• Title/Summary/Keyword: Spatial scales

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The Analysis on the Spatial Characteristics and Inter-organizational Network Structure Change in the Creative Industry: Focused on Design Industry (창조산업의 공간적 특성과 기관별 네트워크구조 변화 분석 : 디자인산업을 중심으로)

  • Choi, Hae-Ok
    • Journal of the Economic Geographical Society of Korea
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    • v.15 no.1
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    • pp.116-130
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    • 2012
  • This study focuses on analyzing the design industry in creative industry in the context of upbringing growth engine of regional development policy and strategy. This research probe the spatial characteristics and inter-organizational network structure change from 2000 to 2010 using social network analysis(SNA) in terms of structural, spatial and temporal aspects. first, with the statistical data of design industry, this research evaluate spatial distribution and agggglomeration compared with 16 cities and 7metropolitan scales in Korea. Next, the group of density in the knowledge network of design industry explained with the spatial characteristics and inter-organizational network evolution in time series. After considering the government policy and strategy providing as a result of establishing regional innovation center strengthen cooperation among industry-university-research center.

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Generating high resolution of daily mean temperature using statistical models (통계적모형을 통한 고해상도 일별 평균기온 산정)

  • Yoon, Sanghoo
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.5
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    • pp.1215-1224
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    • 2016
  • Climate information of the high resolution grid units is an important factor to explain the phenomenon in a variety of research field. Statistical linear interpolation models are computationally inexpensive and applicable to any climate data compared to the dynamic simulation method at regional scales. In this paper, we considered four different linear-based statistical interpolation models: general linear model, generalized additive model, spatial linear regression model, and Bayesian spatial linear regression model. The climate variable of interest was the daily mean temperature, where the spatial variability was explained using geographic terrain information: latitude, longitude, elevation. The data were collected by weather stations in January from 2003 and 2012. In the sense of RMSE and correlation coefficient, Bayesian spatial linear regression model showed better performance in reflecting the spatial pattern compared to the other models.

Modified YOLOv4S based on Deep learning with Feature Fusion and Spatial Attention (특징 융합과 공간 강조를 적용한 딥러닝 기반의 개선된 YOLOv4S)

  • Hwang, Beom-Yeon;Lee, Sang-Hun;Lee, Seung-Hyun
    • Journal of the Korea Convergence Society
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    • v.12 no.12
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    • pp.31-37
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    • 2021
  • In this paper proposed a feature fusion and spatial attention-based modified YOLOv4S for small and occluded detection. Conventional YOLOv4S is a lightweight network and lacks feature extraction capability compared to the method of the deep network. The proposed method first combines feature maps of different scales with feature fusion to enhance semantic and low-level information. In addition expanding the receptive field with dilated convolution, the detection accuracy for small and occluded objects was improved. Second by improving the conventional spatial information with spatial attention, the detection accuracy of objects classified and occluded between objects was improved. PASCAL VOC and COCO datasets were used for quantitative evaluation of the proposed method. The proposed method improved mAP by 2.7% in the PASCAL VOC dataset and 1.8% in the COCO dataset compared to the Conventional YOLOv4S.

Spatial distribution of wastewater treatment plants in diverse river basins over the contiguous United States

  • Soohyun Yang;Olaf Buettner;Yuqi Liu;Dietrich Borchardt
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.142-142
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    • 2023
  • Humans inevitably and continuously produce wastewater in daily life worldwide. To decrease the degradation of river water bodies and aquatic ecosystem therein, humans have built systems at different scales to collect, drain, and treat household-produced wastewater. Particularly, municipal wastewater treatment plants (WWTPs) with centralized controls have played a key role in reducing loads of nutrients in domestic wastewater for the last few decades. Notwithstanding such contributions, impaired rivers regarding water quality and habitat integrity still exist at the whole river basin scale. It is highly attributable to the absence of dilution capacity of receiving streams and/or the accumulation of the pollutant loads along flow paths. To improve the perspective for individual WWTPs assessment, the first crucial step is to achieve systematic understanding on spatial distribution characteristics of all WWTPs together in a given river basin. By taking the initiative, our former study showed spatial hierarchical distributions of WWTPs in three large urbanized river basins in Germany. In this study, we uncover how municipal WWTPs in the contiguous United States are distributed along river networks in a give river basin. The extended spatial scope allows to deal with wide ranges in geomorphological attributes, hydro-climatic conditions, and socio-economic status. Furthermore, we identify the relation of the findings with multiple factors related to human activities, such as the spatial distribution of human settlements, the degree of economy development, and the fraction of communities served by WWTPs. Generalizable patterns found in this study are expected to contribute to establishing viable management plans for recent water-environmental challenges caused by WWTP-discharges to river water bodies.

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Calculating Average Residence Time Distribution Using a Particle Tracking Model (Particle Tracking Model을 이용한 평균체류시간의 공간분포 계산)

  • Park, Sung-Eun;Hong, Sok-Jin;Lee, Won-Chan
    • Journal of Ocean Engineering and Technology
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    • v.23 no.2
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    • pp.47-52
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    • 2009
  • A Lagrangian particle tracking model coupled with the Princeton Ocean Model were used to estimate the average residence time of coastal water in Masan Bay, Korea. Our interest in quantifying the transport time scales in Masan Bay was stimulated by the search for a mechanistic understanding of this spatial variability, which is consistent with the concept of spatially variable transport time scales. Tidal simulation was calibrated through a comparison with the results of semi-diurnal current and water elevation measured at the tidal stations of Masan, Gadeokdo. In the model simulations, particles were released in eight cases, including slack before ebb, peak ebb, slack before flood, and peak flood, during both spring and neap tides. The averaged values obtained from the particle release simulations were used for the average residence times of the coastal water in Masan Bay. The average residence times for the southeastern parts of Somodo and the Samho River, Masan Bay were estimated to be about 20~50days and 70~80days, respectively. The spatial difference for the average residence time was controlled by the tidal currents and distance from the mouth of the bay. Our results might provide useful for understanding the transport and behavior of coastal water in a bay and might be used to estimate the dissimilative capacity for environmental assessment.

Hyperspectral Image Classification via Joint Sparse representation of Multi-layer Superpixles

  • Sima, Haifeng;Mi, Aizhong;Han, Xue;Du, Shouheng;Wang, Zhiheng;Wang, Jianfang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.10
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    • pp.5015-5038
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    • 2018
  • In this paper, a novel spectral-spatial joint sparse representation algorithm for hyperspectral image classification is proposed based on multi-layer superpixels in various scales. Superpixels of various scales can provide complete yet redundant correlated information of the class attribute for test pixels. Therefore, we design a joint sparse model for a test pixel by sampling similar pixels from its corresponding superpixels combinations. Firstly, multi-layer superpixels are extracted on the false color image of the HSI data by principal components analysis model. Secondly, a group of discriminative sampling pixels are exploited as reconstruction matrix of test pixel which can be jointly represented by the structured dictionary and recovered sparse coefficients. Thirdly, the orthogonal matching pursuit strategy is employed for estimating sparse vector for the test pixel. In each iteration, the approximation can be computed from the dictionary and corresponding sparse vector. Finally, the class label of test pixel can be directly determined with minimum reconstruction error between the reconstruction matrix and its approximation. The advantages of this algorithm lie in the development of complete neighborhood and homogeneous pixels to share a common sparsity pattern, and it is able to achieve more flexible joint sparse coding of spectral-spatial information. Experimental results on three real hyperspectral datasets show that the proposed joint sparse model can achieve better performance than a series of excellent sparse classification methods and superpixels-based classification methods.

STUDY OF THE MARINE CLOUD STRUCTURE WITH AQUA AMSR-E

  • Shoom, Mariya Yu.
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.1007-1010
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    • 2006
  • This study investigates the spatial structure of the total cloud liquid water content Q fields over the Northwest Pacific Ocean during winter monsoon. The distributions of Q have been estimated from the brightness temperatures of the ocean - atmosphere system $T_B(f)$, where f is frequency, measured by AQUA AMSR-E in January -March 2003. Marine strati (St) and stratocumuli (Sc) are typical for winter monsoon season. They were analysed using mainly high-frequency channel at f = 36.5 GHz, vertical polarisation. $T_B$ data were accompanied by the data on near surface wind speed, air temperature and humidity from the nearest meteorological stations. Tow one-dimensional spectra were computed for downwind and crosswind sections of Q fields. The AMSR-E antenna field of view (14-8 km) and the cloud field sizes (100-1000 km) restricted the spatial scales. The results of case study Jan 31 2003 are presented. Scale-invariant spectrum is typical. In the cases of extended St levels a spectral slope equals about -1.7, conforming to classical -5/3 of turbulence theory. For Sc cases the absolute magnitude of spectral slope is rather higher, as a rule. The value is about -2. In the case when cloud streets are presented, a strait line form of spectrum is less reliable with a slope being rather lower (about -1.4).

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Analysis of Propagation Characteristics of a Song Sung when Weeding a Rice in Chungcheongbuk-do Using the Geomorphic Elements: The Case of Short Bang-a and Sangsa ryu (지형요소를 활용한 충북 논매기소리의 전파 특성 분석: 짧은방아 및 상사류를 사례로)

  • Park, Hyun-Su;JANG, Dong-Ho
    • Journal of The Geomorphological Association of Korea
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    • v.23 no.2
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    • pp.61-70
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    • 2016
  • This study intended to analyze the spatial distribution of two types of weeding song (Short Bang-a and Sangsa ryu) and how geomorphic elements influence the propagation of the songs in Chungcheongbuk-do area. The distribution of the two types of song was mapped as point data. According to the result, both types showed similar distribution pattern. In order to figure out the reason of this similarity, the distribution pattern of songs was analyzed at various scales based on geomorphic elements including river, mountain and lineament. The result showed that most of distribution pattern of songs followed the lineament direction. Also, the spatial continuity among mountain that was formed by large and small lineament in various directions could be the path of the cultural diffusion. If the lineament with same direction does not intersect other lineament that have different direction, spatial continuity would be blocked. Consequently it was confirmed that propagation of songs has not spread smoothly.

Main Elements for the Global-Local Connectivity of Regional Industrial Clusters (지역산업 클러스터의 세계적-지방적 연결성을 위한 주요 요소들)

  • Park, Yong-Gyu;Jung, Sung-Hoon
    • Journal of the Economic Geographical Society of Korea
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    • v.15 no.4
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    • pp.642-659
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    • 2012
  • The main aim of this article is to examine theoretical issues on the 'global-local connectivity' of regional industrial cluster and regional innovation system which have been presented since the 2000s in terms of three different aspects. Firstly, the concept of 'geographical proximity' is discussed within the context of its importance for the regional industrial development by considering relationships of cluster, local buzz and global pipeline. Secondly, concepts on knowledge gatekeeper and temporary cluster are explored with respect to their role of a mediator in forming or transforming global-local connectivity. Finally, policy implications of the global-local connection are presented. Authors arguments are as follows; firstly, in order to improve regional industrial cluster on the basis of geographical proximity, relational proximity which is beyond different spatial scales has to be secured. It means that geographical convenience and inconvenience are required simultaneously for regional industrial development. Secondly, A base of the global-local connectivity is socal capital and embeddedness. Therefore, it needs to understand that relational proximity is embedded into different culture and habit at different spatial scales. Finally, within the context of the global-local connectivity, in order to overcome spatial hierarchy by the division of labor of firms, it needs to consider the complex system which is composed of vertical and horizontal hierarchy by the spatial division of labor by firms, openness and closeness of clusters, and the scope of policies' inclusion and exclusion by central and local governments.

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Outlook of Discharge for Daecheong and Yongdam Dam Watershed Using A1B Climate Change Scenario Based RCM and SWAT Model (A1B기후변화시나리오 기반 RCM과 SWAT모형을 이용한 대청댐 및 용담댐 유역 유출량 전망)

  • Park, Jin-Hyeog;Kwon, Hyun-Han;No, Sun-Hee
    • Journal of Korea Water Resources Association
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    • v.44 no.12
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    • pp.929-940
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    • 2011
  • In this study, the future expected discharges are analyzed for Daecheong and Yongdam Dam Watershed in Geum River watershed using A1B scenario based RCM with 27 km spatial resolutions from Korea Meteorological Agency and SWAT model. The direct use of GCM and RCM data for water resources impact assessment is practically hard because the spatial and temporal scales are different. In this study, the problems of spatial and temporal scales were settled by the spatial and temporal downscaling from watershed scale to weather station scale and from monthly to daily of RCM grid data. To generate the detailed hydrologic scenarios of the watershed scale, the multi-site non-stationary downscaling method was used to examine the fluctuations of rainfall events according to the future climate change with considerations of non-stationary. The similarity between simulation and observation results of inflows and discharges at the Yongdam Dam and Daecheong Dam was respectively 90.1% and 84.3% which shows a good agreement with observed data using SWAT model from 2001 to 2006. The analysis period of climate change was selected for 80 years from 2011 to 2090 and the discharges are increased 6% in periods of 2011~2030. The seasonal patterns of discharges will be different from the present precipitation patterns because the simulated discharge of summer was decreased and the discharge of fall was increased.