• Journal of Environmental Impact Assessment
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• v.22 no.5
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• pp.513-523
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• 2013

This purpose of this work is to explore the characteristics of urban thermal environment distribution with the case of Daejeon. To do that, this work applied GIS Spatial Statistics to the LandSAT images gathered from 2000 to 2011. The urban thermal environment distribution at the time point of 2 showed high spatial autocorrelation. Therefore, it is judged that spatial autocorrelation is needed to increase the reliability and explanatory power of the characteristics of thermal environment distribution. In the case of the thermal in Daejeon, its positive clustering appeared high at the time point of 2, and its clustering in 2011 more gradually decreased than that in 2000 to 2011. In particular, given the decrease in the core H-H region, it was found that the thermal environment of Daejeon was greatly improved. However, since the rise in the region L-L means another changed like construction of a new city, it is judged that it is necessary to come up with a proper plan. It is considered that this analysis of the characteristics of urban thermal environment distribution in consideration of spatial autocorrelation L-L be useful for providing a fundamental material necessary for the policy and project of thermal environment improvement.

• Korean Journal of Remote Sensing
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• v.33 no.6_1
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• pp.981-992
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• 2017

We, for the first time, retrieved tropospheric nitrogen dioxide ($Trop.NO_2$) vertical column density (VCD) from ground-based instrument, Pandora, using the optical density fitting based on Differential Optical Absorption Spectroscopy (DOAS)in Seoul for the period from May 2014 to December 2014. The $Trop.NO_2$ VCDs retrieved from Pandora were compared with those obtained from Ozone Monitoring Instrument (OMI). A correlation coefficient (R) between those retrieved from Pandora and those obtained from OMI is 0.55. To compare with surface $NO_2$ VMRs obtained from in-situ, Trop. $NO_2$ VCDs retrieved from Pandora and those obtained from OMI are converted into $NO_2$ VMRs in boundary layer (BLH $NO_2$ VMRs) using data measured from Atmospheric Infrared Sounder (AIRS). Surface $NO_2$ VMRs obtained from in-situ range from 5.5 ppbv to 61.5 ppbv. BLH $NO_2$ VMRs retrieved from Pandora and OMI range from 2.1 ppbv to 44.2 ppbv and from 0.9 ppbv to 11.6 ppbv, respectively. The range of BLH $NO_2$ VMRs retrieved from OMI is narrower than that of BLH $NO_2$ VMRs retrieved from Pandora and surface $NO_2$ VMRs obtained from in-situ. There is a batter correlation between surface $NO_2$ VMRs obtained from in-situ and BLH $NO_2$ VMRs retrieved from Pandora (R= 0.50)than the correlation between surface $NO_2$ VMRs obtained from in-situ and BLH $NO_2$ VMRs retrieved from OMI (R = 0.36). This poor correlation is thought to be due to the lower near-surface sensitivity of the satellite-based instrument (OMI) than Pandora, the ground-based instrument.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.337-357
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• 2021

Because the growth of paddy rice is affected by meteorological factors, the selection of appropriate meteorological variables is essential to build a rice yield prediction model. This paper examines the suitability of multiple meteorological datasets for the rice yield modeling in South Korea, 1996-2019, and a hindcast experiment for rice yield using a machine learning method by considering the nonlinear relationships between meteorological variables and the rice yield. In addition to the ASOS in-situ observations, we used CRU-JRA ver. 2.1 and ERA5 reanalysis. From the multiple meteorological datasets, we extracted the four common variables (air temperature, relative humidity, solar radiation, and precipitation) and analyzed the characteristics of each data and the associations with rice yields. CRU-JRA ver. 2.1 showed an overall agreement with the other datasets. While relative humidity had a rare relationship with rice yields, solar radiation showed a somewhat high correlation with rice yields. Using the air temperature, solar radiation, and precipitation of July, August, and September, we built a random forest model for the hindcast experiments of rice yields. The model with CRU-JRA ver. 2.1 showed the best performance with a correlation coefficient of 0.772. The solar radiation in the prediction model had the most significant importance among the variables, which is in accordance with the generic agricultural knowledge. This paper has an implication for selecting from multiple meteorological datasets for rice yield modeling.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.543-557
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• 2021

Because aerosols have different spectral characteristics according to the size and composition of the particle and to the satellite sensors, a comparative analysis of aerosol products from various satellite sensors is required. In South Korea, however, a comprehensive study for the comparison of various official satellite AOD (Aerosol Optical Depth) products for a long period is not easily found. In this paper, we aimed to assess the performance of the AOD products from MODIS (Moderate Resolution Imaging Spectroradiometer), VIIRS (Visible Infrared Imaging Radiometer Suite), Himawari-8, and Sentinel-3 by referring to the AERONET (Aerosol Robotic Network) sun photometer observations for the period between January 2015 and December 2019. Seasonal and geographical characteristics of the accuracy of satellite AOD were also analyzed. The MODIS products, which were accumulated for a long time and optimized by the new MAIAC (Multiangle Implementation of Atmospheric Correction) algorithm, showed the best accuracy (CC=0.836) and were followed by the products from VIIRS and Himawari-8. On the other hand, Sentinel-3 AOD did not appear to have a good quality because it was recently launched and not sufficiently optimized yet, according to ESA (European Space Agency). The AOD of MODIS, VIIRS, and Himawari-8 did not show a significant difference in accuracy according to season and to urban vs. non-urban regions, but the mixed pixel problem was partly found in a few coastal regions. Because AOD is an essential component for atmospheric correction, the result of this study can be a reference to the future work for the atmospheric correction for the Korean CAS (Compact Advanced Satellite) series.

• Spatial Information Research
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• v.2 no.1
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• pp.39-46
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• 1994

GIS technique was applied to identify the geotechnical characte¬ristic of subsurface in a study area, and has produced a Geotechnical Esti¬mat ion Index(GEI) map. Groundwater level, soi I depth & weathered zone, and engineering properties of soils & rocks, were incorporated in the map through GIS. EGIS(Environmental Geologic Information System), developed by ARC/INFO GIS system, was used for this work. Environmental geologic database by EGIS was verified to be effective in analysis of engineering geological properties of the subsurface. Quantitative analysis of environmental and geotechnical information enable to develop a scoring system of GEI model, which was developed through evaluation of each goelogical factor with respect to the other factors.

• Spatial Information Research
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• v.16 no.1
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• pp.33-50
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• 2008

At present, the cadastral field, with the conversion into digital cadastral map management system, not the existing cadastral map management system, has gone through a lot of changes, such as the market opening of cadastral surveying and overseas launching of a cadastral field. Such an environmental change has brought on a lot of advantages, such as improvement in accuracy of surveying, efficient management system, and reinforcement of competitive power in cadastral surveying. However, the conversion into the advanced cadastral management system serves to relatively heightening the possibility of outflow of cadastral information and its technology in comparison with in the past. This research, with the aim to cope with indiscriminate outflow of cadastral technology, is aimed at suggesting the plan for the prevention of outflow of cadastral technique and its protection after examining and considering the contents of environmental changes in the currently going cadastral field.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 1996.06a
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• pp.135-137
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• 1996

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.1
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• pp.187-193
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• 2017

Government has established and operated GIS Data Base in such fields as land-use, road, and underground facilities since 1995. Based on these circumstances, the importance of spatial information industry began to emerge and accordingly MLIT (Ministry of Land, Infrastructure and Transport) established "National Spatial Information Policy Master Plan" and "National Spatial Information Policy Action Plan". However, compared to other fields of transportation, the spatial information data base for railway facilities are not established and provided systematically. As shown in 'Korea National Spatial Data Infrastructure System', only 'transportation information' as an related information and 'transportation' field as an administrative information are included in the system. Detailed information for railway and its facilities are not included in the system. The reason why detailed information for railway facilities are not included in the system is that regulations for establishing and utilizing the spatial information of railway and its facilities are imperfect. In this study, trend of establishing spatial information and regulations related to railway and its facilities are reviewed. Through this review, improvement items such as complementing existent laws and establishing organization for managing spatial information data of railway are deduced and suggested. Based on this research 'Korea National Spatial Data Infrastructure System' could set a legal fundament and both integrated maintenance and operation of railway facilities could be possible.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.1
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• pp.23-29
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• 2015

In this study, the spatial relevance between the regional housing price data and the spatial distribution of the location-based social media data is explored. The spatial analysis with rasterization was applied to this study, because the both data have a different form to analyze. The geo-tagged Twitter data had been collected for a month and the regional housing price index about sales and lease were used. The spatial range of both data includes Seoul and the some parts of the metropolitan area. 2,000m grid was constructed to consider the different spatial measure between two data, and they were combined into the constructed grids. The Hotspot Analysis was operated using the combined dataset to see the comparison of spatial distribution, and the bivariate spatial correlation coefficients between two data were measured for the quantitative analysis. The result of this study shows that Seocho-gu area is detected as a common hotspot of tweet and housing sales price index data. though the spatial relevance is not detected between tweet and housing lease price index data.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.2
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• pp.295-307
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• 2021

The Korean Peninsula is surrounded on three sides by the East Sea, West Sea and South Sea which are connected to many rivers and streams, thereby facilitating easy inflow of debris from land. Furthermore, excessive debris inflow to the sea because of active fishing and various recreational activities. Debris entering the sea are weighted over time and settle in the seabed, thus, making direct monitoring of debris impossible and its collection difficult. Uncollected submerged marine debris affects the seabed ecosystem and water quality and can cause ghost fishing and ship accidents, especially due to waste net ropes and waste fishing gears. Therefore, understanding the debris distribution characteristics is necessary to assist quick collection of these debris (waste net ropes and waste fishing gears). Thus, this study conducted a survey of debris deposited in the seas of 39 ports. Furthermore, distribution characteristics and compositions of submerged marine debris were identified by a map prepared through GIS-based spatial analysis of the East Sea. Consequently, 58% of waste tires in the East Sea were concentrated in breakwaters and ship berthing facilities. Moreover, 26 % of waste plastics were distributed outside the port. Identifying the distinct distribution characteristics of submerged marine debris was difficult; however, compared with others, the distribution of waste plastics was possible outside the port. The findings of this study can serve as baseline data to assist the collection of submerged marine debris using the distribution characteristics.