7 results on '"Jeehun Chung"'
Search Results
2. Soil Moisture Content Estimation Based on Sentinel-1 SAR Imagery Using an Artificial Neural Network and Hydrological Components
- Author
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Jeehun Chung, Yonggwan Lee, Jinuk Kim, Chunggil Jung, and Seongjoon Kim
- Subjects
antecedent precipitation index ,artificial neural network ,Sentinel-1 ,soil moisture content ,synthetic aperture radar ,Science - Abstract
This study estimates soil moisture content (SMC) using Sentinel-1A/B C-band synthetic aperture radar (SAR) images and an artificial neural network (ANN) over a 40 × 50-km2 area located in the Geum River basin in South Korea. The hydrological components characterized by the antecedent precipitation index (API) and dry days were used as input data as well as SAR (cross-polarization (VH) and copolarization (VV) backscattering coefficients and local incidence angle), topographic (elevation and slope), and soil (percentage of clay and sand)-related data in the ANN simulations. A simple logarithmic transformation was useful in establishing the linear relationship between the observed SMC and the API. In the dry period without rainfall, API did not decrease below 0, thus the Dry days were applied to express the decreasing SMC. The optimal ANN architecture was constructed in terms of the number of hidden layers, hidden neurons, and activation function. The comparison of the estimated SMC with the observed SMC showed that the Pearson’s correlation coefficient (R) and the root mean square error (RMSE) were 0.85 and 4.59%, respectively.
- Published
- 2022
- Full Text
- View/download PDF
3. Evaluation of Land-Use Changes Impact on Watershed Health Using Probabilistic Approaches
- Author
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Jiwan Lee, Jeehun Chung, Soyoung Woo, Yonggwan Lee, Chunggil Jung, Daeryong Park, and Seongjoon Kim
- Subjects
multivariate normal distribution ,land-use change ,watershed health ,watershed health index ,SWAT ,Hydraulic engineering ,TC1-978 ,Water supply for domestic and industrial purposes ,TD201-500 - Abstract
This study evaluated watershed health (WH) change using reference values for environmental changes at various times. Land use in 1985 was defined as the reference value under the most natural conditions, and the WH for the years 1995 to 2019 was calculated in comparison to 1985. The proposed method was used to assess the WH of 78 standard subbasins in South Korea’s Geum River Basin (GRB), where complex land-use change has occurred since 1995. For evaluating hydrology and water quality (WQ) health index, Soil and Water Assessment Tool (SWAT) and four land-use maps (1985, 1995, 2008, and 2019) were used to simulate the hydrology and WQ. A multivariate normal distribution (MND) from poor (0) to good (1) was used to assess WH based on SWAT modeling results. Based on the reference value, the WQ health from 1995 to 2019 changed to within 0.1, while the range of changes in the hydrology index was analyzed over 0.18. As a result of WH changes from 1985 to 2019, hydrological health deteriorated in high-density urbanized subbasins, while WQ health deteriorated in upland-cultivation-increased subbasins. This study provides useful information for recognizing potential WH issues related to long-term environmental changes.
- Published
- 2021
- Full Text
- View/download PDF
4. Correlation Analysis between Air Temperature and MODIS Land Surface Temperature and Prediction of Air Temperature Using TensorFlow Long Short-Term Memory for the Period of Occurrence of Cold and Heat Waves
- Author
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Jeehun Chung, Yonggwan Lee, Wonjin Jang, Siwoon Lee, and Seongjoon Kim
- Subjects
air temperature prediction ,heat and cold waves ,long short-term memory ,MODIS land surface temperature ,TensorFlow ,Science - Abstract
The purpose of this study is to analyze the correlation between surface air temperature (SAT) and land surface temperature (LST) based on land use when heat and cold waves occur and to predict the distribution of SAT using the long short-term memory (LSTM) of TensorFlow. For the correlation analysis, the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) daytime and nighttime LST and maximum, minimum, and mean SAT were measured at 79 weather stations of the Korea Meteorological Administration (KMA) from 2008 to 2018. As a result of the correlation analysis between SAT and LST, the maximum SAT (TMX) had a good correlation with the daytime LST of Terra MODIS, with a Pearson’s correlation coefficient (R) of 0.92 and root mean square error (RMSE) of 4.8 °C, and the minimum SAT (TMN) showed a good correlation with the nighttime LST of Terra MODIS, with an R of 0.93 and RMSE of 4.2 °C. When analyzing temperature characteristics by land use (urban, paddy, upland crop, forest, grass, wetland, bare field, and water), it was confirmed that the climate mitigation effect of the wetland and vegetation area appeared in the LSTs and the observed SAT. In the cold wave period, the average temperatures for urban and wetland areas was the highest, and the average temperature for wetland and forest was not higher than that of other land use classes. As the SAT results predicted through the LSTM model, the accuracy of the TMN during the cold wave period was 0.59 for the coefficient of determination (R2), 3.1 °C for RMSE, and 0.76 for the index of agreement (IoA), while the accuracy of the TMX for the heat wave period was 0.24 for R2, 2.23 °C for RMSE, and 0.63 for IoA.
- Published
- 2020
- Full Text
- View/download PDF
5. Evaluation of Land-Use Changes Impact on Watershed Health Using Probabilistic Approaches
- Author
-
Yonggwan Lee, Seong-Joon Kim, Soyoung Woo, Daeryong Park, Jiwan Lee, Chung-Gil Jung, and Jeehun Chung
- Subjects
geography ,geography.geographical_feature_category ,Watershed ,watershed health ,Land use ,Soil and Water Assessment Tool ,Water supply for domestic and industrial purposes ,Geography, Planning and Development ,Drainage basin ,Probabilistic logic ,multivariate normal distribution ,Hydraulic engineering ,Aquatic Science ,Biochemistry ,land-use change ,watershed health index ,Hydrology (agriculture) ,Environmental science ,Land use, land-use change and forestry ,SWAT ,Water quality ,Water resource management ,TC1-978 ,TD201-500 ,Water Science and Technology - Abstract
This study evaluated watershed health (WH) change using reference values for environmental changes at various times. Land use in 1985 was defined as the reference value under the most natural conditions, and the WH for the years 1995 to 2019 was calculated in comparison to 1985. The proposed method was used to assess the WH of 78 standard subbasins in South Korea’s Geum River Basin (GRB), where complex land-use change has occurred since 1995. For evaluating hydrology and water quality (WQ) health index, Soil and Water Assessment Tool (SWAT) and four land-use maps (1985, 1995, 2008, and 2019) were used to simulate the hydrology and WQ. A multivariate normal distribution (MND) from poor (0) to good (1) was used to assess WH based on SWAT modeling results. Based on the reference value, the WQ health from 1995 to 2019 changed to within 0.1, while the range of changes in the hydrology index was analyzed over 0.18. As a result of WH changes from 1985 to 2019, hydrological health deteriorated in high-density urbanized subbasins, while WQ health deteriorated in upland-cultivation-increased subbasins. This study provides useful information for recognizing potential WH issues related to long-term environmental changes.
- Published
- 2021
6. The relationship among meteorological, agricultural, and in situ news-generated big data on droughts
- Author
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Chung-Gil Jung, Jeehun Chung, Jiwan Lee, and Seong-Joon Kim
- Subjects
021110 strategic, defence & security studies ,Atmospheric Science ,010504 meteorology & atmospheric sciences ,business.industry ,fungi ,0211 other engineering and technologies ,food and beverages ,Forestry ,02 engineering and technology ,01 natural sciences ,Central region ,Drought risk ,Agriculture ,Natural hazard ,Typhoon ,parasitic diseases ,Earth and Planetary Sciences (miscellaneous) ,Reservoir storage ,Environmental science ,Precipitation ,Precipitation index ,business ,0105 earth and related environmental sciences ,Water Science and Technology - Abstract
The purpose of this study is to evaluate the effectiveness of agricultural drought risk management using news media data (NMD) by elucidating the relationships among the standardized precipitation index (SPI), the agricultural reservoir storage deficit index (RDI), and the NMD obtained from news sources. For a severe drought that occurred in South Korea from 2014 to 2016, the SPI and RDI were calculated, and the NMD were collected. In drought-affected areas, the receiver operating characteristic (ROC) was used to assess the performance of NMD and to replicate the temporal drought trends using the SPI and RDI. The ROC analysis of NMD and drought indices showed a hit rate above 0.65, and the hit rate showed the highest value (0.75) in SPI-12. The central region of South Korea showed the highest number of news postings during the 12 months in which SPI-12 remained in the severe drought category. For the southern region of South Korea, large amounts of NMD were collected when the RDI had the lowest value. The amount of NMD was sensitive to spring drought from March, the delayed Jangma in late June, the dry Jangma in July, and the absence of a typhoon in September of 2015. The study results showed that NMD are closely related to both meteorological drought and agricultural drought conditions. As NMD represent the in situ drought experienced by the people, these data can provide a useful drought indicator along with government-published drought information.
- Published
- 2019
7. Correlation Analysis between Air Temperature and MODIS Land Surface Temperature and Prediction of Air Temperature Using TensorFlow Long Short-Term Memory for the Period of Occurrence of Cold and Heat Waves
- Author
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Won-Jin Jang, Seong-Joon Kim, Yonggwan Lee, Jeehun Chung, and Siwoon Lee
- Subjects
Daytime ,Coefficient of determination ,010504 meteorology & atmospheric sciences ,Correlation coefficient ,Land surface temperature ,TensorFlow ,0211 other engineering and technologies ,Wetland ,02 engineering and technology ,Atmospheric sciences ,01 natural sciences ,air temperature prediction ,heat and cold waves ,long short-term memory ,MODIS land surface temperature ,lcsh:Science ,021101 geological & geomatics engineering ,0105 earth and related environmental sciences ,geography ,geography.geographical_feature_category ,Cold wave ,Vegetation ,General Earth and Planetary Sciences ,Environmental science ,lcsh:Q ,Moderate-resolution imaging spectroradiometer - Abstract
The purpose of this study is to analyze the correlation between surface air temperature (SAT) and land surface temperature (LST) based on land use when heat and cold waves occur and to predict the distribution of SAT using the long short-term memory (LSTM) of TensorFlow. For the correlation analysis, the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) daytime and nighttime LST and maximum, minimum, and mean SAT were measured at 79 weather stations of the Korea Meteorological Administration (KMA) from 2008 to 2018. As a result of the correlation analysis between SAT and LST, the maximum SAT (TMX) had a good correlation with the daytime LST of Terra MODIS, with a Pearson’s correlation coefficient (R) of 0.92 and root mean square error (RMSE) of 4.8 °C, and the minimum SAT (TMN) showed a good correlation with the nighttime LST of Terra MODIS, with an R of 0.93 and RMSE of 4.2 °C. When analyzing temperature characteristics by land use (urban, paddy, upland crop, forest, grass, wetland, bare field, and water), it was confirmed that the climate mitigation effect of the wetland and vegetation area appeared in the LSTs and the observed SAT. In the cold wave period, the average temperatures for urban and wetland areas was the highest, and the average temperature for wetland and forest was not higher than that of other land use classes. As the SAT results predicted through the LSTM model, the accuracy of the TMN during the cold wave period was 0.59 for the coefficient of determination (R2), 3.1 °C for RMSE, and 0.76 for the index of agreement (IoA), while the accuracy of the TMX for the heat wave period was 0.24 for R2, 2.23 °C for RMSE, and 0.63 for IoA.
- Published
- 2020
- Full Text
- View/download PDF
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