• Journal of the Korean Society of Environmental Restoration Technology
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• v.22 no.5
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• pp.1-12
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• 2019

It is important to measure the height of trees as an essential element for assessing the forest health in urban areas. Therefore, an automated method that can measure the height of individual tree as a three-dimensional forest information is needed in an extensive and dense forest. Since airborne LiDAR dataset is easy to analyze the tree height(z-coordinate) of forests, studies on individual tree height measurement could be performed as an assessment forest health. Especially in urban forests, that adversely affected by habitat fragmentation and isolation. So this study was analyzed to measure the height of individual trees for assessing the urban forests health, Furthermore to identify environmental factors that affect forest growth. The survey was conducted in the Mt. Bongseo located in Seobuk-gu. Cheonan-si(Middle Chungcheong Province). We segment the individual trees on coniferous by automatic method using the airborne LiDAR dataset of the two periods (year of 2016 and 2017) and to find out individual tree growth. Segmentation of individual trees was performed by using the watershed algorithm and the local maximum, and the tree growth was determined by the difference of the tree height according to the two periods. After we clarify the relationship between the environmental factors affecting the tree growth. The tree growth of Mt. Bongseo was about 20cm for a year, and it was analyzed to be lower than 23.9cm/year of the growth of the dominant species, Pinus rigida. This may have an adverse effect on the growth of isolated urban forests. It also determined different trees growth according to age, diameter and density class in the stock map, effective soil depth and drainage grade in the soil map. There was a statistically significant positive correlation between the distance to the road and the solar radiation as an environmental factor affecting the tree growth. Since there is less correlation, it is necessary to determine other influencing factors affecting tree growth in urban forests besides anthropogenic influences. This study is the first data for the analysis of segmentation and the growth of the individual tree, and it can be used as a scientific data of the urban forest health assessment and management.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.599-610
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• 2020

The AED (Automated External Defibrillator) is not evaluated for spatial accuracy and temporal availability even if it is located within a building or a specific area that needed necessary to partition by spatial analysis and location allocation analysis. As a result of the analysis, the spatial analysis was performed using the existing public data of AED with applied the GIS location analysis method. A public institution (119 safety center, police box) was selected as a candidate for a public AED base that can operate 24 hours a day, 365 days a year according to the characteristics of each residential area. In addition, Thiessen Polygons were created for each candidate site and divided by regions. In the analysis of the service was analyzed regional in terms of accessibility to emergency medical services in consideration of the characteristics of AED, that emergency vehicles could arrive within 4 minutes of the time required for emergency medical treatment in most areas of the study area, but it did not areas outside of the city center. As a result, It was found that the operation of the AED base service center centered on vehicles of public institutions is effective for responding to AED patients at night and weekend hours. 19 Safety Center under and police box the jurisdiction of Daegu City to establish an AED service center for public institutions, location-based distance, attribute analysis, and minimization of overlapping areas that the method of using a vehicle appeared more efficient than using the existing walking type AED.

• Journal of the Korean earth science society
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• v.44 no.2
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• pp.135-147
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• 2023

Satellite-observed significant wave heights (SWHs), which are widely used to understand the response of the ocean to climate change, require long-term and continuous validation. This study examines the accuracy and error characteristics of SWH observed by nine satellite altimeters in the North Pacific and North Atlantic Ocean for 25 years (1992-2016). A total of 137,929 matchups were generated to compare altimeter-observed SWH and in-situ measurements. The altimeter SWH showed a bias of 0.03 m and a root mean square error (RMSE) of 0.27 m, indicating relatively high accuracy in the North Pacific and North Atlantic Ocean. However, the spatial distribution of altimeter SWH errors showed notable differences. To better understand the error characteristics of altimeter-observed SWH, errors were analyzed with respect to in-situ SWH, time, latitude, and distance from the coast. Overestimation of SWH was observed in most satellite altimeters when in-situ SWH was low, while underestimation was observed when in-situ SWH was high. The errors of altimeter-observed SWH varied seasonally, with an increase during winter and a decrease during summer, and the variability of errors increased at higher latitudes. The RMSEs showed high accuracy of less than 0.3 m in the open ocean more than 100 km from the coast, while errors significantly increased to more than 0.5 m in coastal regions less than 15 km. These findings underscore the need for caution when analyzing the spatio-temporal variability of SWH in the global and regional oceans using satellite altimeter data.

• Journal of Environmental Health Sciences
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• v.48 no.6
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• pp.298-305
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• 2022

Background: The concentration of air pollutants as measured by the Air Quality Monitoring System (AQMS) is not an accurate population exposure level since actual human activities and temporal and spatial variability need to be considered. Therefore, to increase the accuracy of exposure assessment, the population should be considered. However, it is difficult to obtain population data due to limitations such as personal information. Objectives: The existing population defined in this study is the number of people in each region's grid. The purpose is to provide a methodology for evaluating exposure to PM_2.5 through existing population data provided by the National Geographic Information Institute. Methods: The selected study period was from October 26 to October 28, 2021. Using PM_2.5 concentration data measured at the Sensor-based Air Monitoring Station (SAMS) installed in Guro-gu and Wonju-si, the concentration for each grid was estimated by applying inverse distance weights through QGIS version 3.22. Considering the existing population, population-weighted average concentration (PWAC) was calculated and the exposure level of the population was compared by region. Results: The outdoor PM_2.5 concentration as measured through the SAMS was high in Wonju-si on all three days. Wonju-si showed an average 22% higher PWAC than Guro-gu. As a result of comparing the PWAC and outdoor PM_2.5 concentration by region, the PWAC in Guro-gu was 1~2% higher than the observed value, but it was almost the same. Conversely, observations of Wonju-si were 10.1%, 11.3%, and 8.2% higher than PWAC. Conclusions: It is expected that the Geographic Information System (GIS) method and the existing population will be used to evaluate the exposure level of a population with a narrow activity radius in further research. In addition, based on this study, it is judged that research on exposure to environmental pollutants and risk assessment methods should be expanded.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.9
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• pp.141-149
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• 2017

Numerous products are on the market every day and consumption is becoming increasingly polarized. Some products have been introduced to the market for the first time and others are the existing products that have upgraded performance. For companies, new products must be released constantly to prevent losing existing customers and to increase loyalty. However, when companies released new product, they communicate consumer brand name and core benefits of the new product. Moreover, if a new product fails, the amount that the company has to pay is bound to grow. So companies often use brand extension strategies that use the names of famous brands that are already loved by their customers for new products. In this study, the effect of extension similarity, time of release, and message type on brand extension was investigated. Result shows that using abstract messages rather than specific messages is more effective when similarities with existing brands are poor. In particular, the closer the release period is, the more effective these effects are. However, in case of extending the brand with high similarity products, it is effective to focus on concrete messages when the release time is near, and to communicate abstract messages when the release time is long. This result suggests that companies should take into consideration not only the similarity of extension but also the timing and characteristics of messages when extending the brand.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.467-479
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• 2023

Satellite altimeters have continuously observed sea surface height (SSH) in the global ocean for the past 30 years, providing clear evidence of the rise in global mean sea level based on observational data. Accurate altimeter-observed SSH is essential to study the spatial and temporal variability of SSH in regional seas. In this study, we used measurements from the Ieodo Ocean Research Station (IORS) and validate SSHs observed by satellite altimeters (Envisat, Jason-1, Jason-2, SARAL, Jason-3, and Sentinel-3A/B). Bias and root mean square error of SSH for each satellite ranged from 1.58 to 4.69 cm and 6.33 to 9.67 cm, respectively. As the matchup distance between satellite ground tracks and the IORS increased, the error of satellite SSHs significantly amplified. In order to validate the correction of the tide and atmospheric effect of the satellite data, the tide was estimated using harmonic analysis, and inverse barometer effect was calculated using atmospheric pressure data at the IORS. To achieve accurate tidal corrections for satellite SSH data in the seas around the Korean Peninsula, it was confirmed that improving the accuracy of tide data used in satellites is necessary.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.6
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• pp.598-608
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• 2023

To comprehensively grasp the dynamic changes in the coastal terrain and coastal erosion, it is imperative to incorporate temporal and spatial continuity through frequent and continuous monitoring. Recently, there has been a proliferation of research in coastal monitoring using remote sensing, accompanied by advancements in image monitoring and analysis technologies. Remote sensing, typically involves collection of images from aircraft or satellites from a distance, and offers distinct advantages in swiftly and accurately analyzing coastal terrain changes, leading to an escalating trend in its utilization. Remote satellite image-based coastal line detection involves defining measurable coastal lines from satellite images and extracting coastal lines by applying coastal line detection technology. Drawing from the various data sources surveyed in existing literature, this study has comprehensively analyzed encompassing the definition of coastal lines based on satellite images, current status of remote satellite imagery, existing research trends, and evolving landscape of technology for satellite image-based coastal line detection. Based on the results, research directions, on latest trends, practical techniques for ideal coastal line extraction, and enhanced integration with advanced digital monitoring were proposed. To effectively capture the changing trends and erosion levels across the entire Korean Peninsula in future, it is vital to move beyond localized monitoring and establish an active monitoring framework using digital monitoring, such as broad-scale satellite imagery. In light of these results, it is anticipated that the coastal line detection field will expedite the progression of ongoing research practices and analytical technologies.

• Information Systems Review
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• v.21 no.3
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• pp.111-129
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• 2019

Recently, artificial intelligence (AI)-enabled products and services such as smartphones, smart speakers, chatbots are being released due to advances in AI technology. Thus researchers making effort to reveal that consumers' intention to adopt AI-enabled products. Yet, little is known about the intended adoption of AI-enabled products. Because most of studies has been not consideredthe perceived utility value of consumers for each attribute by classified based on the characteristics of AI-enabled products. Therefore, the purpose of this study is to investigate the difference in importance between attributes that affect the intention to adopt of AI-enabled products. For this, first, identified and classified the attributes of AI-enabled products based on IS Success Model of DeLone and McLean. Second, measured the utility value of each attribute on the adoption of AI-enabled products through conjoint analysis. And we employed construal level theory to see whether there are differences in the relative importance of AI-enabled products attributes depending on the temporal distance. Third, we segmented the market based on the utility value of each respondent through cluster analysis and tried to understand the characteristics and needs of consumers in each segment market. We expect to provide theoretical implications for conceptually structured attributes and factors of AI-enabled products and practical implications for how development efforts of AI-enabled products are needed to reach consumers need for each segment.

• Journal of the Korean Geographical Society
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• v.40 no.2 s.107
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• pp.221-241
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• 2005

Land Use and Land Cover Changes (LUCC) occur over a wide range of space and time scales, and involve complex natural, socio-economic, and institutional processes. Therefore, modelling and predicting LUCC demands an understanding of how various measured properties behave when considered at different scales. Understanding spatial and temporal variability of driving forces and constraints on LUCC is central to understanding the scaling issues. This paper aims to 1) assess the heterogeneity of land cover change processes over the landscape in northern Ghana, where intensification of agricultural activities has been the dominant land cover change process during the past 15 years, 2) characterise dominant land cover change mechanisms for various spatial scales, and 3) identify the optimal spatial scale for LUCC modelling in a savanna landscape. A multivariate statistical method was first applied to identify land cover change intensity (LCCI), using four time-sequenced NDVI images derived from LANDSAT scenes. Three proxy land use change predictors: distance from roads, distance from surface water bodies, and a terrain characterisation index, were regressed against the LCCI using a multi-scale hierarchical adaptive model to identify scale dependency and spatial heterogeneity of LUCC processes. High spatial associations between the LCCI and land use change predictors were mostly limited to moving windows smaller than 10$\times$10km. With increasing window size, LUCC processes within the window tend to be too diverse to establish clear trends, because changes in one part of the window are compensated elsewhere. This results in a reduced correlation between LCCI and land use change predictors at a coarser spatial extent. The spatial coverage of 5-l0km is incidentally equivalent to a village or community area in the study region. In order to reduce spatial variability of land use change processes for regional or national level LUCC modelling, we suggest that the village level is the optimal spatial investigation unit in this savanna landscape.

• 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.