott (AP) model that depends on two coefficients obtained empirically at a specific site ($AP_{Choi}$) or for a climate zone ($AP_{Frere}$). The objective of this study was to identify the coefficients of the AP model for reliable estimation of solar radiation under a wide range of spatial and temporal conditions. A global optimization was performed for a range of AP coefficients to identify the values of $AP_{max}$ that resulted in the greatest degree of agreement at each of 20 sites for a given month during 30 years. The degree of agreement was assessed using the value of Concordance Correlation Coefficient (CCC). When $AP_{Frere}$ was used to estimate solar radiation, the values of CCC were relatively high for conditions under which crop growth simulation would be performed, e.g., at rural sites during summer. The statistics for $AP_{Frere}$ were greater than those for $AP_{Choi}$ although $AP_{Frere}$ had the smaller statistics than $AP_{max}$ did. The variation of CCC values was small over a wide range of AP coefficients when those statistics were summarized by site. $AP_{Frere}$ was included in each range of AP coefficients that resulted in reasonable accuracy of solar radiation estimates by site, year, and month. These results suggested that $AP_{Frere}$ would be useful to provide estimates of solar radiation as an input to crop models in Korea. Further studies would be merited to examine feasibility of using $AP_{Frere}$ to obtain gridded estimates of solar radiation at a high spatial resolution under a complex terrain in Korea.
Park, Won-Zei;Lee, Kyong-Jae;Han, Bong-Ho;Jang, Jae-Hoon
Journal of the Korean Institute of Landscape Architecture
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v.40
no.2
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pp.112-129
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2012
The aim of this study was to provide basic data in managing the project that was carried out on Bulgwangcheon in a nature-friendly way to improve the conditions around the areas, which was brought to completion in 2002, based on changes in ecological characteristics. For this propose, this study examined documents related to the project, compared physical and enviromnental changes before and after the project was conducted and analyzed changes in the stream ecosystem. The result showed that in areas that effluent water was often observed, especially when it rained, the river wall was washed away and vegetation was found damaged. As for actual vegetation, this study compared planting coverage of each section of the research area and actual vegetation charts. The results indicated that Lespedeza spp., Aster koraiensis among mixed seeds that were planted in the reservoir path were almost swept away while Festuca arundinacea dominated the areas. Phragmites communis, Miscanthus sacchariflorns and Salix gracilistyla which had been planted in a small number were also almost washed out though a small number of them were left to form a colony. After examining the topography and structure of the plant community, this study found that areas where mixed seed were planted had changed into two types of vegetation: First type of area is dominated by P and R which are usually raised in apron with abundant floating particles. The second type of area is dominated by dry gramineous plant such as F and A. Areas around low flow channel where Phragmites communis, Miscanthus sacchariflorus and Salix gracilistyla planting construction method is applied was washed away with the width of low flow channel reduced. Though P, M and S formed a small community in some areas around the low flow area, they were in small number and in composition of simple plant species. Two ways were suggested in this study to manage the stream in an ecological way. First, adequate revetment construction methods should be applied by monitoring the flow of the stream as well as considering the flood control of urban streams. Second, target vegetation communities that are suitable for the environment of the stream should be chosen and be plantedconstantly with high density. At the same time, ornamental native plants shouldn't be planted as they have been and disturbing vegetation should be removed.
The study was carried out to estimate runoff loads of heavy metals in the valley watershed at the middle of South Korea, during farming season. There were no other pollution sources except agricultural activity. From 27 April 2006 to 31 October 2007, water samples were collected using two methods. The first method was regular sampling wherein water samples were taken every two weeks; and the other method was through regular sampling when water were collected during each rainfall event. Results showed that heavy metals were found in the water from the regular samples, and were highest during May and June. It was presumed that this might have been contributed by farming activities. Heavy metal concentration of the irregular samples was lower than regular samples. The correlation coefficient between each heavy metal of the regular samples were as follows: Fe-Al>Cr-Al>Fe-Cr>Mn-Fe. The correlation coefficient of the irregular samples were the following: Fe-Al>Fe-Cu is positive; and Pb-Cu>Ni-Al is negative. Measured pollutant loads of heavy metals in the valley watershed were : 2.047 kg $day^{-1}$ of Al, 0.008 kg $day^{-1}$ of Cd, 0.034 kg $day^{-1}$ of Cr, 0.311 kg $day^{-1}$ of Cu, 0.601 kg $day^{-1}$ of Fe, and 0.282 kg $day^{-1}$ of Zn in 2006; while in 2007, the following were observed: 2.535 kg $day^{-1}$ of Al, 0.026 kg $day^{-1}$ of Cd, 0.055 kg $day^{-1}$ of Cu, 0.727 kg $day^{-1}$ of Fe, and 0.317 kg $day^{-1}$ of Zn. In the analysis of data gathered, the loading rates of effluents from the valley watershed during the rainy season were : 79.8% of Al, 69.1% of Cu, 82.5% of Fe, and 69.1% of Zn in 2006; while 69.9% of Al, 67.5% of Cu, 70.4% of Fe, and 67.5% of Zn in 2007.
Effects of environmental factors on phytoplankton succession and community structure were studied in Lake Chuncheon located in Bukhan River, South Korea. The data were sampled at three sites such as CC1 (lower side), CC2 (middle side), and CC3 (upper side of Lake Chuncheon) from 2014 to 2017. The annual average precipitation in Lake Chuncheon was 992 mm during the study period (2014~2017), and the annual precipitation was lower than 800 mm in 2014 and 2015. The annual average water temperature, total phosphorus (TP), and total nitrogen (TN) ranged from 17.0 to $21.1^{\circ}C$, 0.012 to $0.019mg\;L^{-1}$, and 1.272 to $1.922mg\;L^{-1}$, respectively. The TN concentration was relatively high in 2015 compared with the other study years, as a drought continued from 2014 to 2015. When comparing the correlation between precipitation and environmental factors, water temperature (p<0.01) and TP(p<0.05) showed positive correlations with rainfall. The average numbers of phytoplankton cells by branch were 2,094, 2,182, and $3,108cells\;mL^{-1}$ in CC1, CC2, and CC3, respectively. CC3 is considered advantageous for phytoplankton growth, even in small pollution sources due to low water depth. As a result of analyzing the relationship between precipitation and phytoplankton, the correlation between the two was shown to be high for 2016 (p<0.01) and 2017 (p<0.05), which is when precipitation was high. However, the correlation was not clear to 2014 and 2015. The relationship between water temperature and phytoplankton indicated a negative correlation with diatoms (p<0.01), yet positive correlations with green algae (p<0.01) and cyanobacteria (p<0.01). Diatoms increased in spring and autumn, which are characterized by low water temperature, and green algae and cyanobacteria increased in summer, when the water temperature is high. Our findings provide a scientific basis for characteristics of phytoplankton and water quality and management at the Lake Chuncheon.
The warming of the climate is increasing the damage caused by termites to wooden buildings, cultural properties and houses. A group removal system can be installed around the building to detect and remove termite damage; however, if the site is not visited regularly, every one to two months, you cannot observe whether termites have spread within, and it is difficult to take prompt effective action. In addition, since the system is installed and operated in an exposed state for a long period of time, it may be ineffective or damaged, resulting in a loss of function. Furthermore if the system is installed near a cultural site, it may affect the aesthetic environment of the site. In this study, we created a detection system that uses wood, cellulose, magnets, and magnetic sensors to determine whether termites have entered the area. The data was then transferred to a low power LoRa Network which displayed the results without the necessity of visiting the site. The wood was made in the shape of a pile, and holes were made from the top to the bottom to make it easier for termites to enter and produce a cellulose sample. The cellulose sample was made in a cylindrical shape with a magnet wrapped in cellulose and inserted into the top of a hole in the wood. Then, the upper part of the wood pile was covered with a stopper to prevent foreign matter from entering. It also served to block external factors such as light and rainfall, and to create an environment where termites could add cellulose samples. When the cellulose was added by the termites, a space was created around the magnet, causing the magnet to either fall or tilt. The magnetic sensor inside the stopper was fixed on the top of the cellulose sample and measured the change in the distance between the magnet and the sensor according to the movement of the magnet. In outdoor experiments, 11 cellulose samples were inserted into the wood detection system and the termite inflow was confirmed through the movement of the magnet without visiting the site within 5 to 17 days. When making further improvements to the function and operation of the system it in the future, it is possible to confirm that termites have invaded without visiting the site. Then it is also possible to reduce damage and fruiting due to product exposure, and which would improve the condition and appearance of cultural properties.
Rice lodging is an annual occurrence caused by typhoons accompanied by strong winds and strong rainfall, resulting in damage relating to pre-harvest sprouting during the ripening period. Thus, rapid estimations of the area of lodged rice are necessary to enable timely responses to damage. To this end, we obtained images related to rice lodging using a drone in Gimje, Buan, and Gunsan, which were converted to 128 × 128 pixels images. A convolutional neural network (CNN) model, a deep learning model based on these images, was used to predict rice lodging, which was classified into two types (lodging and non-lodging), and the images were divided in a 8:2 ratio into a training set and a validation set. The CNN model was layered and trained using three optimizers (Adam, Rmsprop, and SGD). The area of rice lodging was evaluated for the three fields using the obtained data, with the exception of the training set and validation set. The images were combined to give composites images of the entire fields using Metashape, and these images were divided into 128 × 128 pixels. Lodging in the divided images was predicted using the trained CNN model, and the extent of lodging was calculated by multiplying the ratio of the total number of field images by the number of lodging images by the area of the entire field. The results for the training and validation sets showed that accuracy increased with a progression in learning and eventually reached a level greater than 0.919. The results obtained for each of the three fields showed high accuracy with respect to all optimizers, among which, Adam showed the highest accuracy (normalized root mean square error: 2.73%). On the basis of the findings of this study, it is anticipated that the area of lodged rice can be rapidly predicted using deep learning.
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