• Journal of Korea Water Resources Association
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• v.49 no.12
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• pp.981-993
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• 2016

This study explains the GIS database of flood inundation area developed for Samsung-1 Drainage Sector, Seoul, Korea. The XP-SWMM dual drainage model was developed for the study area, and the time series observed at the watershed outlet was used to obtain the watershed time of concentration and to calibrate the XP-SWMM model. The rainfall scenario was developed by dividing the 40 minute watershed time of concentration into two 20-minute time steps and then applying the gradually increasing 5 mm/hr interval rainfall intensity to each of the time step up to 200 mm/hr, which is the probable maximum precipitation of the study area. The developed rainfall scenarios was used as the input of the XP-SWMM model to obtain the database of the flood inundation area. The analysis on the developed GIS database revealed that: (1) For the same increment of the rainfall, the increase of the flooded area can be different, and this was caused by topographic characteristics and spatial formation of pipe network of the study area; (2) For the same flooded area, the spatial extent can be significantly different depending on the temporal distribution of rainfall; and (3) For the same amount of the design rainfall, the flood inundation area and the extent can be significantly different depending on the temporal distribution of rainfall.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.1
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• pp.52-61
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• 2004

Korea Water Resources Corporation carried out LiDAR survey to construct detailed terrain data for flood mapping and it is expected that much money is required in flood mapping of all over the country. Therefore, it is desirable to use NGIS digital map to construct preliminary modelling data for selection of flood mapping area. And the analysis of DEM error with respect to scale of digital map is necessary for the sake of applying digital map as the input data of flood mapping. We compared DEM from digital map with DEM from LiDAR survey. Especially we analyzed DEM error characteristics that is occurred with respect to the interpolation method that is used to construct DEM from TIN of digital map. As a result of analysis, digital map(1:1,000) showed smaller error than digital map(1:5,000) and DEM applying linear interpolation showed smaller error than DEM applying quintic interpolation. Especially, variation of DEM error by cell resolution was evaluated as very slight because urban district was composed of gentle slope.

• Korean Journal of Remote Sensing
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• v.22 no.2
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• pp.111-121
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• 2006

The classification using spectral angle is a new approach based on the fact that the spectra of the same type of surface objects in RS data are approximately linearly scaled variations of one another due to atmospheric and topographic effects. There are many researches on the unsupervised classification using spectral angle recently. Nevertheless, there are only a few which consider the characteristics of Hyperspectral data. On this study, we propose the ISOMUSAC(Iterative Self-Organizing Modified Unsupervised Spectral Angle Classification) which can supplement the defects of previous unsupervised spectral angle classification. ISOMUSAC uses the Angle Division for the selection of seed points and calculates the center of clusters using spectral angle. In addition, ISOMUSAC perform the iterative merging and splitting clusters. As a result, the proposed algorithm can reduce the time of processing and generate better classification result than previous unsupervised classification algorithms by visual and quantitative analysis. For the comparison with previous unsupervised spectral angle classification by quantitative analysis, we propose Validity Index using spectral angle.

• Journal of the Korean earth science society
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• v.40 no.2
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• pp.149-162
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• 2019

In the macro-tide open coast of the Korean western coast, typhoon effects were investigated in terms of variations on topography, surface sediment, and sedimentary environment, which appeared before and after the typhoon Kompasu of 2010. The Kompasu of small size and strong intensity landed on the southwestern coast of the Korean Peninsula and passed across the inland between September 1st and 2nd in 2010. Topography and surface sediments before and after the typhoon were measured and sampled along the survey line of 22 sites in the Gochang Donghori intertidal flat. The intertidal area was divided into high tidal zone, middle tidal zone, and lower tidal zone on the basis of mean high water level, mean sea level, and mean low water level. Topographic variation before and after the typhoon represented deposition of average 0.03 m in high tidal zone, erosion of average -0.15 m in middle tidal zone, and erosion of average -0.39 m in lower tidal zone, respectively. Surface sediments of the intertidal flat consisted mainly of fine to medium sands, and the ratio of fine sand was the largest both before and after the typhoon. Surface sediments after the typhoon became finer in mean grain size showing well sorting rather than those before the typhoon.

• Journal of Veterinary Clinics
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• v.36 no.1
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• pp.7-14
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• 2019

In South Korea, six large outbreaks of highly pathogenic avian influenza (HPAI) have occurred since the first confirmation in 2003 from chickens. For the past 15 years, HPAI outbreaks have become an annual phenomenon throughout the country and has extended to wider regions, across rural and urban environments. An understanding of the spatial epidemiology of HPAI occurrence is essential in assessing and managing the risk of the infection; however, local spatial variations of relationship between HPAI incidences in Korea and related risk factors have rarely been derived. This study examined whether spatial heterogeneity exists in this relationship, using a geographically weighted Poisson regression (GWPR) model. The outcome variable was the number of HPAI-positive farms at 252 Si-Gun-Gu (administrative boundaries in Korea) level notified to government authority during the period from January 2014 to April 2016. This response variable was regressed to a set of sociodemographic and topographic predictors, including the number of wild birds infected with HPAI virus, the number of wintering birds and their species migrated into Korea, the movement frequency of vehicles carrying animals, the volume of manure treated per day, the number of livestock farms, and mean elevation. Both global and local modeling techniques were employed to fit the model. From 2014 to 2016, a total of 403 HPAI-positive farms were reported with high incidence especially in western coastal regions, ranging from 0 to 74. The results of this study show that local model (adjusted R-square = 0.801, AIC = 954.5) has great advantages over corresponding global model (adjusted R-square = 0.408, AIC = 2323.1) in terms of model fitting and performance. The relationship between HPAI incidence in Korea and seven predictors under consideration were significantly spatially non-stationary, contrary to assumptions in the global model. The comparison between global Poisson and GWPR results indicated that a place-specific spatial analysis not only fit the data better, but also provided insights into understanding the non-stationarity of the associations between the HPAI and associated determinants. We demonstrated that an empirically derived GWPR model has the potential to serve as a useful tool for assessing spatially varying characteristics of HPAI incidences for a given local area and predicting the risk area of HPAI occurrence. Considering the prominent burden of HPAI this study provides more insights into spatial targeting of enhanced surveillance and control strategies in high-risk regions against HPAI outbreaks.

• Journal of Wetlands Research
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• v.21 no.2
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• pp.125-131
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• 2019

The Nakdong Estuary has experienced hydraulic and topographic changes over the last century, which have had negative effects of habitat loss and fragmentation. The population of Scirpus planiculmis, a major food plant for wintering birds in Nakdong Estuary, has decreased over the last decade. To identify factors that influence S. planiculmis population, 6 short core samples (about 30cm) were collected in June and August, 2018. The sand percentage was over 80% in every samples and the average sediment salinity in June and August were $17.8{\pm}1.12psu$ and $18.4{\pm}1.83psu$, respectively. ${\delta}^{13}C$ of sediment cores varied from -25.4‰ to -22.6‰ which fall within the estuarine particulate organic matters. In cores collected in Eulsuk area, the highest ${\delta}^{13}C$ values were observed at the surface (0~1cm) indicating inputs of marine POM (particulate organic matter) to the Nakdong Estuary. No significant difference between vegetation and non-vegetation stations was observed in every items we investigated which might indicate that the physicochemical environment of vegetation area is almost same as that of non-vegetation area. Therefore, the high sand percentage and sediment salinity of Nakdong Estuary might affect the reduction in S. planiculmis population.

• Journal of Wetlands Research
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• v.24 no.4
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• pp.354-366
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• 2022

To analyze the distribution of plant communities growing in river wetlands and the relationship between biotic and abiotic environmental factors, plant communities and environmental factors were investigated in river wetlands in the Boseong River. The Boseong River Wetland, the research site, consists of Hwapyeong Wetland, Bangujeong Wetland, and Seokgok Wetland. From June to September 2022, a plant community survey was conducted from the perspective of physiognomical vegetation, and the coverage of the emerging species followed the Braun-Blanquet scale. Plant species and the coverage of each species were recorded in the quadrant for plant community survey, and the cover of the quadrant, the total number of species, and the number of exotic species were measured as biological factors. As abiotic factors, altitude, orientation, inclination, soil texture, litter layer depth, dominant species diameter at breast height, and topography were recorded. In a total of 50 square plots, the most common Salix koreensis and Phragmites japonicus communities were found, and the community with the highest Shannon species diversity index was Phragmites japonicus-Echinochloa caudata community. As a result of ordination analysis by DCCA, the most significant clusters were separated according to topographic factors such as leeve, leeve slope, upper floodplain, lower floodplain, upper waterside, middle waterside, lower waterside, river island and opem water. As rare plants that need to be preserved in river wetlands, Hydrocharis dubia and Penthorum chinense were found in lower waterside, and it was found that the management of the river in the reservoir is necessary in line with the topographical distribution of ecosystem-disrupting plants, such as Paspalum distichum var. indutum.

• Journal of the Korean earth science society
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• v.41 no.6
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• pp.647-657
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• 2020

Infrasound signals associated with the 29 May 2004 offshore Uljin earthquake (Mw 5.1) were recorded at infrasound arrays of CHNAR (epicentral distance of 321 km) and TJNAR (256 km). Back-azimuths, indicating the directions to source locations, varied more than 28° broadly for the long-lasting signals over several minutes. From the analysis of the back-projecting location method and attenuation correction for infrasound propagation, the infrasound waves were to be generated by the interaction (diffraction) between seismic waves and topography in an area of ~4,600 ㎢ connecting the Samcheok-Uljin-Pohang regions. The maximum sound source pressure (BSP) was estimated to be 11.1 Pa. This result was consistent with the peak sound pressure (PSP) calculated by the Rayleigh integral approximation to the peak ground acceleration (PGA) dataset. In addition, the minimum PGA that was detectable at the two arrays was estimated to be ~3.0 cm s-2. Although the earthquake occurred offshore, diffracted infrasound signals were effectively generated by ground motions when seismic surface waves passed through high-topographic regions in the eastern Korean Peninsula. The relationship between infrasound source pressure and PGA can be applicable to characterize the ground motions in areas with insufficient seismological observatories.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.511-521
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• 2022

Cloud detection and removal from satellite images is an essential process for topographic observation and analysis. Threshold-based cloud detection techniques show stable performance because they detect using the physical characteristics of clouds, but they have the disadvantage of requiring all channels' images and long computational time. Cloud detection techniques using deep learning, which have been studied recently, show short computational time and excellent performance even using only four or less channel (RGB, NIR) images. In this paper, we confirm the performance dependence of the deep learning network according to the heterogeneous learning dataset with different resolutions. The DeepLabV3+ network was improved so that channel features of cloud detection were extracted and learned with two published heterogeneous datasets and mixed data respectively. As a result of the experiment, clouds' Jaccard index was low in a network that learned with different kind of images from test images. However, clouds' Jaccard index was high in a network learned with mixed data that added some of the same kind of test data. Clouds are not structured in a shape, so reflecting channel features in learning is more effective in cloud detection than spatial features. It is necessary to learn channel features of each satellite sensors for cloud detection. Therefore, cloud detection of heterogeneous sensors with different resolutions is very dependent on the learning dataset.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.571-585
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• 2022

As the threat of natural disasters such as droughts, floods, forest fires, and landslides increases due to climate change, social demand for high-resolution soil moisture retrieval, such as Synthetic Aperture Radar (SAR), is also increasing. However, the domestic environment has a high proportion of mountainous topography, making it challenging to retrieve soil moisture from SAR data. This study evaluated the usability of Sentinel-1 SAR, which is applied with the Artificial Neural Network (ANN) technique, to retrieve soil moisture. It was confirmed that the backscattering coefficient obtained from Sentinel-1 significantly correlated with soil moisture behavior, and the possibility of stand-alone use to correct vegetation effects without using auxiliary data observed from other satellites or observatories. However, there was a large difference in the characteristics of each site and topographic group. In particular, when the model learned on the mountain and at flat land cross-applied, the soil moisture could not be properly simulated. In addition, when the number of learning points was increased to solve this problem, the soil moisture retrieval model was smoothed. As a result, the overall correlation coefficient of all sites improved, but errors at individual sites gradually increased. Therefore, systematic research must be conducted in order to widely apply high-resolution SAR soil moisture data. It is expected that it can be effectively used in various fields if the scope of learning sites and application targets are specifically limited.