• Title/Summary/Keyword: 통계적 분광특성

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Spectral Signatures of Tombs and their Classification (묘지의 분광적 특성과 통계적 분류)

  • Eunmi Change;Kyeong Park;Minho Kim
    • Journal of the Korean Geographical Society
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    • v.39 no.2
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    • pp.283-296
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    • 2004
  • More than 0.5 percent of land in Korea is used for cemetery and the rate is growing in spite of the increase in cremation these days. The systematic management of tombs may be possible through the ‘Feature Extraction’ method which is applied to the high-resolution satellite imagery. For this reason, this research focused on finding out the radiometric characteristics of tombs and the classification of them. An IKONOS image of northwest areas of Seoul with 8km x 10km dimension was analyzed. After sampling 24 tombs in the study area, the statistical radiometric characteristics of tombs are analyzed. And tombs were classified based on the criteria such as landscape, NDVI, and cluster analysis. In addition, it was investigated if the aspect or slope of the terrain influenced to the classification of tombs. As a result of this research, authors find that there is similarity between the classification tv NDVI and the classification through cluster analysis. And aspect or slope didn't have much influence on the classification of tombs.

Analysis of Image Fusion Methods for the Satellite Image Map Generation (위성 영상지도 제작을 위한 영상융합기법비교 분석)

  • 진경혁;유복모;조형진;유환희
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2002.04a
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    • pp.173-186
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    • 2002
  • 서로 다른 공간해상도와 분광해상도를 가진 영상들을 이용하여 영상지도를 제작할 때 공간해상도를 향상시킬 수 있는 영상융합기법에 대해 연구하였다. 사용된 영상은 IKONOS panchromatic 영상과 multispectral 위성영상, KOMPSAT-1호 위성영상과 SPOT XS 위성영상에 대해 Brovey, IHS, PCA, HPF, CN, MWD 융합기법을 적용하여 시각적 분석, 공간정보의 분포특성, 통계적 특성을 기준으로 분석하였으며, 시각적 분석에서는 IHS, PCA 융합기법이, 통계적 분석에서는 HPF, MWD 융합기법이 좋은 결과를 보여주었으며, 종합적인 결과분석을 고려할 때 MWD 융합기법이 원 영상의 분광정보를 가장 작게 왜곡시킴을 알 수 있었다.

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A Study on the Improvement of Image Fusion Accuracy Using Smoothing Filter-based Replacement Method (SFR기법을 이용한 영상 융합의 정확도 향상에 관한 연구)

  • Yun Kong-Hyun
    • Spatial Information Research
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    • v.14 no.1 s.36
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    • pp.85-94
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    • 2006
  • Image fusion techniques are widely used to integrate a lower spatial resolution multispectral image with a higher spatial resolution panchromatic image. However, the existing techniques either cannot avoid distorting the image spectral properties or involve complicated and time-consuming decomposition and reconstruction processing in the case of wavelet transform-based fusion. In this study a simple spectral preserve fusion technique: the Smoothing Filter-based Replacement(SFR) is proposed based on a simplified solar radiation and land surface reflection model. By using a ratio between a higher resolution image and its low pass filtered (with a smoothing filter) image, spatial details can be injected to a co-registered lower resolution multispectral image minimizing its spectral properties and contrast. The technique can be applied to improve spatial resolution for either colour composites or individual bands. The fidelity to spectral property and the spatial quality of SFM are convincingly demonstrated by an image fusion experiment using IKONOS panchromatic and multispectral images. The visual evaluation and statistical analysis compared with other image fusion techniques confirmed that SFR is a better fusion technique for preserving spectral information.

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Quantification of Soil Properties using Visible-NearInfrared Reflectance Spectroscopy (가시·근적외 분광 스펙트럼을 이용한 토양 이화학성 추정)

  • Choe, Eunyoung;Hong, S. Young;Kim, Yi-Hyun;Song, Kwan-Cheol;Zhang, Yong-Seon
    • Korean Journal of Soil Science and Fertilizer
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    • v.42 no.6
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    • pp.522-528
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    • 2009
  • This study focused on establishing prediction models using visible-near infrared spectrum to simultaneously detect multiple components of soils and enhancing the performance quality by suitably transformed input spectra and classification of soil spectral types for prediction model input. The continuum-removed spectra showed significant result for all cases in terms of soil properties and classified or bulk predictions. The prediction model using classified soil spectra at an absorption peak area around 500nm and 950nm efficiently indicating soil color showed slightly better performance. Especially, Ca and CEC were well estimated by the classified prediction model at $R^{2}$ > 0.8. For organic carbon, both classified and bulk prediction model had a good performance with $R^{2}$ > 0.8 and RPD> 2. This prediction model may be applied in global soil mapping, soil classification, and remote sensing data analysis.

Modeling of Plasma Etch Non-Uniformity by Using OES Information and Neural Network (OES 정보와 신경망을 이용한 플라즈마 식각들 비균일도의 모델링)

  • Kwon, Min-Ji;Kim, Byung-Whan
    • Proceedings of the KIEE Conference
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    • 2007.10a
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    • pp.403-404
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    • 2007
  • 소자 수율을 향상시키기 위해서는 웨이퍼 전체에 걸쳐 플라즈마 공정특성이 균일하게 분포되어야 한다. 본 연구에서는 Actinomeric 광 반사분광기 (Otical Emission Spectroscopy) 정보를 이용하여 식각률 비균일도에 대한 모델을 개발하였다. 제안된 기법은 Oxide 식각공정에서 수집한 데이터에 적용하였으며, 체계적인 모델링을 위해 공정데이터는 통계적 실험계획 법을 적용하여 수집되었다. 신경망의 예측성능은 유전자 알고리즘을 이용해서 증진시켰다. OES의 차수를 줄이기 위해 주인자 분석을 세 종류의 분산(100, 99, 98%)에 대해서 적용하였다. 개발된 모델은 발표된 이전의 모델에 비해 17% 증진된 예측성능을 보였다.

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Application of Spectral Indices to Drone-based Multispectral Remote Sensing for Algal Bloom Monitoring in the River (하천 녹조 모니터링을 위한 드론 다중분광영상의 분광지수 적용성 평가)

  • Choe, Eunyoung;Jung, Kyung Mi;Yoon, Jong-Su;Jang, Jong Hee;Kim, Mi-Jung;Lee, Ho Joong
    • Korean Journal of Remote Sensing
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    • v.37 no.3
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    • pp.419-430
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    • 2021
  • Remote sensing techniques using drone-based multispectral image were studied for fast and two-dimensional monitoring of algal blooms in the river. Drone is anticipated to be useful for algal bloom monitoring because of easy access to the field, high spatial resolution, and lowering atmospheric light scattering. In addition, application of multispectral sensors could make image processing and analysis procedures simple, fast, and standardized. Spectral indices derived from the active spectrum of photosynthetic pigments in terrestrial plants and phytoplankton were tested for estimating chlorophyll-a concentrations (Chl-a conc.) from drone-based multispectral image. Spectral indices containing the red-edge band showed high relationships with Chl-a conc. and especially, 3-band model (3BM) and normalized difference chlorophyll index (NDCI) were performed well (R2=0.86, RMSE=7.5). NDCI uses just two spectral bands, red and red-edge, and provides normalized values, so that data processing becomes simple and rapid. The 3BM which was tuned for accurate prediction of Chl-a conc. in productive water bodies adopts originally two spectral bands in the red-edge range, 720 and 760 nm, but here, the near-infrared band replaced the longer red-edge band because the multispectral sensor in this study had only one shorter red-edge band. This index is expected to predict more accurately Chl-a conc. using the sensor specialized with the red-edge range.

Image Segmentation based on Statistics of Sequential Frame Imagery of a Static Scene (정지장면의 연속 프레임 영상 간 통계에 기반한 영상분할)

  • Seo, Su-Young;Ko, In-Chul
    • Spatial Information Research
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    • v.18 no.3
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    • pp.73-83
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    • 2010
  • This study presents a method to segment an image, employing the statistics observed at each pixel location across sequential frame images. In the acquisition and analysis of spatial information, utilization of digital image processing technique has very important implications. Various image segmentation techniques have been presented to distinguish the area of digital images. In this study, based on the analysis of the spectroscopic characteristics of sequential frame images that had been previously researched, an image segmentation method was proposed by using the randomness occurring among a sequence of frame images for a same scene. First of all, we computed the mean and standard deviation values at each pixel and found reliable pixels to determine seed points using their standard deviation value. For segmenting an image into individual regions, we conducted region growing based on a T-test between reference and candidate sample sets. A comparative analysis was conducted to assure the performance of the proposed method with reference to a previous method. From a set of experimental results, it is confirmed that the proposed method using a sequence of frame images segments a scene better than a method using a single frame image.

SEM/EDS Analysis of the Enamel in Mesiodens (정중 과잉치 법랑질의 SEM/EDS 분석)

  • Oh, Nakyeong;Lee, Jaesik;Nam, Soonhyeun;Kwon, Taeyub;Kim, Hyunjung
    • Journal of the korean academy of Pediatric Dentistry
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    • v.46 no.1
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    • pp.101-110
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    • 2019
  • The aim of this study was to evaluate and compare the microstructural properties and mineralization quality of mesiodens with permanent and primary central incisors. Fifteen mesiodens, permanent and primary central incisors were collected. The enamel rod diameter and enamel thickness were observed and measured using field emission scanning electron microscope (FE-SEM). Chemical composition of the enamel was analyzed using energy dispersive X-ray spectrometer (EDS). The measurements were then assessed using the one-way ANOVA and Tukey test. There was no statistically significant difference in the enamel rod diameter between mesiodens and permanent central incisors. However, enamel rods of primary central incisors were smaller than remaining two groups. The thickness of enamel was thick in order of permanent central incisors, mesiodens, primary central incisors. In the composition analysis using EDS, there was no difference in the Ca/P ratio and Ca/C ratio between mesiodens and permanent central incisors, but small in primary central incisors. In conclusion, the microstructural properties of mesiodens were more similar to those of permanent central incisors compared to primary central incisors. Futher, the mineralization quality of mesiodens did not differ significantly from that of permanent central incisors.

Analysis the Impact of Topographic Factors on the Structure of Forest Vegetation in Deogyusan National Park (덕유산 국립공원 산림식생구조의 지형적 영향 분석)

  • Kim, Tae-Geun;Noh, Il;Jeong, Jong-Chul;Cho, Young-Hwan;Oh, Jang-Geun
    • Korean Journal of Ecology and Environment
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    • v.46 no.1
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    • pp.53-59
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    • 2013
  • The purpose of this study was to analyze the topographic effect of the LAI (Leaf Area Index), which has been widely used as an index that quantifies the structure of forest vegetation in Deogyusan National Park. With this aim, the study was conducted through a regression analysis which took as explanation the following variables: the elevation, slope, aspect, and soil moisture conditions. The LAI was taken as the response variable. Overall, the correlation between the Field-LAI and topographic factors was less than 0.5, which was relatively low. Except for topographic altitude, there was no statistical significance regarding the correlation with other factors. Meanwhile, regarding the orientation of the correlation, the higher the attitude, the steeper slope, the lower the soil moist, the lower the LAI value. The topographic altitude was found as a statistically significant explanation variable. The TWI (Topographic Wetness Index), which was used in this study to explain the soil moisture conditions, was not significantly related to the LAI distribution. The results of this study are expected to be utilized as basic data in more accurate forecasting the LAI distribution using remote sensing data.

Extraction of Primary Factors Influencing Dam Operation Using Factor Analysis (요인분석 통계기법을 이용한 댐 운영에 대한 영향 요인 추출)

  • Kang, Min-Goo;Jung, Chan-Yong;Lee, Gwang-Man
    • Journal of Korea Water Resources Association
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    • v.40 no.10
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    • pp.769-781
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    • 2007
  • Factor analysis has been usually employed in reducing quantity of data and summarizing information on a system or phenomenon. In this analysis methodology, variables are grouped into several factors by consideration of statistic characteristics, and the results are used for dropping variables which have lower weight than others. In this study, factor analysis was applied for extracting primary factors influencing multi-dam system operation in the Han River basin, where there are two multi-purpose dams such as Soyanggang Dam and Chungju Dam, and water has been supplied by integrating two dams in water use season. In order to fulfill factor analysis, first the variables related to two dams operation were gathered and divided into five groups (Soyanggang Dam: inflow, hydropower product, storage management, storage, and operation results of the past; Chungju Dam: inflow, hydropower product, water demand, storage, and operation results of the past). And then, considering statistic properties, in the gathered variables, some variables were chosen and grouped into five factors; hydrological condition, dam operation of the past, dam operation at normal season, water demand, and downstream dam operation. In order to check the appropriateness and applicability of factors, a multiple regression equation was newly constructed using factors as description variables, and those factors were compared with terms of objective function used in operation water resources optimally in a river basin. Reviewing the results through two check processes, it was revealed that the suggested approach provided satisfactory results. And, it was expected for extracted primary factors to be useful for making dam operation schedule considering the future situation and previous results.