• Korean Journal of Remote Sensing
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• v.36 no.5_2
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• pp.989-1006
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• 2020

Building change monitoring based on building detection is one of the most important fields in terms of monitoring artificial structures using high-resolution multi-temporal images such as CAS500-1 and 2, which are scheduled to be launched. However, not only the various shapes and sizes of buildings located on the surface of the Earth, but also the shadows or trees around them make it difficult to detect the buildings accurately. Also, a large number of misdetection are caused by relief displacement according to the azimuth and elevation angles of the platform. In this study, object-based building detection was performed using the azimuth angle of the Sun and the corresponding main direction of shadows to improve the results of building change detection. After that, the platform's azimuth and elevation angles were used to detect changed buildings. The object-based segmentation was performed on a high-resolution imagery, and then shadow objects were classified through the shadow intensity, and feature information such as rectangular fit, Gray-Level Co-occurrence Matrix (GLCM) homogeneity and area of each object were calculated for building candidate detection. Then, the final buildings were detected using the direction and distance relationship between the center of building candidate object and its shadow according to the azimuth angle of the Sun. A total of three methods were proposed for the building change detection between building objects detected in each image: simple overlay between objects, comparison of the object sizes according to the elevation angle of the platform, and consideration of direction between objects according to the azimuth angle of the platform. In this study, residential area was selected as study area using high-resolution imagery acquired from KOMPSAT-3 and Unmanned Aerial Vehicle (UAV). Experimental results have shown that F1-scores of building detection results detected using feature information were 0.488 and 0.696 respectively in KOMPSAT-3 image and UAV image, whereas F1-scores of building detection results considering shadows were 0.876 and 0.867, respectively, indicating that the accuracy of building detection method considering shadows is higher. Also among the three proposed building change detection methods, the F1-score of the consideration of direction between objects according to the azimuth angles was the highest at 0.891.

• Journal of Korea Water Resources Association
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• v.40 no.12
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• pp.921-930
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• 2007

The objective of this study is to present temporal-spatial variation of water resources on climate change impacts using the IPCC SRES A2 scenario and dynamical downscaling of the results (using the MM5 model with a resolution of 27km by 27km) at 139 sub-basins in Korea. The variation of runoff shows differences in the change of rate according to the each sub-basins and analysis durations. It has increased in the sub-basins located in Han river basin and east part of it, the other basins have decreased. In seasonal analysis, runoff in autumn and winter have increased, while in spring and summer have decreased. The results of frequency analyzing classified runoff(Low flow(Q$\leq$5mm), Normal flow(5$\geq$100mm)) show that low flow increase in most of the sub-basins for 2031-2060 and 2061-2090. In the case of high flow, it have higher frequency ranging from -100% to 500% than low flow. Regardless of the variation of mean runoff, maximum discharge appeared to be increase in process of time. The regression method is used to figure out the relationship between the rate of runoff change and mean temperature, mean precipitation under A2 scenario. The mean actual evapotranspirations from the regression equations increased by 3.4$\sim$5.3% for the change of $1^{\circ}C$. Also, for the precipitation change of $\pm$10%, runoff variety range is -18.2$\sim$+12.4% in Han River, -21.6$\sim$+14.6% in Nakdong River, -17.5$\sim$+11.5% in Gum River, -18.4$\sim$+10.6% in Sumjin River, -19.9$\sim$+12.7% Youngsan River basin.

• Journal of the Korean Society for Marine Environment & Energy
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• v.12 no.1
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• pp.35-46
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• 2009

In order to investigate spatial and temporal distributional characteristics of major water qualities in the Saemangeum area during the Saemangeum dike construction, salinity, COD, dissolved nutrients(DIN, Silicate) and heavy metals were analyzed from the surface water collected in April, May, August and November 2002. The overall value of Salinity, COD, DIN, and silicate in surface waters were in the range of $13.08{\sim}31.96\;psu$, $0.12{\sim}3.43\;mg/L$, $0.001{\sim}2.638\;mg/L$, and $0.010{\sim}3.181\;mg/L$, respectively. The COD and DIN in each survey showed the highest concentration at the mouth of Mangyeong river estuary(St. 1) where freshwater flow into the Saemangeum area. The concentrations of nutrients were high in the inner part of the Saemangeum dike with low-salinity, and low nutrients in the outer part of the dike with high-salinity, which strongly indicated that concentrations were adjusted by physical mixing. The ranges of dissolved metals and acid-soluble Hg in surface seawater were $0.006{\sim}0.115{\mu}g/L$ for Co, $0.26{\sim}0.114{\mu}g/L$ for Ni, $0.14{\sim}0.93{\mu}g/L$ for Cu, $0.04{\sim}0.53{\mu}g/L$ for Zn, $0.010{\sim}0.043{\mu}g/L$ for Cd, $0.010{\sim}0.795{\mu}g/L$ for Pb, and $0.25{\sim}4.16{\mu}g/L$ for Hg. The highest concentrations of some metals except for Cd were found at the estuary(Sts. 1 or 3). In most cases, a decreasing order of metal concentrations towards open sea(low-salinity$\rightarrow$high-salinity) was observed and showed positive relationship with DIN and silicate caused by land base pollutants input. On the other hand, due to Cd desorption from suspended solids in saline water, dissolved Cd concentrations were high in high-salinity area and low in low-salinity. In November, Co, Zn, Cu and Pb were relatively high in the northern area of the outer-side of Saemangeum, which was only influenced by the Geum river discharge. The concentrations of most dissolved metals of this study were lower than those of the past data in this area, but higher than those in Lena river estuary under the pristine environment.

• Korean Journal of Remote Sensing
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• v.27 no.4
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• pp.467-480
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• 2011

Spatial and temporal variabilities of NPP(Net Primary Production) retrieved from two satellite instruments, AVHRR(Advanced Very High Resolution Radiometer, 1981-2000) and MODIS(MODerate-resolution Imaging Spectroradiometer, 2000-2006), were investigated. The range of mean NPP from A VHRR and MODIS were estimated to be 894-1068 $g{\cdot}C/m^2$/yr and 610-694.90 $g{\cdot}C/m^2$/yr, respectively. The discrepancy of NPP between the two instruments is about 325 $g{\cdot}C/m^2$/yr, and MODIS product is generally closer to the ground measurement than AVHRR despite the limitation in direct comparison such as spatial resolution and vegetation classification. The higher NPP values over South Korea are related to the regions with higher biomass (e.g., mountains) and higher annual temperature. The interannual NPP trends from the two satellite products were computed, and both mean annual trends show continuous NPP increase; 2.14 $g{\cdot}C/m^2$/yr from AVHRR(1981-2000) and 6.08 $g{\cdot}C/m^2$/yr from MODIS (2000-2006) over South Korea. Specifically, the higher increasing trends over the Southwestern region are likely due to the increasing productivity of crop fields from sufficient irrigation and fertilizer use. The retrieved NPP shows a closer relationship between monthly temperature and precipitation, which results in maximum correlation during summer monsoons. The difference in the detection wavelength and model schemes during the retrieval can make a significant difference in the satellite products, and a better accuracy in the meterological and land use data and modeling applications will be necessary to improve the satellite-based NPP data.

• Korean Journal of Remote Sensing
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• v.35 no.6_1
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• pp.919-932
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• 2019

Fine particulate matter (PM2.5) is not only affected by anthropogenic emissions, but also intensifies, migrates, decreases by hydrometeorological factors. Therefore, it is essential to understand relationships between the hydrometeorological factors and PM2.5 concentration. In Korea, PM2.5 concentration is measured at the ground observatories and estimated data are given to locations where observatories are not present. In this way, the data is not suitable to represent an area, hence it is impossible to know accurate concentration at such locations. In addition, it is hard to trace migration, intensification, reduction of PM2.5. In this study, we analyzed the relationships between hydrometeorological factors, acquired from Global Land Data Assimilation System (GLDAS), and PM2.5 by means of Bayesian Model Averaging (BMA). By BMA, we also selected factors that have meaningful relationship with the variation of PM2.5 concentration. 4 PM2.5 concentration models for different seasons were developed using those selected factors, with Aerosol Optical Depth (AOD) from MODerate resolution Imaging Spectroradiometer (MODIS). Finally, we mapped the result of the model, to show spatial distribution of PM2.5. The model correlated well with the observed PM2.5 concentration (R ~0.7; IOA ~0.78; RMSE ~7.66 ㎍/㎥). When the models were compared with the observed PM2.5 concentrations at different locations, the correlation coefficients differed (R: 0.32-0.82), although there were similarities in data distribution. The developed concentration map using the models showed its capability in representing temporal, spatial variation of PM2.5 concentration. The result of this study is expected to be able to facilitate researches that aim to analyze sources and movements of PM2.5, if the study area is extended to East Asia.

• Korean Journal of Agricultural and Forest Meteorology
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• v.2 no.2
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• pp.47-61
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• 2000

Agroclimatic zoning was done for paddy rice culture in North Korea based on a simulation experiment. Daily weather data for the experiment were generated by 3 steps consisting of spatial interpolation based on topoclimatological relationships, zonal summarization of grid cell values, and conversion of monthly climate data to daily weather data. Regression models for monthly climatological temperature estimation were derived from a statistical procedure using monthly averages of 51 standard weather stations in South and North Korea (1981-1994) and their spatial variables such as latitude, altitude, distance from the coast, sloping angle, and aspect-dependent field of view (openness). Selected models (0.4 to 1.6$^{\circ}C$ RMSE) were applied to the generation of monthly temperature surface over the entire North Korean territory on 1 km$\times$l km grid spacing. Monthly precipitation data were prepared by a procedure described in Yun (2000). Solar radiation data for 27 North Korean stations were reproduced by applying a relationship found in South Korea ([Solar Radiation, MJ m$^{-2}$ day$^{-1}$ ] =0.344 + 0.4756 [Extraterrestrial Solar Irradiance) + 0.0299 [Openness toward south, 0 - 255) - 1.307 [Cloud amount, 0 - 10) - 0.01 [Relative humidity, %), $r^2$=0.92, RMSE = 0.95 ). Monthly solar irradiance data of 27 points calculated from the reproduced data set were converted to 1 km$\times$1 km grid data by inverse distance weighted interpolation. The grid cell values of monthly temperature, solar radiation, and precipitation were summed up to represent corresponding county, which will serve as a land unit for the growth simulation. Finally, we randomly generated daily maximum and minimum temperature, solar irradiance and precipitation data for 30 years from the monthly climatic data for each county based on a statistical method suggested by Pickering et a1. (1994). CERES-rice, a rice growth simulation model, was tuned to accommodate agronomic characteristics of major North Korean cultivars based on observed phenological and yield data at two sites in South Korea during 1995~1998. Daily weather data were fed into the model to simulate the crop status at 183 counties in North Korea for 30 years. Results were analyzed with respect to spatial and temporal variation in yield and maturity, and used to score the suitability of the county for paddy rice culture.

• Journal of Oral Medicine and Pain
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• v.37 no.3
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• pp.183-188
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• 2012

Previous studies of the relationship of TMJ signs and symptoms in elderly people have provided inconsistent findings. The objective of this study was to retrospectively analyze the prevalence of signs and symptoms of temporomandibular disorders(TMD). Additionally, young subjects were examined as a control group. Forty old patients (28 female, 12 male, mean age: $65.2{\pm}2.5$ years) and forty young patients (30 female, 10 male, mean age: $23.3{\pm}2.6$ years) clinically diagnosed with TMD were screened. Patient records were analyzed regarding: pain on chief complain, amount of range of mouth opening, TMJ noises(clicking sounds, crepitus), pain on palpation of the TMJ and masticatory muscles and neck and upper back muscles. Differences between the groups were assessed using t-test and the chi-squared test. (SPSS v.17) P value <0.05 was considered statistically significant. Geriatric subjects more often exhibited crepitus on mouth opening (25%), muscular palpation pain of masseter muscles (82.5%) and temporal muscles(60%). In contrast, young subjects more frequently exhibited joint sounds (62.5%), more amount of range of passive mouth opening (p=0.043). It was found that the younger subjects (82.5%) and the older subjects (87.5%) suffered from subjective sign (orofacial pain on chief complain). There were not statistically significant relationships between orofacial pain (VAS) and the groups. Differences between the groups with respect to joint sounds, muscular palpation pain and mandibular range of motion were significant. Although older subjects more frequently exhibited objective signs (crepitus on opening, pain on muscular palpation) of TMD, younger subjects more frequently objective signs (clicking sound on mouth opening, amount of mandibular range of motion).

• Journal of Environmental Policy
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• v.7 no.4
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• pp.35-55
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• 2008

Assessing vulnerability to climate change is the first step to take when setting up appropriate adaptation strategies. Adaptive capacity to climate change is the important factor comprising vulnerability. An adaptive capacity index in agricultural water management system was developed considering agricultural water supply and demand for rice production in Jeolla-do, Korea. The agricultural water supply was assumed to be equal to the amount of water stored in the major agricultural reservoirs, while data on the agricultural water demand was obtained from the dynamic simulation results by Korea Agriculture Corporation(KAC). The spatial unit for analysis was conducted at the county(Si, Gun, Gu) level and temporal scale was based on every month from 1991-2003. Adaptive capacity for drought stress index(ACDS index) was calculated as the percentage of data points where the irrigated water supply was greater than the crop water demand. The ACDS index was compared with SWSCI(Standard Water Storage Capacity Index) and the relationship showed high degree of fit($R^2$=0.84) using the exponential function, indicating that the developed ACDS index is useful for evaluating the status of the balance between agricultural water supply and demand, especially for the small sized agricultural reservoirs. This study provided the methodological basis for developing climate change vulnerability index in agricultural water system which is projected to be more frequently exposed to drought condition in the future due to climate change. Further research should be extended to the study on the water demand of the crops other than rice and to the projection of the change in ACDS index in the future.

• Korean Journal of Remote Sensing
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• v.25 no.1
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• pp.31-44
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• 2009

The objective of this study was to measure backscattering coefficients of paddy rice using a L-, C-, and X-band scatterometer system with full polarization and various angles during the rice growth period and to relate backscattering coefficients to rice growth parameters. Radar backscattering measurements of paddy rice field using multifrequency (L, C, and X) and full polarization were conducted at an experimental field located in National Academy of Agricultural Science (NAAS), Suwon, Korea. The scatterometer system consists of dual-polarimetric square horn antennas, HP8720D vector network analyzer ($20\;MHz{\sim}20\;GHz$), RF cables, and a personal computer that controls frequency, polarization and data storage. The backscattering coefficients were calculated by applying radar equation for the measured at incidence angles between $20^{\circ}$ and $60^{\circ}$ with $5^{\circ}$ interval for four polarization (HH, VV, HV, VH), respectively. We measured the temporal variations of backscattering coefficients of the rice crop at L-, C-, X-band during a rice growth period. In three bands, VV-polarized backscattering coefficients were higher than hh-polarized backscattering coefficients during rooting stage (mid-June) and HH-polarized backscattering coefficients were higher than VV-, HV/VH-polarized backscattering coefficients after panicle initiation stage (mid-July). Cross polarized backscattering coefficients in X-band increased towards the heading stage (mid-Aug) and thereafter saturated, again increased near the harvesting season. Backscattering coefficients of range at X-band were lower than that of L-, C-band. HH-, VV-polarized ${\sigma}^{\circ}$ steadily increased toward panicle initiation stage and thereafter decreased, and again increased near the harvesting season. We plotted the relationship between backscattering coefficients with L-, C-, X-band and rice growth parameters. Biomass was correlated with L-band hh-polarization at a large incident angle. LAI (Leaf Area Index) was highly correlated with C-band HH- and cross-polarizations. Grain weight was correlated with backscattering coefficients of X-band VV-polarization at a large incidence angle. X-band was sensitive to grain maturity during the post heading stage.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.959-974
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• 2021

Forel-Ule Index (FUI) is an index which classifies the colors of inland and seawater exist in nature into 21 gradesranging from indigo blue to cola brown. FUI has been analyzed in connection with the eutrophication, water quality, and light characteristics of water systems in many studies, and the possibility as a new water quality index which simultaneously contains optical information of water quality parameters has been suggested. In thisstudy, Ocean Colour-Climate Change Initiative (OC-CCI) based 4 km FUI was spatially downscaled to the resolution of 500 m using the Geostationary Ocean Color Imager (GOCI) data and Random Forest (RF) machine learning. Then, the RF-derived FUI was examined in terms of its correlation with various water quality parameters measured in coastal areas and its spatial distribution and seasonal characteristics. The results showed that the RF-derived FUI resulted in higher accuracy (Coefficient of Determination (R²)=0.81, Root Mean Square Error (RMSE)=0.7784) than GOCI-derived FUI estimated by Pitarch's OC-CCI FUI algorithm (R²=0.72, RMSE=0.9708). RF-derived FUI showed a high correlation with five water quality parameters including Total Nitrogen, Total Phosphorus, Chlorophyll-a, Total Suspended Solids, Transparency with the correlation coefficients of 0.87, 0.88, 0.97, 0.65, and -0.98, respectively. The temporal pattern of the RF-derived FUI well reflected the physical relationship with various water quality parameters with a strong seasonality. The research findingssuggested the potential of the high resolution FUI in coastal water quality management in the Korean Peninsula.