• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1414-1430
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• 2022

Due to the Internet of Things popularity, many agricultural data are collected by sensors automatically. The abundance of agricultural data makes precise prediction of rice yield possible. Because the climate factors have an essential effect on the rice yield, we considered the climate factors in the prediction model. Accordingly, this paper proposes a machine learning model for rice yield prediction in Taiwan, including the genetic algorithm and support vector regression model. The dataset of this study includes the meteorological data from the Central Weather Bureau and rice yield of Taiwan from 2003 to 2019. The experimental results show the performance of the proposed model is nearly 30% better than MARS, RF, ANN, and SVR models. The most important climate factors affecting the rice yield are the total sunshine hours, the number of rainfall days, and the temperature.The proposed model also offers three advantages: (a) the proposed model can be used in different geographical regions with high prediction accuracies; (b) the proposed model has a high explanatory ability because it could select the important climate factors which affect rice yield; (c) the proposed model is more suitable for predicting rice yield because it provides higher reliability and stability for predicting. The proposed model can assist the government in making sustainable agricultural policies.

• Korean Journal of Remote Sensing
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• v.29 no.1
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• pp.123-135
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• 2013

The reflectance observed in the visible channels of a geostationary meteorological satellite can be used to calculate the amount of cloud by comparing the reflectance with the observed solar radiation data at the ground. Using this, the solar radiation arriving at the surface can be estimated. This study used the Meteorological Imager (MI) reflectance observed at a wavelength of 675 nm and the Geostationary Ocean Color Imager (GOCI) reflectance observed at similar wavelengths of 660 and 680 nm. Cloudy days during a typhoon and sunny days with little cloud cover were compared using observation data from the geostationary satellite. Pixels that had more than 40% reflectance in the satellite images showed less than 0.3 of the cloud index and blocked more than 70% of the solar energy. Pixels that showed less than 15% reflectance showed more than 0.9 of the cloud index and let through more than 90% of the solar energy to the surface. The calculated daily accumulated solar radiation was compared with the observed daily accumulated solar radiation in 22 observatories of the Korean Meteorological Administration. The values calculated for the COMS and MTSAT MI sensors were smaller than the observation and showed low correlations of 0.94 and 0.93, respectively, which were smaller than the 0.96 correlation coefficient calculated for the GOCI sensor. The RMSEs of MTSAT, COMS MI and GOCI calculation results showed 2.21, 2.09, 2.02 MJ/$m^2$ in order. Comparison of the calculated daily accumulated results from the GOCI sensor with the observed data on the ground gave correlations and RMSEs for cloudy and sunny days of 0.96 and 0.86, and 1.82 MJ/$m^2$ and 2.27 MJ/$m^2$, respectively, indicating a slightly higher correlation for cloudy days. Compared to the meteorological imager, the geostationary ocean color imager in the COMS satellite has limited observation time and observation is not continuous. However, it has the advantage of providing high resolution so that it too can be useful for solar energy analysis.

• Geophysics and Geophysical Exploration
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• v.16 no.3
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• pp.190-195
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• 2013

We estimated near-surface shear-wave velocity (${\nu}_s$) at the Hwacheon seismic station using a geologic log of a well, microtremors recorded during a period of 56 days, and records of three teleseismic events ($M_w{\geq}6.0$). The vs of the 10-m thick soil layer (${\nu}^s_s$= 296 m/s) was determined from horizontal-to-vertical spectral ratios of microtremors recorded at the surface. The average ${\nu}_s$ ($\bar{\nu}_s$= 1,309 m/s) from the surface to the 96-m depth of a borehole sensor, was computed using spectral coherence analyses of data recorded by surface- and borehole-sensors for the three teleseismic events. Using these calculated values of ${\nu}^s_s$ and $\bar{\nu}_s$, the computed bedrock ${\nu}_s$ is 2,150 m/s and the time-averaged ${\nu}_s$ to a 30-m depth is 696 m/s. Accordingly the Hwacheon seismic station is regarded as a relatively good site. The deduced near-surface ${\nu}_s$ can be used for further quantitative evaluation of site amplification and earthquake hazard.

• Journal of Korean Society for Atmospheric Environment
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• v.26 no.5
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• pp.475-489
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• 2010

In order to verify the enhancement of ozone and carbon monoxide (CO) during springtime in East Asia, we investigated weather conditions and data from remote sensors, air quality models, and air quality monitors. These include the geopotential height archived from the final (FNL) meteorological field, the potential vorticity and the wind velocity simulated by the Meteorological Mesoscale Model 5 (MM5), the back trajectory estimated by the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model, the total column amount of ozone and the aerosol index retrieved from the Total Ozone Mapping Spectrometer (TOMS), the total column density of CO retrieved from the Measurement of Pollution in the Troposphere (MOPITT), and the concentration of ozone and CO simulated by the Model for Ozone and Related Chemical Tracers (MOZART). In particular, the total column density of CO, which mightoriginate from the combustion of fossil fuels and the burning of biomass in China, increased in East Asia during spring 2000. In addition, the enhancement of total column amounts of ozone and CO appeared to be associated with both the upper cut-off low near 500 hPa and the frontogenesis of a surface cyclone during a weak Asian dust event. At the same time, high concentrations of ozone and CO on the Earth's surface were shown at the Seoul air quality monitoring site, located at the surface frontogenesis in Korea. It was clear that the ozone was invaded by the downward stretched vortex anomalies, which included the ozone-rich airflow, during movement and development of the cut-off low, and then there was the catalytic photochemical reaction of ozone precursors on the Earth's surface during the day. In addition, air pollutants such as CO and aerosol were tracked along both the cyclone vortex and the strong westerly as shown at the back trajectory in Seoul and Busan, respectively. Consequently, the maxima of ozone and CO between the two areas showed up differently because of the time lag between those gases, including their catalytic photochemical reactions together with the invasion from the upper troposphere, as well as the path of their transport from China during the weak Asian dust event.

• Journal of Digital Contents Society
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• v.18 no.7
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• pp.1377-1386
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• 2017

We propose a smart ocean meteorological observation system which is capable of real-time measurement of vulnerable marine climate and oceanographic conditions. Besides, imported products have several disadvantages such that they can't be measured for a long time and can't transmit data in real time. In the proposed system, smart ocean observation digging system, it observes real-time ocean weather with data logger methods. Furthermore, we also use existing dataloggers functions with various sensors which are available in the ocean at the same time. Also, we applied the Kalman-filter algorithm to the ocean crest measurement to reduce the noise and increase the accuracy of the real-time wave height measurement. In the experiment, we experimented the proposed system with our proposed algorithms through calibration devices in the real ocean environment. Then we compared the proposed system with and without the algorithms. As a result, the system developed with a lithium iron phosphate battery that can be charged by a system used in the ocean and minimized power consumption by using an RTC based timer for optimal use. Besides, we obtained optimal battery usage and measured values through experiments based on the measurement cycle.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.107-116
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• 2020

In this data paper, we share the dataset obtained during 2019 from the test-bed to develop soil moisture estimation technology for upland fields, which was built in Seosan and Taean, South Korea on May 3. T his dataset includes various eco-hydro-meteorological variables such as soil moisture, evapotranspiration, precipitation, radiation, temperature, humidity, and vegetation indices from the test-bed nearby the Automated Agricultural Observing System (AAOS) in Seosan operated by the Korea Meteorological Administration. T here are three remarkable points of the dataset: (1) It can be utilized to develop and evaluate spatial scaling technology of soil moisture because the areal measurement with wide spatial representativeness using a COSMIC-ray neutron sensor as well as the point measurement using frequency/time domain reflectometry (FDR/TDR) sensors were conducted simultaneously, (2) it can be used to enhance understanding of how soil moisture and crop growth interact with each other because crop growth was also monitored using the Smart Surface Sensing System (4S), and (3) it is possible to evaluate the surface water balance by measuring evapotranspiration using an eddy covariance system.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.5
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• pp.513-522
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• 2021

A smartphone (SMP) includes a MEMS sensor that can record 3-components motions and has a wireless network device to transmit data in live. These features and relatively low maintenance costs are the advantage of using SMPs as an auxiliary seismic observation network. Currently, 279 SMPs are monitoring seismic motions. In this study, we compare the SMP records with the seismic station (SS) records to validate SMP records. The data used for comparison are records for five earthquakes that occurred in 2019, which are 321 SS data recorded by the Korea Meteorological Administration and the Korea Institute of Geoscience and Mineral Resources and 145 recorded by SMPs. The analysis shows that the event-term corrected average residual of the SMP MEMS sensor records is 0.59 which indicating that the peak horizontal acceleration by SMP is 1.8 factor bigger than the peak ground acceleration by SS. In addition, the residuals tend to decrease as the installation floor of the smartphone MEMS sensor increases, which is the similar trend with response spectra from SS.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1301-1314
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• 2022

Normalized Difference Vegetation Index (NDVI) is utilized as an indicator to represent the vegetation condition on the land surface in various applications such as land cover, crop yield, agricultural drought, soil moisture, and forest disaster. However, satellite optical sensors for visible and infrared rays cannot see through the clouds, so the NDVI of the cloud pixel is not a valid value for the land surface. This study proposed a real-time correction of the underestimation noise for GEO-KOMPSAT-2A (GK2A) daily NDVI and made sure its feasibility through the quantitative comparisons with Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI and the qualitative interpretation of time-series changes. The underestimation noise was effectively corrected by the procedures such as the time-series correction considering vegetation phenology, the outlier removal using long-term climatology, and the gap filling using rigorous statistical methods. The correlation with MODIS NDVI was higher, and the difference was lower, showing a 32.7% improvement compared to the original NDVI product. The proposed method has an extensibility for use in other satellite products with some modification.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.729-741
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• 2023

The Operational Linescan System (OLS)sensor is a sensor aboard satellites launched through the Defense Meteorological Satellite Program (DMSP) that detects light in the visible and infrared bands emitted at night. Studies by several researchers have shown a high correlation between nighttime light data from OLS sensors and gross domestic product values. In this study, we investigated the correlation of nighttime light data with the total amount of individual land prices, which is one of the various indicators related to economic development. The study found that most cities and provinces showed a high correlation with a correlation coefficient of more than 0.7, and the correlation coefficient of 0.7837 between the total amount of individual land price and nighttime light data for the entire South Korea was also high. However, unlike other cities and provinces, Seoul has a low correlation coefficient of 0.5648 between nighttime light and the total amount of individual land price, which is analyzed as a reason that the digital number value of the OLS sensor is close to the maximum value and cannot show further brightness changes. This study is expected to help identify announced land prices in areas where announced land prices are not systematically organized and to analyze land use changes in such areas.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.1-6
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• 2020

UAV (Unmanned Aerial Vehicles) are used widely for military purposes because they are more economical than general manned aircraft and satellites, and have easy access to the object. Recently, owing to the development of IT technology, UAV equipped with various sensors have been released, and their use is increasing in a wide range of fields, such as surveying, agriculture, meteorological observation, communication, broadcasting, and sports. An increasing number of studies and attempts have made use of it. On the other hand, existing research was related mostly to photogrammetry, but there has been a lack of analytical research on LiDAR (Light Detection And Ranging). Therefore, this study examined the characteristics of a UAV LiDAR sensor for the application of a geospatial information field. In this study, the performance of commercialized LiDAR sensors, such as the acquisition speed and the number of echoes, was investigated, and data acquisition and analysis were conducted by selecting Surveyor Ultra and VX15 models with similar accuracy and data acquisition distances. As a result, a DSM of each study site was generated for each sensor, and the characteristics of data density, precision, and acquisition of ground data from vegetation areas were presented through comparison. In addition, the UAV LiDAR sensor showed an accuracy of 0.03m ~ 0.05m. Hence, it is necessary to select equipment considering the characteristics of data for effective use. In the future, the use of UAV LiDAR may be suggested if additional data can be obtained and analyzed for various areas, such as urban areas and forest areas.