• 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.

• Journal of Information Processing Systems
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• v.18 no.2
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• pp.235-244
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• 2022

Many new techniques have been adopted in HEVC (High efficiency video coding) standard, such as quadtree-structured coding unit (CU), prediction unit (PU) partition, 35 intra-mode, and so on. To reduce computational complexity, the paper proposes two optimization algorithms which include fast CU depth range decision and fast PU partition mode decision. Firstly, depth range of CU is predicted according to spatial-temporal correlation. Secondly, we utilize the depth difference between the current CU and CU corresponding to the same position of adjacent frame for PU mode range selection. The number of traversal candidate modes is reduced. The experiment result shows the proposed algorithm obtains a lot of time reducing, and the loss of coding efficiency is inappreciable.

• Spatial Information Research
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• v.22 no.4
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• pp.21-38
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• 2014

Since users who search maps conduct their searching using the name they already know or is commonly called rather than formal name of a specific place, they tend to fail to find their destination. In addition, in typical web map service in terms of spatial searching of map. Location information of unintended place can be provided because when spatial searching is conducted with the vocabulary 'nearby' and 'in the vicinity', location exceeding 2 km from the current location is searched altogether as well. In this research, spatial range that human can perceive is calculated by extracting POI date with the usage of twitter data of SNS, constructing spatial relations with existing POI, which is already constructed. As a result, various place names acquired could be utilized as different names of existing POI data and it is expected that new POI data would contribute to select places for constructing POI data by utilizing to recognize places having lots of POI variation. Besides, we also expect efficient spatial searching be conducted using diverse spatial vocabulary which can be used in spatial searching and spatial range that human can perceive.

• Journal of Korea Multimedia Society
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• v.22 no.2
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• pp.210-224
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• 2019

Given a positive integer k as input, a spatial preference query finds the k best data objects based on the scores (e.g., qualities) of feature objects in their spatial neighborhoods. Several solutions have been proposed for spatial preference queries in Euclidean space. A few algorithms study spatial preference queries in undirected spatial networks where each edge is undirected and the distance between two points is the length of the shortest path connecting them. However, spatial preference queries have not been thoroughly investigated in directed spatial networks where each edge has a particular orientation that makes the distance between two points noncommutative. Therefore, in this study, we present a new method called ALPS+ for processing spatial preference queries in directed spatial networks. We conduct extensive experiments with different setups to demonstrate the superiority of ALPS+ over conventional solutions.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.12 no.3
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• pp.130-141
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• 2009

The spatial range of EIA is mainly related to landscape ecological factors such as topography, geology, animals, and plants. Problems were detected involved land, soil, noise, oscillation, the atmosphere, animals, and plants in the natural-environment. First of all, the current EIA lacks explicit spatial ranges and sections in terms of scientific exactitude and objectivity for assessment. Secondly, there are overlapping influence-area problems resulting in cumulative impacts of unit developments that accumulate. Finally, some developments have no regard for ecological and conservational value in relation to determining which effect ecological stability, and which should be regarded as Regional Ecological Resources. Therefore, this study suggests that EIA should be improved in the following manner. First, the standard classification of landscape unit for analysis should be established 10 regulate each spatial range on a wide-landscape scale. Secondly, the impacts resulting from the interaction of overlapping influence-area developments between individual development should be assessed. Third, Minimization of the of the environmental effects is needed by applying the cumulative effects to the influence-area where developments occur in the same time or in a sequence. Fourth, individual characteristics of landscape elements such as roads, rivers, and green networks need to be considered separately in the analysis. Finally, regional ecological habitats should be included in the analysis in order to achieve stable ecosystems.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.11
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• pp.611-616
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• 2004

In this paper, we introduce a very fast and efficient fractal coding scheme by using the spatial prediction on ultra-small atomic range blocks. This new approach drastically speeds up the encoding while improving the fidelity and the compression ratio. The affine transformation coefficients between adjacent range blocks induced by this method often have good correlations thereby the compression ratios can further be improved. The proposed method leads to improved rate-distortion performance compared to previously reported pure fractals, and it is faster than other state-of-the-art fractal coding methods.

• Journal of the Korean earth science society
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• v.31 no.2
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• pp.119-128
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• 2010

To make reliable interpretations on the sparse spatial data, the spatial distribution characteristics that are inevitable for spatial estimation should be properly analyzed. Variograms have been widely used for obtaining the spatial characteristics inherent to data in spatial estimation problems. But their applications were limited as the basic information for further data estimation. Therefore, the additional analysis of the meaning of variograms is required for more reliable data processing and interpretations. In this paper, we investigated the proper meaning of variogram values and the specific features of distributions which can be obtained through variogram analysis. Variograms can provide the information on both linearity and the strength changes of interrelationships between the data sets according to the direction and lag distance. First, sill and range values, which are main parameters of variograms, were analyzed. Then a similarity range using spatial auto-correlation values was introduced to verify the applicability of linearity analysis through the comparative study of spatial distribution features of gravity and magnetic data collected in Hwasan caldera. Through these analyses, we were able to identify the dissimilar patterns of gravity and magnetic data that became apparent according to the distribution and variation ranges of the data sets. It is inferred that the gravity and magnetic anomalous bodies are extended to the ground because linearity direction of gravity and magnetic data appear similarly with linearity derection of topography in Hwasan caldera.

• Journal of the Korean Geographical Society
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• v.43 no.3
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• pp.276-295
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• 2008

Recent disputes on mountain ranges in Korea have partially been derived from the discordance of the spatial distribution and the extent of mountain ranges presented by different researchers and school textbooks. The lack of consensus on the definition and genesis of mountain ranges adds further confusion. In order to overcome these problems, it is necessary to provide genetically classified mountain range maps for different usages, map scales and educational purposes. This paper first argues that mountain ranges and mountain ridges should separately be used as different conceptual frameworks to explain complex spatial distribution of mountains in Korea. The new mountain range map (sanmaekdo) proposed in this research puts strong emphasis on tectonic movement and denudational processes to explain the spatial distribution of mountains. The new mountain range map has 15 mountain ranges (sanmaek: in total, which are further divided into 7 primary and 8 secondary mountain ranges. The new mountain range map eliminates Jeogyuryeongsanmaek, Myohyangsanmaek, Myeoraksanmaek, and Masingnyeongsanmaek from the existing map, since these have a vague definition and obscure spatial distribution. On the contrary, few new primary mountain ranges (Gilju-Myeongcheonsanmaek, Yangsansanmaek, Jirisanmaek) and secondary mountain ranges (Wolchulsanmaek and Buksubaeksanmaek) are added to the new mountain range map. Other mountain ranges also show a large difference both in their spatial distribution and the extent of mountain ranges, compared with the previous map. This is especially the case for Nangnimsanmaek, Hamgyeongsanmaek, Taebaeksanmaek, and Sobaeksanmaek. A few new names are also assigned to Macheollyeongsanmaek (Baekdusanmaek), Gwangjusanmaek (Hwaaksanmaek), Charyeongsanmaek (Chiaksanmaek), and Horyeongsanmaek (Naejangsanmaek), even though they show similar spatial distribution patterns with the ones in the existing map.

• Korean Journal of Remote Sensing
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• v.34 no.4
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• pp.661-670
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• 2018

This study aims to develop a methodology of convolutional neural networks (CNNs) to produce thematic maps from remote sensing data. Optimizing the image size for CNNs was studied, since the size of the image affects to accuracy, working as hyper-parameter. The selected study area is Mt. Ung, located in Dangjin-si, Chungcheongnam-do, South Korea, consisting of both coniferous forest and deciduous forest. Spatial structure analysis and the classification of forest type using CNNs was carried in the study area at a diverse range of scales. As a result of the spatial structure analysis, it was found that the local variance (LV) was high, in the range of 7.65 m to 18.87 m, meaning that the size of objects in the image is likely to be with in this range. As a result of the classification, the image measuring 15.81 m, belonging to the range with highest LV values, had the highest classification accuracy of 85.09%. Also, there was a positive correlation between LV and the accuracy in the range under 15.81 m, which was judged to be the optimal image size. Therefore, the trial and error selection of the optimum image size could be minimized by choosing the result of the spatial structure analysis as the starting point. This study estimated the optimal image size for CNNs using spatial structure analysis and found that this can be used to promote the application of deep-learning in remote sensing.

• Geomechanics and Engineering
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• v.36 no.6
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• pp.631-640
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• 2024

In the traditional slope stability analysis, ignoring the spatial variability of slope soil will lead to inaccurate analysis. In this paper, the K-L series expansion method is adopted to simulate random field of soil strength parameters. Based on Random Limit Equilibrium Method (RLEM), the influence of variation coefficient and fluctuation range on reliability of soil slope supported by micro-pile is investigated. The results show that the fluctuation ranges and the variation coefficients significantly influence the failure probability of soil slope supported by micro-pile. With the increase of fluctuation range of soil strength parameters, the mean safety factor of the slope increases slightly. The failure probability of the soil slope increases with the increase of fluctuation range when the mean safety factor of the slope is greater than 1. The failure probability of the slope increases by nearly 8.5% when the fluctuation range is increased from δ_v=2 m to δ_v =8 m. With the increase of the variation coefficient of soil strength parameters, the mean safety factor of the slope decreases slightly, and the probability of failure of soil slope increases accordingly. The failure probability of the slope increases by nearly 31% when the variation coefficient increases from COV_c=0.2, COV_φ=0.05 to COV_c=0.5, COV_φ=0.2.