• Korean Journal of Remote Sensing
• /
• v.27 no.2
• /
• pp.191-201
• /
• 2011

Soybean has widely grown for its edible bean which has numerous uses. Microwave remote sensing has a great potential over the conventional remote sensing with the visible and infrared spectra due to its all-weather day-and-night imaging capabilities. In this investigation, a ground-based polarimetric scatterometer operating at multiple frequencies was used to continuously monitor the crop conditions of a soybean field. Polarimetric backscatter data at L, C, and X-bands were acquired every 10 minutes on the microwave observations at various soybean stages. The polarimetric scatterometer consists of a vector network analyzer, a microwave switch, radio frequency cables, power unit and a personal computer. The polarimetric scatterometer components were installed inside an air-conditioned shelter to maintain constant temperature and humidity during the data acquisition period. The backscattering coefficients were calculated from the measured data at incidence angle $40^{\circ}$ and full polarization (HH, VV, HV, VH) by applying the radar equation. The soybean growth data such as leaf area index (LAI), plant height, fresh and dry weight, vegetation water content and pod weight were measured periodically throughout the growth season. We measured the temporal variations of backscattering coefficients of the soybean crop at L, C, and X-bands during a soybean growth period. In the three bands, VV-polarized backscattering coefficients were higher than HH-polarized backscattering coefficients until mid-June, and thereafter HH-polarized backscattering coefficients were higher than VV-, HV-polarized back scattering coefficients. However, the cross-over stage (HH > VV) was different for each frequency: DOY 200 for L-band and DOY 210 for both C and X-bands. The temporal trend of the backscattering coefficients for all bands agreed with the soybean growth data such as LAI, dry weight and plant height; i.e., increased until about DOY 271 and decreased afterward. We plotted the relationship between the backscattering coefficients with three bands and soybean growth parameters. The growth parameters were highly correlated with HH-polarization at L-band (over r=0.92).

• Journal of Preventive Medicine and Public Health
• /
• v.32 no.2
• /
• pp.177-182
• /
• 1999

Objectives: To reexamine the association between air pollution and daily mortality in Seoul, Korea using a method of meta-analysis with the data filed for 1991 through 1995. Methods: A separate Poisson regression analysis on each district within the metropolitan area of Seoul was conducted to regress daily death counts on levels of each ambient air pollutant, such as total suspended particulates (TSP), sulfur dioxide $(SO_2)$, and ozone $(O_3)$, controlling for variability in the weather condition. We calculated a weighted mean as a meta-analysis summary of the estimates and its standard error. Results: We found that the p value from each pollutant model to test the homogeneity assumption was small (p<0.01) because of the large disparity among district-specific estimates. Therefore, all results reported here were estimated from the random effect model. Using the weighted mean that we calculated, the mortality at a $100{\mu}g/m^3$ increment in a 3-day moving average of TSP levels was 1.034 (95% Cl 1.009-1.059). The mortality was estimated to increase 6% (95% Cl 3-10%) and 3% (95% Cl 0-6%) with each 50 ppb increase for 9-day moving average of SO2 and 1-hr maximum O3, respectively. Conclusions: Like most of air pollution epidemiologic studies, this meta-analysis cannot avoid fleeing from measurement misclassification since no personal measurement was taken. However, we can expect that a measurement bias be reduced in a district-specific estimate since a monitoring station is hefter representative cf air quality of the matched district. The similar results to those from the previous studios indicated existence of health effect of air pollution at current levels in many industrialized countries, including Korea.

• Journal of the Korean earth science society
• /
• v.36 no.1
• /
• pp.90-108
• /
• 2015

The WRF-Chem model was applied to simulate the Asian dust event affecting the Korean Peninsula from 11 to 13 November 2010. GOCART dust emission schemes, RADM2 chemical mechanism, and MADE/SORGAM aerosol scheme were adopted within the WRF-Chem model to predict dust aerosol concentrations. The results in the model simulations were identified by comparing with the weather maps, satellite images, monitoring data of $PM_{10}$ concentration, and LIDAR images. The model results showed a good agreement with the long-range transport from the dust source area such as Northeastern China and Mongolia to the Korean Peninsula. Comparison of the time series of $PM_{10}$ concentration measured at Backnungdo showed that the correlation coefficient was 0.736, and the root mean square error was $192.73{\mu}g/m^3$. The spatial distribution of $PM_{10}$ concentration using the WRF-Chem model was similar to that of the $PM_{2.5}$ which were about a half of $PM_{10}$. Also, they were much alike in those of the UM-ADAM model simulated by the Korean Meteorological Administration. Meanwhile, the spatial distributions of $PM_{10}$ concentrations during the Asian dust events had relevance to those of both the wind speed of u component ($ms^{-1}$) and the PBL height (m). We performed a regressive analysis between $PM_{10}$ concentrations and two meteorological variables (u component and PBL) in the strong dust event in autumn (CASE 1, on 11 to 23 March 2010) and the weak dust event in spring (CASE 2, on 19 to 20 March 2011), respectively.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.12 no.2
• /
• pp.132-142
• /
• 2010

Characteristics of meteorological elements were analyzed at Hwagae and Agyang where are the representative areas of Hadong green tea cultivation in Korea. An automatic weather monitoring system (AWS) and a simple data log were employed to measure meteorological data such as temperature, relative humidity, precipitation, and wind direction and speed for 2009. The annual average air temperature of Hwagae and Agyang was 14.5 and 14.2, respectively, showing the warmest month in August ($25.4^{\circ}C$ for Hwagae and $24.9^{\circ}C$ for Agyang) and the coldest month in January ($0.3^{\circ}C$ for Hwagae and $0.2^{\circ}C$ for Agyang). Annual average of daily temperature difference (= daily maximum temperature - daily minimum temperature) was $11.3^{\circ}C$ for Hwagae and $11.1^{\circ}C$ for Agyang. Hwagae and Agyang had 62.7% and 65.3% of the annual average relative humidity, respectively. Annual precipitation was 1387 mm for Hwagae and 1793 mm for Agyang of which were higher of 605mm for Hwagae and 835 mm for Agyang compared to that in 2008. Majority of precipitation occurred between May and August, attributing 77.6% for Hwagae and 76.6% for Agyang to the annual precipitation. The annual total sunshine duration was 2054.3 hrs in Hwagae with the longest monthly sunshine duration in May (235.1 hrs) and the shortest monthly sunshine duration in July (102.5 hrs). Dominant wind direction changed seasonally from northwesterly wind in fall and winter to southeasterly wind in spring and summer. The annual average wind speed was 1.5 m $s^{-1}$ with the highest monthly wind speed of 2.0 m $s^{-1}$ in December and the lowest monthly wind speed of 1.1 m $s^{-1}$ in February. It is expected that continuous observation and assessment of meteorological data will improve our understanding of optimal environmental conditions for green tea cultivation and be used for developing models of green tea cultivation in the Hadong area.

• Journal of Korean Society for Atmospheric Environment
• /
• v.34 no.4
• /
• pp.567-587
• /
• 2018

A severe haze event occurred in October 2015 in Gwangju, Korea. In this study, the driving chemical species and the formation mechanisms of $PM_{2.5}$ pollution were investigated to better understand the haze event. Hourly concentrations of $PM_{2.5}$, organic and elemental carbon, water-soluble ions, and elemental constituents were measured at the air quality intensive monitoring station in Gwangju. The haze event occurred was attributed to a significant contribution (72.3%) of secondary inorganic species concentration to the $PM_{2.5}$, along with the contribution of organic aerosols that were strongly attributed to traffic emissions over the study site. MODIS images, weather charts, and air mass backward trajectories supported the significant impact of long-range transportation (LTP) of aerosol particles from northeastern China on haze formation over Gwangju in October 2015. The driving factor for the haze formation was stagnant atmospheric flows around the Korean peninsula, and high relative humidity (RH) promoted the haze formation at the site. Under the high RH conditions, $SO{_4}^{2-}$ and $NO_3{^-}$ were mainly produced through the heterogenous aqueous-phase reactions of $SO_2$ and $NO_2$, respectively. Moreover, hourly $O_3$ concentration during the study period was highly elevated, with hourly peaks ranging from 79 to 95ppb, suggesting that photochemical reaction was a possible formation process of secondary aerosols. Over the $PM_{2.5}$ pollution, behavior and formation of secondary ionic species varied with the difference in the impact of LTP. Prior to October 19 when the influence of LTP was low, increasing rate in $NO_3{^-}$ was greater than that in $NO_2$, but both $SO_2$ and $SO{_4}^{2-}$ had similar increasing rates. While, after October 20 when the impact of haze by LTP was significant, $SO{_4}^{2-}$ and $NO_3{^-}$ concentrations increased significantly more than their gaseous precursors, but with greater increasing rate of $NO_3{^-}$. These results suggest the enhanced secondary transformation of $SO_2$ and $NO_2$ during the haze event. Overall, the result from the study suggests that control of anthropogenic combustion sources including vehicle emissions is needed to reduce the high levels of nitrogen oxide and $NO_3{^-}$ and the high $PM_{2.5}$ pollution occurred over fall season in Gwangju.

• Korean Journal of Soil Science and Fertilizer
• /
• v.46 no.1
• /
• pp.23-31
• /
• 2013

Microwave remote sensing can help monitor the land surface water cycle and crop growth. This type of remote sensing has great potential over conventional remote sensing using the visible and infrared regions due to its all-weather day-and-night imaging capabilities. In this paper, a ground-based multi-frequency (L-, C-, and X-band) polarimetric scatterometer system capable of making observations every 10 min was developed. This system was used to monitor the wheat over an entire growth cycle. The polarimetric scatterometer components were installed inside an air-conditioned shelter to maintain constant temperature and humidity during the data acquisition period. Backscattering coefficients for the crop growing season were compared with biophysical measurements. Backscattering coefficients for all frequencies and polarizations increased until dat of year 137 and then decreased along with fresh weight, dry weight, plant height, and vegetation water content (VWC). The range of backscatter for X-band was lower than for L- and C-band. We examined the relationship between the backscattering coefficients of each band (frequency/polarization) and the various wheat growth parameters. The correlation between the different vegetation parameters and backscatter decreased with increasing frequency. L-band HH-polarization (L-HH) is best suited for the monitoring of fresh weight (r=0.98), dry weight (r=0.96), VWC (r=0.98), and plant height (r=0.96). The correlation coefficients were highest for L-band observations and lowest for X-band. Also, HH-polarization had the highest correlations among the polarization channels (HH, VV and HV). Based on the correlation analysis between backscattering coefficients in each band and wheat growth parameters, we developed prediction equations using the L-HH based on the observed relationships between L-HH and fresh weight, dry weight, VWC and plant height. The results of these analyses will be useful in determining the optimum microwave frequency and polarizations necessary for estimating vegetation parameters in the wheat.

• Korean Journal of Environmental Biology
• /
• v.31 no.4
• /
• pp.429-439
• /
• 2013

This study was conducted to identify the relationship between environmental factors and algal bloom, and provide information for efficient management based on the results of monitoring the environmental parameters and algal diversity in the Jundai reservoir from March 2011 to October 2013. Little change in the weather conditions was observed during the study period except for a slight decrease in rainfall. Concentration of TN and TP in the reservoir exceeded water quality standards for agriculture and significant correlation between algal growth and environmental factors was observed. Phytoplankton in Jundai reservoir included 6 classes, 40 genus, 62 species, and the phytoplankton abundance was in the range of $1.3{\times}10^4{\sim}2.8{\times}10^6$ cells $mL^{-1}$. The annual average of phytoplankton abundance and Chl-a gradually decreased as TN and TP concentrations decreased. Overall Anabaena sp., Oscillatoria sp., and Microcystis sp. were the dominant species in Jundai reservoir. As the water temperature increased, the dominant species were Anabaena sp., Microcystis sp. and Oscillatoria sp., in that order. Anabaena sp. was dominant from spring to early summer with increase in water temperature and pollutant concentrations, and high correlation with environmental factors was observed. Microcystis sp. was dominant depending on changes in the nutrient levels. In the case of Oscillatoria sp., there was no significant correlation between phytoplankton biomess and Chl-a. However, efficient management of water environment and practical control of algal bloom in small scale reservoir polluted by livestock and farm irrigation should be achieved by identification of the relationship between algal growth and environmental factors.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.8 no.1
• /
• pp.36-44
• /
• 2006

In this study, we constructed a forest fire danger map in the Yeongdong area of Gangwon-do and Northeastern area of Gyeongsangbuk-do using a forest fire rating model and geographical information system (GIS). We investigated the appropriate positions of the automatic weather station (AWS) and a comprehensive network solution (a system including measurement, communication and data processing) for the establishment of an optimum mountain meteorological observation network system (MMONS). Also, we suggested a possible plan for combining the MMONS with unmanned monitoring camera systems and wireless relay towers operated by local governments and the Korea Forest Service for prevention of forest fire.

• Korean Journal of Soil Science and Fertilizer
• /
• v.44 no.5
• /
• pp.878-886
• /
• 2011

The soybean is one of the oldest cultivated crops in the world. Microwave remote sensing is an important tool because it can penetrate into cloud independent of weather and it can acquire day or night time data. Especially a ground-based polarimetric scatterometer has advantages of monitoring crop conditions continuously with full polarization and different frequencies. In this study, soybean growth parameters and soil moisture were estimated using polarimetric discrimination ratio (PDR) by radar scatterometer. A ground-based polarimetric scatterometer operating at multiple frequencies was used to continuously monitor the soybean growth condition and soil moisture change. It was set up to obtain data automatically every 10 minutes. The temporal trend of the PDR for all bands agreed with the soybean growth data such as fresh weight, Leaf Area Index, Vegetation Water Content, plant height; i.e., increased until about DOY 271 and decreased afterward. Soil moisture lowly related with PDR in all bands during whole growth stage. In contrast, PDR is relative correlated with soil moisture during below LAI 2. We also analyzed the relationship between the PDR of each band and growth data. It was found that L-band PDR is the most correlated with fresh weight (r=0.96), LAI (r=0.91), vegetation water content (r=0.94) and soil moisture (r=0.86). In addition, the relationship between C-, X-band PDR and growth data were moderately correlated ($r{\geq}0.83$) with the exception of the soil moisture. Based on the analysis of the relation between the PDR at L, C, X-band and soybean growth parameters, we predicted the growth parameters and soil moisture using L-band PDR. Overall good agreement has been observed between retrieved growth data and observed growth data. Results from this study show that PDR appear effective to estimate soybean growth parameters and soil moisture.

• Korean Journal of Remote Sensing
• /
• v.37 no.5_1
• /
• pp.947-958
• /
• 2021

This study was conducted to provide basic data for crop monitoring by comparing and analyzing changes in reflectance and vegetation index by sensor of multi-spectral sensors mounted on unmanned aerial vehicles. For four types of unmanned aerial vehicle-mounted multispectral sensors, such as RedEdge-MX, S110 NIR, Sequioa, and P4M, on September 14 and September 15, 2020, aerial images were taken, once in the morning and in the afternoon, a total of 4 times, and reflectance and vegetation index were calculated and compared. In the case of reflectance, the time-series coefficient of variation of all sensors showed an average value of about 10% or more, indicating that there is a limit to its use. The coefficient of variation of the vegetation index by sensor for the crop test group showed an average value of 1.2 to 3.6% in the crop experimental sites with high vitality due to thick vegetation, showing variability within 5%. However, this was a higher value than the coefficient of variation on a clear day, and it is estimated that the weather conditions such as clouds were different in the morning and afternoon during the experiment period. It is thought that it is necessary to establish and implement a UAV flight plan. As a result of comparing the NDVI between the multi-spectral sensors of the unmanned aerial vehicle, in this experiment, it is thought that the RedEdeg-MX sensor can be used together without special correction of the NDVI value even if several sensors of the same type are used in a stable light environment. RedEdge-MX, P4M, and Sequioa sensors showed a linear relationship with each other, but supplementary experiments are needed to evaluate joint utilization through off-set correction between vegetation indices.