• Title/Summary/Keyword: spatial neighbor

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Analysis of Temporal and Spatial Distribution of Traffic Accidents in Jinju (진주시 교통사고의 시계열적 공간분포특성 분석)

  • Sung, Byeong Jun;Bae, Gyu Han;Yoo, Hwan Hee
    • Journal of Korean Society for Geospatial Information Science
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    • v.23 no.2
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    • pp.3-9
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    • 2015
  • Since changes in land use in urban space cause traffic volume and it is closely related to traffic accidents. Therefore, an analysis on the causes of traffic accidents is judged to be an essential factor to establish the measure to reduce traffic accidents. In this regard, the analysis was conducted on the clustering by using the nearest neighbor indexes with regard to the occurrence frequencies of commercial and residential zone based on traffic accident data of the past five years (2009-2013) with the target of local small-medium sized city, Jinju-si. The analysis results, obtained in this study, are as follows: the occurrence frequency of traffic accidents was the highest in spring and the lowest in winter respectively. The clustering of traffic accident occurrence at nighttime was stronger than at daytime. In addition, terms of the analysis on the clustering of traffic accident according to land use, changes according to the seasons was not significant in commercial areas, while clustering density in winter tended to become significantly lower in residential areas. The analysis results of traffic accident types showed that the side-right angle collision of cars was the highest in frequency occurrence, and widespread in both commercial areas and residential areas. These results can provide us with important information to identify the occurrence pattern of traffic accidents in the structure of urban space, and it is expected that they will be appropriately utilized to establish measures to reduce traffic accidents.

A Study on the Characteristics of Garden Architecture in Italian Renaissance Villa Lante (이탈리아 르네상스 빌라 란테의 정원건축적 특성)

  • Choi, Jong-Hee
    • Journal of the Korean Institute of Traditional Landscape Architecture
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    • v.29 no.2
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    • pp.90-98
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    • 2011
  • This study aims to discuss the characteristics of garden architecture in Italian Renaissance Villa Lante that was constructed by the cardinal in Bagnaia at 16th century through actual survey and analysis of the garden's elements. To do this, it was studied in two ways: Analysis of the present conditions and review historical documents. The results are as follows. First, the buildings, the gardens and the surrounding landscapes are visually connected each other in relations between the topography and the surrounding landscapes. Second, the spatial composition accepted Neoplatonic law of multiple proportions and was influenced by ancient myth and "Liber ruralium commodorum" of Pietro de Crescenzi(1305). Third, the garden's elements consist of plants, buildings and items. In plants, the upper plants are fir tree, cypress and pine tree and the lower plants are english holly, box tree and sweet oleander. The buildings are casino, loggia and terrace. The items are pot, sundial, chair, viewing platform and fountain. The result of this study, the political and social, technical phenomena which constitute construction pattern affected the locational property and the spatial organization of the neighbor on Villa Lante.

A Comparison between Simulation Results of DSSAT CROPGRO-SOYBEAN at US Cornbelt using Different Gridded Weather Forecast Data (격자기상예보자료 종류에 따른 미국 콘벨트 지역 DSSAT CROPGRO-SOYBEAN 모형 구동 결과 비교)

  • Yoo, Byoung Hyun;Kim, Kwang Soo;Hur, Jina;Song, Chan-Yeong;Ahn, Joong-Bae
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.24 no.3
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    • pp.164-178
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    • 2022
  • Uncertainties in weather forecasts would affect the reliability of yield prediction using crop models. The objective of this study was to compare uncertainty in crop yield prediction caused by the use of the weather forecast data. Daily weather data were produced at 10 km spatial resolution using W eather Research and Forecasting (W RF) model. The nearest neighbor method was used to downscale these data at the resolution of 5 km (W RF5K). Parameter-elevation Regressions on Independent Slopes Model (PRISM) was also applied to the WRF data to produce the weather data at the same resolution. W RF5K and PRISM data were used as inputs to the CROPGRO-SOYBEAN model to predict crop yield. The uncertainties of the gridded data were analyzed using cumulative growing degree days (CGDD) and cumulative solar radiation (CSRAD) during the soybean growing seasons for the crop of interest. The degree of agreement (DOA) statistics including structural similarity index were determined for the crop model outputs. Our results indicated that the DOA statistics for CGDD were correlated with that for the maturity dates predicted using WRF5K and PRISM data. Yield forecasts had small values of the DOA statistics when large spatial disagreement occured between maturity dates predicted using WRF5K and PRISM. These results suggest that the spatial uncertainties in temperature data would affect the reliability of the phenology and, as a result, yield predictions at a greater degree than those in solar radiation data. This merits further studies to assess the uncertainties of crop yield forecasts using a wide range of crop calendars.

Adaptive Block Recovery Based on Subband Energy and DC Value in Wavelet Domain (웨이블릿 부대역의 에너지와 DC 값에 근거한 적응적 블록 복구)

  • Hyun, Seung-Hwa;Eom, Il-Kyu;Kim, Yoo-Shin
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.5 s.305
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    • pp.95-102
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    • 2005
  • When images compressed with block-based compression techniques are transmitted over a noisy channel, unexpected block losses occur. In this paper, we present a post-processing-based block recovery scheme using Haar wavelet features. No consideration of the edge-direction, when recover the lost blocks, can cause block-blurring effects. The proposed directional recovery method in this paper is effective for the strong edge because exploit the varying neighboring blocks adaptively according to the edges and the directional information in the image. First, the adaptive selection of neighbor blocks is performed based on the energy of wavelet subbands (EWS) and difference of DC values (DDC). The lost blocks are recovered by the linear interpolation in the spatial domain using selected blocks. The method using only EWS performs well for horizontal and vertical edges, but not as well for diagonal edges. Conversely, only using DDC performs well diagonal edges with the exception of line- or roof-type edge profiles. Therefore, we combined EWS and DDC for better results. The proposed methods out performed the previous methods using fixed blocks.

Face Recognition based on Hybrid Classifiers with Virtual Samples (가상 데이터와 융합 분류기에 기반한 얼굴인식)

  • 류연식;오세영
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.40 no.1
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    • pp.19-29
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    • 2003
  • This paper presents a novel hybrid classifier for face recognition with artificially generated virtual training samples. We utilize both the nearest neighbor approach in feature angle space and a connectionist model to obtain a synergy effect by combining the results of two heterogeneous classifiers. First, a classifier called the nearest feature angle (NFA), based on angular information, finds the most similar feature to the query from a given training set. Second, a classifier has been developed based on the recall of stored frontal projection of the query feature. It uses a frontal recall network (FRN) that finds the most similar frontal one among the stored frontal feature set. For FRN, we used an ensemble neural network consisting of multiple multiplayer perceptrons (MLPs), each of which is trained independently to enhance generalization capability. Further, both classifiers used the virtual training set generated adaptively, according to the spatial distribution of each person's training samples. Finally, the results of the two classifiers are combined to comprise the best matching class, and a corresponding similarit measure is used to make the final decision. The proposed classifier achieved an average classification rate of 96.33% against a large group of different test sets of images, and its average error rate is 61.5% that of the nearest feature line (NFL) method, and achieves a more robust classification performance.

Study of Groundwater Recharge Rate Change by Using Groundwater Level and GRACE Data in Korea (지하수위와 GRACE 자료를 이용한 국내 지하수 함양량 변화 연구)

  • Jeon, Hang-Tak;Hamm, Se-Yeong;Jo, Young-Heon;Kim, Jinsoo;Park, Soyoung;Cheong, Jae-Yeol
    • The Journal of Engineering Geology
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    • v.29 no.3
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    • pp.265-277
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    • 2019
  • Changes in the amount, intensity, frequency, and type of precipitation, in conjunction with global warming and climate change, critically impact groundwater recharge and associated groundwater level fluctuations. Monthly gravity levels by the Gravity Recovery and Climate Experiment (GRACE) are acquired to monitor total water storage changes at regional and global scales. However, there are inherent difficulties in quantitatively relating the GRACE observations to groundwater level data due to the difficulties in spatially representing groundwater levels. Here three local interpolation methods (kriging, inverse distance weighted, and natural neighbor) were implemented to estimate the areal distribution of groundwater recharge changes in South Korea during the 2002-2016 period. The interpolated monthly groundwater recharge changes are compared with the GRACE-derived groundwater storage changes. There is a weak decrease in the groundwater recharge changes over time in both the GRACE observations and groundwater measurements, with the rate of groundwater recharge change exhibiting mean and median values of -0.01 and -0.02 cm/month, respectively.

Comparison of Forest Carbon Stocks Estimation Methods Using Forest Type Map and Landsat TM Satellite Imagery (임상도와 Landsat TM 위성영상을 이용한 산림탄소저장량 추정 방법 비교 연구)

  • Kim, Kyoung-Min;Lee, Jung-Bin;Jung, Jaehoon
    • Korean Journal of Remote Sensing
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    • v.31 no.5
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    • pp.449-459
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    • 2015
  • The conventional National Forest Inventory(NFI)-based forest carbon stock estimation method is suitable for national-scale estimation, but is not for regional-scale estimation due to the lack of NFI plots. In this study, for the purpose of regional-scale carbon stock estimation, we created grid-based forest carbon stock maps using spatial ancillary data and two types of up-scaling methods. Chungnam province was chosen to represent the study area and for which the $5^{th}$ NFI (2006~2009) data was collected. The first method (method 1) selects forest type map as ancillary data and uses regression model for forest carbon stock estimation, whereas the second method (method 2) uses satellite imagery and k-Nearest Neighbor(k-NN) algorithm. Additionally, in order to consider uncertainty effects, the final AGB carbon stock maps were generated by performing 200 iterative processes with Monte Carlo simulation. As a result, compared to the NFI-based estimation(21,136,911 tonC), the total carbon stock was over-estimated by method 1(22,948,151 tonC), but was under-estimated by method 2(19,750,315 tonC). In the paired T-test with 186 independent data, the average carbon stock estimation by the NFI-based method was statistically different from method2(p<0.01), but was not different from method1(p>0.01). In particular, by means of Monte Carlo simulation, it was found that the smoothing effect of k-NN algorithm and mis-registration error between NFI plots and satellite image can lead to large uncertainty in carbon stock estimation. Although method 1 was found suitable for carbon stock estimation of forest stands that feature heterogeneous trees in Korea, satellite-based method is still in demand to provide periodic estimates of un-investigated, large forest area. In these respects, future work will focus on spatial and temporal extent of study area and robust carbon stock estimation with various satellite images and estimation methods.

Development of Regularized Expectation Maximization Algorithms for Fan-Beam SPECT Data (부채살 SPECT 데이터를 위한 정칙화된 기댓값 최대화 재구성기법 개발)

  • Kim, Soo-Mee;Lee, Jae-Sung;Lee, Soo-Jin;Kim, Kyeong-Min;Lee, Dong-Soo
    • The Korean Journal of Nuclear Medicine
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    • v.39 no.6
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    • pp.464-472
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    • 2005
  • Purpose: SPECT using a fan-beam collimator improves spatial resolution and sensitivity. For the reconstruction from fan-beam projections, it is necessary to implement direct fan-beam reconstruction methods without transforming the data into the parallel geometry. In this study, various fan-beam reconstruction algorithms were implemented and their performances were compared. Materials and Methods: The projector for fan-beam SPECT was implemented using a ray-tracing method. The direct reconstruction algorithms implemented for fan-beam projection data were FBP (filtered backprojection), EM (expectation maximization), OS-EM (ordered subsets EM) and MAP-EM OSL (maximum a posteriori EM using the one-step late method) with membrane and thin-plate models as priors. For comparison, the fan-beam protection data were also rebinned into the parallel data using various interpolation methods, such as the nearest neighbor, bilinear and bicubic interpolations, and reconstructed using the conventional EM algorithm for parallel data. Noiseless and noisy projection data from the digital Hoffman brain and Shepp/Logan phantoms were reconstructed using the above algorithms. The reconstructed images were compared in terms of a percent error metric. Results: for the fan-beam data with Poisson noise, the MAP-EM OSL algorithm with the thin-plate prior showed the best result in both percent error and stability. Bilinear interpolation was the most effective method for rebinning from the fan-beam to parallel geometry when the accuracy and computation load were considered. Direct fan-beam EM reconstructions were more accurate than the standard EM reconstructions obtained from rebinned parallel data. Conclusion: Direct fan-beam reconstruction algorithms were implemented, which provided significantly improved reconstructions.

Development of an Approach for Analysing Vegetation Community Mosaic Using Landscape Metrics (경관지수를 활용한 식생군락 모자이크화 분석법)

  • Lee, Peter Sang-Hoon;Jeong, Jong-Chul
    • Journal of Cadastre & Land InformatiX
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    • v.47 no.1
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    • pp.161-178
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    • 2017
  • Whereas the demand for development of forested areas covering more than 60% of Korean territory, permission on the forest development has been still given from the perspective of effective land utilization rather than conservation. As the assessment of large forested areas usually focuses more on forest structure, it has its limitation of observing and analyzing the interior change in forest in this way. This study was aimed at computing landscape metrics using a presence vegetation map and FRAGTSTATS 4.2 and analyzing vegetation mosaics. Colonies in native vegetation were classified into a series of major groups and sub-groups based on the native species within the colonies. The colonies were investigated by analyzing a suite of landscape metrics - Core Area, Percentage of Landscape, Number of Patches, Patch Density, Largest Patch Index, Total Edge, Edge Density, Landscape Shape Index, Mean Patch Area, Euclidean Nearest Neighbor. In the Chungnam province major groups and sub-groups of colonies classified based on the proportion of pine and oak species, and pine species was the principal one in terms of distribution area. As for the competition between pines and oaks, while the coverage of pine-centered colonies were three times larger than those of oak-centered ones, pine colonies showed the greater number of patches and therefore higher fragmentation than oaks at the major group level. For the sub-groups, the largest coverage colonies were not only indicated by Pinus densiflora-Quesrcus mongolica colonies among P. densiflora-centered colonies, Q. accutissima colonies among Q. accutissima-centered ones, Q. accutissima-P. densiflora colonies among Q. accutissima-centered ones, Q. mongolica colonies among Q. mongolica-centered ones, P. thumbergii colonies among P. thumbergii-centered ones, and Q. serrata-Q. acutissima colonies among Q. serrata-centered ones, but also revealed more severely mosaicked than other smaller colonies. The overall mosaicking degree estimated by landscape metrics was considered useful for monitoring and investigating vegetation. However, in order to develop management strategy based on analyzing the reason for the mosaicking process and anticipating a trend in vegetation succession, it is essential to further study about ecological characteristics of each colony in the vegetation.