• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.5
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• pp.373-383
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• 2015

Spatial information has been widely used for efficient land use and management, disaster management, environment management, infrastructure management, corporate marketing, and cultural assets management, and the need for spatial information is expected to be increased. For this reason, central government, local government and public institutions must establish a National Spatial Information System (Fifteen systems related to spatial information managed by National Spatial Data Infrastructure Policy office, NSIS) framework that guarantees high accuracy and quality. The NSIS will provide convenience usage of spatial information in the field of decision-making or civil support. However the current National Spatial Information System is mainly established with separate processes, which causes data redundancy, deterioration of information, passive opening, and sharing of the spatial data. This study suggests 4 standards, which has been derived by applying value-chain model to NSIS data flow, and they are ‘Production and Establishment’, ‘Integration and Sharing’, ‘Application and Fusion’ and ‘Release and Opening’. Based on these standards, the 15 NSIS were analyzed to draw out implications and reforming directions were suggested. By following these suggestions we expect more recent, consist, accurate, and connected National Spatial Information Service which will be more open to public and then satisfy the demands.

• Journal of Environmental Science International
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• v.15 no.12
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• pp.1141-1154
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• 2006

Orographic effect is one of the important factors to induce Local circulations and to make atmospheric turbulence, so it is necessary to use the exact topographic data for prediction of local circulations. In order to clarify the sensitivity of the spatial resolution of topography data, numerical simulations using several topography data with different spatial resolution are carried out under stable and unstable synoptic conditions. The results are as follows: 1) Influence of topographic data resolution on local circulation tends to be stronger at simulation with fine grid than that with coarse grid. 2) The hight of mountains in numerical model become mote reasonable with high resolution topographic data, so the orographic effect is also emphasized and clarified when the topographic data resolution is higher. 2) The higher the topographic resolution is, the stronger the mountain effect is. When used topographic data resolution become fine, topography in numerical model becomes closer to real topography. 3) The topographic effect tends to be stronger when atmospheric stability is strong stable. 4) Although spatial resolution of topographic data is not fundamental factor for dramatic improvement of weather prediction accuracy, some influence on small scale circulation can be recognized, especially in fluid dynamic simulation.

• Journal of Environmental Impact Assessment
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• v.18 no.1
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• pp.31-39
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• 2009

A lot of data which are used in environment analysis of air pollution have characteristics that are distributed continuously in space. In this point, the collected data value such as precipitation, temperature, altitude, pollution density, PM10 have spatial aspect. When geostatistical data analysis are needed, acquisition of the value in every point is the best way, however, it is impossible because of the costs and time. Therefore, it is necessary to estimate the unknown values at unsampled locations based on observations. In this study, spatial interpolation method such as local trend surface model, IDW(inverse distance weighted), RBF(radial basis function), Kriging were applied to PM10 annual average concentration of Seoul in 2005 and the accuracy was evaluated. For evaluation of interpolation accuracy, range of estimated value, RMSE, average error were analyzed with observation data. The Kriging and RBF methods had the higher accuracy than others.

• Environmental Analysis Health and Toxicology
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• v.28
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• pp.5.1-5.7
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• 2013

Objectives Despite increasing availability of global positioning system (GPS), no research has been conducted to analyze GPS data for exposure opportunities associated with time at indoor and outdoor microenvironments. We developed location-based and time-weighted spatial measures that incorporate indoor and outdoor time-location data collected by GPS. Methods Time-location data were drawn from 38 female subjects in California who wore a GPS device for seven days. Ambient standard deviational ellipse was determined based on outdoor locations and time duration, while indoor time weighted standard deviational ellipse (SDE) was developed to incorporate indoor and outdoor times and locations data into the ellipse measure. Results Our findings indicated that there was considerable difference in the sizes of exposure potential measures when indoor time was taken into consideration, and that they were associated with day type (weekday/weekend) and employment status. Conclusions This study provides evidence that time-location weighted measure may provide better accuracy in assessing exposure opportunities at different microenvironments. The use of GPS likely improves the geographical details and accuracy of time-location data, and further development of such location-time weighted spatial measure is encouraged.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.1-8
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• 2024

Busan is the 6th largest port city in the world, where nitrogen dioxide (NO₂) emissions from transportation and port industries are significant. This study aims to assess the NO₂ products of the Geostationary Environment Monitoring Spectrometer (GEMS) over Busan using ground-based instruments (i.e., surface in-situ network and Pandora). The GEMS vertical column densities of NO₂ showed reasonable consistency in the spatiotemporal variations, comparable to the previous studies. The GEMS data showed a consistent seasonal trend of NO₂ with the Korea Ministry of Environment network and Pandora in 2022, which is higher in winter and lower in summer. These agreements prove the capability of the GEMS data to monitor the air quality in Busan. The correlation coefficient and the mean bias error between the GEMS and Pandora NO₂ over Busan in 2022 were 0.53 and 0.023 DU, respectively. The GEMS NO₂ data were also positively correlated with the ground-based in-situ network with a correlation coefficient of 0.42. However, due to the significant spatiotemporal variabilities of the NO₂, the GEMS footprint size can hardly resolve small-scale variabilities such as the emissions from the road and point sources. In addition, relative biases of the GEMS NO₂ retrievals to the Pandora data showed seasonal variabilities, which is attributable to the air mass factor estimation of the GEMS. Further studies with more measurement locations for longer periods of data can better contribute to assessing the GEMS NO₂ data. Reliable GEMS data can further help us understand the Asian air quality with the diurnal variabilities.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.21 no.5
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• pp.29-37
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• 2018

Biodiversity refers to the diversity of organisms originating from all sources, including terrestrial ecosystems, aquatic ecosystems, and complex ecosystems and it is considered to be the standard of the area to be preserved and protected. So The Importance of environmental assessment for biodiversity conservation is increasing and International efforts to quantify biodiversity and to develop indices have been made, but there are insufficient researches on the use of biomass databases and their quantification in Korea. In this study, the biodiversity map was constructed using the 3rd National Ecosystem Survey Mammal Data with three spatial units(Administrative Area, 1:5,000 index map, hexagonal lattice). and the difference of map constructed by spatial unit was suggested to help research on quantification and evaluation of biodiversity in the future. As a result of the study, biodiversity index for the same area varied according to the spatial unit and overall average and standard deviation were different too. Therefore it is necessary to utilize appropriate spatial unit considering the suitability and purpose of quantification rather than using specific unit. It also showed the necessity of establishing a standard for biodiversity index as a result of comparative analysis with ecosystem and nature map. Based on this research, comprehensive efforts should be made for the sustainable development of the country through further research and institutional improvement for quantification and evaluation of biodiversity, set standards.

• Korean Journal of Remote Sensing
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• v.37 no.4
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• pp.665-685
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• 2021

This study focused on the a 20-year evaluation of the dynamism of critical thermal anomalies in Busan metropolitan area prompted by unusual infrastructural development and demographic growth rate. Archived Landsat thermal data derived-LST was the major input for UTFVI and hot spot analysis (Getis-Ord Gi^*). Results revealed that the surface urban heat island-affected area has gradually expanded overtime from 23.32% to 32.36%; while the critical positive thermal anomalies (level-3 hotspots) have also spatially increased from 19.88% in 2000 to 23.56% in 2020, recording a net LST difference of > 5℃ between the maximum level-3 hotspot and minimum level-3 coldspot each year. It is been observed that thermal conditions of Busan have gradually deteriorated with time, which is potentially inherent in the rate of urban expansion. Thus, this work serves as an eye-opener to powers that be, to think and act constructively towards a sustainable thermal conform for city dwellers.

• Korean Journal of Remote Sensing
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• v.36 no.4
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• pp.573-586
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• 2020

PM (particulate matter) is of interest to everyone because it can have adverse effects on human health by the infiltration from respiratory to internal organs. To date, many studies have made efforts for the prediction of PM10 and PM2.5 concentrations. Unlike previous studies, we conducted the prediction of tomorrow's PM10 concentration for the Air Korea stations using Chinese PM10 data in addition to the satellite AOD and weather variables. We constructed 230,639 matchups from the raw data over 3 million and built an RF (random forest) model from the matchups to cope with the complexity and nonlinearity. The validation statistics from the blind test showed excellent accuracy with the RMSE (root mean square error) of 9.905 ㎍/㎥ and the CC (correlation coefficient) of 0.918. Moreover, our prediction model showed a stable performance without the dependency on seasons or the degree of PM10 concentration. However, part of coastal areas had a relatively low accuracy, which implies that a dedicated model for coastal areas will be necessary. Additional input variables such as wind direction, precipitation, and air stability should also be incorporated into the prediction model as future work.

• Korean Journal of Remote Sensing
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• v.33 no.3
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• pp.333-338
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• 2017

We compared sea ice concentration(SIC) and sea ice extent(SIE) using EUMETSAT Ocean and Sea Ice Satellite Application Facilities(OSI SAF) and NASA Team(NT) sea ice algorithm in the Arctic during 1980-2010 to investigate the difference between sea ice data applied different algorithms. SIC and SIE of the two data showed different consistency by season and by sea area. Seasonally, SIC of OSI SAF was 0.85 % overall, 0.48 % in spring, 0.97 % in summer, 1.38 % in autumn and 0.66 % in winter higher than NT SIC. By sea area, OSI SAF SIC was 2.7 %, SIE was $198,000km^2$ higher than NT in Arctic Ocean, but in Lincoln Sea, OSI SAF SIC was 2.3 %, SIE was $20,000km^2$ lower than NT.

• Journal of Environmental Impact Assessment
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• v.22 no.1
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• pp.19-26
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• 2013

The propose of this study is to analyze the optimum spatial resolution of the urban spatial thermal environment structure and to evaluate of the possibility detection using aerial photographs and thermal satellite images. The proper techniques of the optimum spatial resolution for the urban spatial thermal environment structure were analyzed. Thermal infrared satellite image of Seoul city were used for the change rate of surface temperature variation and suggested to the spatial extent and effects of urban surface characteristics and spatial data was interpreted as regions. To extract the surface temperature, Landsat thermal infrared satellite image compared with an automatic weather station data and in the field of the measured temperature and surface temperature by thermal environment affects, the spatial domain has been verified. The surface temperature of the satellite images to extract after adjusting surface temperature isotherms were constructed. The changes in surface temperature from 2008 to 2012 the average surface temperature observation images of changing areas were divided into space. The results of this study are as follows: Through analysis of satellite imagery, Seoul city surface temperature change due to extraction comfort indices were classified into four grades. The comfort index indicative of the temperature of Gangnam-gu, $23.7{\sim}27.2(^{\circ}C)$ range and Songpagu, a $22.7{\sim}30.6(^{\circ}C)$ respectively, the surface temperature of Yeouido $25.8{\sim}32.6(^{\circ}C)$ were in the range.