• Korean Journal of Remote Sensing
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• v.37 no.4
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• pp.777-788
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• 2021

Since aerosol has a relatively short duration and significant spatial variation, satellite observations become more important for the spatially and temporally continuous quantification of aerosol. However, optical remote sensing has the disadvantage that it cannot detect AOD (Aerosol Optical Depth) for the regions covered by clouds or the regions with extremely high concentrations. Such missing values can increase the data uncertainty in the analyses of the Earth's environment. This paper presents a spatial gap-filling framework using a univariate statistical method such as DCT-PLS (Discrete Cosine Transform-based Penalized Least Square Regression) and FMM (Fast Matching Method) inpainting. We conducted a feasibility test for the hourly AOD product from AHI (Advanced Himawari Imager) between January 1 and December 31, 2019, and compared the accuracy statistics of the two spatial gap-filling methods. When the null-pixel area is not very large (null-pixel ratio < 0.6), the validation statistics of DCT-PLS and FMM techniques showed high accuracy of CC=0.988 (MAE=0.020) and CC=0.980 (MAE=0.028), respectively. Together with the AI-based gap-filling method using extra explanatory variables, the DCT-PLS and FMM techniques can be tested for the low-resolution images from the AMI (Advanced Meteorological Imager) of GK2A (Geostationary Korea Multi-purpose Satellite 2A), GEMS (Geostationary Environment Monitoring Spectrometer) and GOCI2 (Geostationary Ocean Color Imager) of GK2B (Geostationary Korea Multi-purpose Satellite 2B) and the high-resolution images from the CAS500 (Compact Advanced Satellite) series soon.

• Spatial Information Research
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• v.18 no.1
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• pp.69-76
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• 2010

Spatial data streams from sensors are useful in context-awareness for many types of applications. However, an important gap is found between spatial data stream management in real-time and complex computation for spatial context-awareness, and this brings about serious difficulty to integrate spatial data stream processing and context-awareness. In this paper, we present a system called SCONSTREAM(Spatial CONtext STREAm Management) that we have developed to resolve the gap between spatial data stream and context-awareness. The key approach of our system is to filter off unnecessary spatial data streams and convert them to the spatial context streams, which are smaller and more suitable to be processed by the context-awareness module than raw data from sensors. By experimentation, We show that SCONSTREAM resolves the functional gap between spatial stream processing and spatial context-awareness module.

• Journal of Korean Association for Spatial Structures
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• v.1 no.1 s.1
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• pp.57-69
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• 2001

설계와 구조의 바람직한 상관관계는 무엇인가라는 논제를 던져놓고 시작해 보기로 하자, 누구나 이러한 질의에 대해 정확한 답을 찾을 수 없을 것이다. 또한 다른 표현을 빌려보자면 서로의 관계에서 그러한 갭(gap)을 어떻게 줄일 것인가에 대해 답을 얻는 것과 유사할 것이다. 위에서 설정한 'Bridging the Gap'의 논제는 수년 전 미국에서 위 논제로 심포지움(symposium)이 열린 적 있고, 그것에 대한 책이 출간된 것으로 알고 있다. 이러한 의미에서 현 한국의 건축과 학제 개편에서 급히 해결되어야 필연적인 과제다.

• Spatial Information Research
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• v.23 no.3
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• pp.101-111
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• 2015

The Emirate of Abu Dhabi is swiftly rising into a newly industrialized country by achieving economic prosperity among the Islamic cultural regions of Middle East and North Africa(MENA). Abu Dhabi Emirate is performing the conversion from oil economy to non-oil economy and the sustainable urban development policy. However, there are various social and environmental problems in Abu Dhabi. In order to solve the urban problems caused by the rapid economic growth and the changes in society and environment, Abu Dhabi is recognizing the importance of spatial information and triggering the establishment of spatial information. Spatial information is regarded as a basic infrastructure for urban construction and enlarged as a blue ocean market in Abu Dhabi. However, the base of spatial data infrastructure in Abu Dhabi is not well managed in comparison to that of Korea. Especially, Abu Dhabi has some characteristics that it depends on foreign multinational companies and it does not have its own systemic organization and law system. To advance into Abu Dhabi spatial data market under-controlled by global vendors, it is necessary to identify the advantage and disadvantage on spatial data infrastructure of Abu Dhabi and required to establish the advance methods into niche markets by considering priority order of spatial information. Thus, this study aims to analyze the gap of spatial information between Abu Dhabi and Korea and suggest the short and long term development methods for spatial data infrastructure of Abu Dhabi. The results of gap analyses will be the milestone for Korean companies' advance into MENA.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.953-966
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• 2022

Since aerosols adversely affect human health, such as deteriorating air quality, quantitative observation of the distribution and characteristics of aerosols is essential. Recently, satellite-based Aerosol Optical Depth (AOD) data is used in various studies as periodic and quantitative information acquisition means on the global scale, but optical sensor-based satellite AOD images are missing in some areas with cloud conditions. In this study, we produced gap-free GeoKompsat 2A (GK-2A) Advanced Meteorological Imager (AMI) AOD hourly images after generating a Random Forest based gap-filling model using grid meteorological and geographic elements as input variables. The accuracy of the model is Mean Bias Error (MBE) of -0.002 and Root Mean Square Error (RMSE) of 0.145, which is higher than the target accuracy of the original data and considering that the target object is an atmospheric variable with Correlation Coefficient (CC) of 0.714, it is a model with sufficient explanatory power. The high temporal resolution of geostationary satellites is suitable for diurnal variation observation and is an important model for other research such as input for atmospheric correction, estimation of ground PM, analysis of small fires or pollutants.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1407-1419
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• 2020

Long time-series gridded data is crucial for the analyses of Earth environmental changes. Climate reanalysis and satellite images are now used as global-scale periodical and quantitative information for the atmosphere and land surface. This paper examines the feasibility of DCT-PLS (penalized least square regression based on discrete cosine transform) for the spatial gap filling of gridded data through the experiments for multiple variables. Because gap-free data is required for an objective comparison of original with gap-filled data, we used LDAPS (Local Data Assimilation and Prediction System) daily data and MODIS (Moderate Resolution Imaging Spectroradiometer) monthly products. In the experiments for relative humidity, wind speed, LST (land surface temperature), and NDVI (normalized difference vegetation index), we made sure that randomly generated gaps were retrieved very similar to the original data. The correlation coefficients were over 0.95 for the four variables. Because the DCT-PLS method does not require ancillary data and can refer to both spatial and temporal information with a fast computation, it can be applied to operative systems for satellite data processing.

• Water Engineering Research
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• v.3 no.1
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• pp.31-44
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• 2002

The effect of diurnal cycle, intermittent visit of observation satellite, sensor installation, partial coverage of remote sensing, heterogeneity of soil properties and precipitation to the soil moisture estimation error were analyzed to present the global sampling strategy of soil moisture. Three models, the theoretical soil moisture model, WGR model proposed Waymire of at. (1984) to generate rainfall, and Turning Band Method to generate two dimensional soil porosity, active soil depth and loss coefficient field were used to construct sufficient two-dimensional soil moisture data based on different scenarios. The sampling error is dominated by sampling interval and design scheme. The effect of heterogeneity of soil properties and rainfall to sampling error is smaller than that of temporal gap and spatial gap. Selecting a small sampling interval can dramatically reduce the sampling error generated by other factors such as heterogeneity of rainfall, soil properties, topography, and climatic conditions. If the annual mean of coverage portion is about 90%, the effect of partial coverage to sampling error can be disregarded. The water retention capacity of fields is very important in the sampling error. The smaller the water retention capacity of the field (small soil porosity and thin active soil depth), the greater the sampling error. These results indicate that the sampling error is very sensitive to water retention capacity. Block random installation gets more accurate data than random installation of soil moisture gages. The Walnut Gulch soil moisture data show that the diurnal variation of soil moisture causes sampling error between 1 and 4 % in daily estimation.

• Journal of the Korean Regional Science Association
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• v.6 no.2
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• pp.149-153
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• 1990

• Journal of Korean Society of Forest Science
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• v.97 no.2
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• pp.165-170
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• 2008

Litterfall has been recognized an important part of the forest ecosystem production, playing a major pathway in energy flow and nutrient cycling through the ecosystem. This study was carried out to examine the quantity and components, temporal variation, and spatial heterogeneity of the litterfall in the mixed broadleaved-Korean pine forest. The data were collected from the 9ha permanent experimental plot, of which on the center area, i.e. $150m{\times}150m$, the total number of 319 circular litterfall traps with the size of $0.5m^2$ were established to collect falling litterfall. The results showed that the annual amount of litterfall was totalized 3,033.7 kg/ha, occupying broad-leaves of 39.3%, conifer-leaves of 29.5%, others of 18.5%, branches of 10.4%, and seeds of 2.3%. The peak point of the litterfall production was made at the end of September, proportionating 32.2% of total amount. The analysis of semivariogram revealed the existence of high spatial heterogeneity, calculated the scale of spatial heterogeneity ranged from 11.6 m to 29.1 m. The result of proportion (C/[Co+C]) showed that spatial heterogeneity of autocorrelation in total spatial heterogeneity were from 97.0% to 100%. The relatively heavy branches and others had significant differences in litterfall production between the areas of canopy gap and closed canopy in the 95% probability level, but the other components did not show statistical differences.

• Journal of Engineering Education Research
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• v.18 no.4
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• pp.34-44
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• 2015

Mathematical, spatial, and verbal abilities are important for future engineers to succeed in the STEM disciplines. The purpose of the study is to assess engineering students' spatial abilities and analyse the relationship with mathematical achievement, verbal achievement, and gender. On the mental rotation tests, 65% of male students demonstrated a substantial level of spatial abilities. But only 30% of female students exhibited spatial skills at the same level as their male colleagues. The correlations between mathematical - spatial - verbal abilities are found to be negligible. When spatial visualization ability was plotted according to the mathematical achievement level, there was no difference in the mean spatial abilities score. But when mathematical achievement score was plotted according to the spatial abilities, there was a noticeable difference. Regression analysis confirmed that female students' mathematical achievement increased as spatial abilities improved. This phenomenon was not observed for male students. It's because male students' spatial ability already contributed to their mathematics achievement. So spatial ability can be regarded as one factor for the gender differences in mathematics achievement. The gender gap on spatial abilities and math achievement is large among high achieving students. For example, there was a 4.3 to 1 male - female ratio and 3.4 to 1 male - female ratio among students scoring 99th percentile in spatial visualization test and scholastic aptitude test-math.