• 제목/요약/키워드: spatial classification

검색결과 964건 처리시간 0.028초

대학생이 과학 관련 과제에서 사용한 분류 전략의 미시발생적 분석 (A Microgenetic Analysis on the Classification Strategy Used in Tasks Related to Science by College Students)

  • 최현동
    • 대한지구과학교육학회지
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    • 제4권2호
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    • pp.151-165
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    • 2011
  • Following a microgenetic design, this study was analysed the characteristic and the change of classification strategy that appear in college students' classification activity. The 4 tasks were developed for classification activity; a shell as a familiar real things, an animal fossil as a unfamiliar real things, a snow flake as a familiar picture cards and galaxy as a unfamiliar picture card. Achieved study to 6 college students who major in elementary education. Data were collected by interview with subjects, subject's classification schema, investigator's observation of subject's activity, and videotaped that record subject's subject classification process over an extended period of 6 times. Result proved in this study is as following. In the 6 times of the data collection procedures, a strategy F identifying concrete attribution of classification objects and a more detailed strategy X3 combining qualitative, spatial and dimensional attribution were found and more frequently used in both groups of college students which reported a classification process and did not report the process. While discovery and absorption of both a concrete classification strategy and a detailed classification strategy were rapidly developed in the reporting group, they were gradually developed in the non-reporting group. In addition to this, as the data collection procedures were progressing, the college students were familiar with change factors of classification tasks and in the case of pictures the classification strategy showed more desirable changes.

Improvement of Land Cover Classification Accuracy by Optimal Fusion of Aerial Multi-Sensor Data

  • Choi, Byoung Gil;Na, Young Woo;Kwon, Oh Seob;Kim, Se Hun
    • 한국측량학회지
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    • 제36권3호
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    • pp.135-152
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    • 2018
  • The purpose of this study is to propose an optimal fusion method of aerial multi - sensor data to improve the accuracy of land cover classification. Recently, in the fields of environmental impact assessment and land monitoring, high-resolution image data has been acquired for many regions for quantitative land management using aerial multi-sensor, but most of them are used only for the purpose of the project. Hyperspectral sensor data, which is mainly used for land cover classification, has the advantage of high classification accuracy, but it is difficult to classify the accurate land cover state because only the visible and near infrared wavelengths are acquired and of low spatial resolution. Therefore, there is a need for research that can improve the accuracy of land cover classification by fusing hyperspectral sensor data with multispectral sensor and aerial laser sensor data. As a fusion method of aerial multisensor, we proposed a pixel ratio adjustment method, a band accumulation method, and a spectral graph adjustment method. Fusion parameters such as fusion rate, band accumulation, spectral graph expansion ratio were selected according to the fusion method, and the fusion data generation and degree of land cover classification accuracy were calculated by applying incremental changes to the fusion variables. Optimal fusion variables for hyperspectral data, multispectral data and aerial laser data were derived by considering the correlation between land cover classification accuracy and fusion variables.

퍼지 클래스 벡터를 이용하는 다중센서 융합에 의한 무감독 영상분류 (Unsupervised Image Classification through Multisensor Fusion using Fuzzy Class Vector)

  • 이상훈
    • 대한원격탐사학회지
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    • 제19권4호
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    • pp.329-339
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    • 2003
  • 본 연구에서는 무감독 영상분류를 위하여 특성이 다른 센서로 수집된 영상들에 대한 의사결정 수준의 영상 융합기법을 제안하였다. 제안된 기법은 공간 확장 분할에 근거한 무감독 계층군집 영상분류기법을 개개의 센서에서 수집된 영상에 독립적으로 적용한 후 그 결과로 생성되는 분할지역의 퍼지 클래스 벡터(fuzzy class vector)를 이용하여 각 센서의 분류 결과를 융합한다. 퍼지 클래스벡터는 분할지역이 각 클래스에 속할 확률을 표시하는 지시(indicator) 벡터로 간주되며 기대 최대화 (EM: Expected Maximization) 추정 법에 의해 관련 변수의 최대 우도 추정치가 반복적으로 계산되어진다. 본 연구에서는 같은 특성의 센서 혹은 밴드 별로 분할과 분류를 수행한 후 분할지역의 분류결과를 퍼지 클래스 벡터를 이용하여 합성하는 접근법을 사용하고 있으므로 일반적으로 다중센서의 영상의 분류기법에 사용하는 화소수준의 영상융합기법에서처럼 서로 다른 센서로부터 수집된 영상의 화소간의 공간적 일치에 대한 높은 정확도를 요구하지 않는다. 본 연구는 한반도 전라북도 북서지역에서 관측된 다중분광 SPOT 영상자료와 AIRSAR 영상자료에 적용한 결과 제안된 영상 융합기법에 의한 피복 분류는 확장 벡터의 접근법에 의한 영상 융합보다 서로 다른 센서로부터 얻어지는 정보를 더욱 적합하게 융합한다는 것을 보여주고 있다.

도심 캠퍼스 공유공간의 공간 구조 변화에 대한 연구 - 그리드락의 반대 개념으로서의 공유 캠퍼스로의 변화에 대하여 - (A Study on the Change of Spatial Structures of Shared Space at Urban Campuses - The opposite concept of Gridlock upon the change to shared campuses -)

  • 강은기;백진
    • 대한건축학회논문집:계획계
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    • 제34권11호
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    • pp.145-156
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    • 2018
  • Urban campus, one of the main urban facilities, is the representative place that is struggling with 'gridlock'. Due to privatization of space among different departments and space shortages, gridlock has been occurring as a result. The urban campus trying to solve this problem by changing the quality of space, especially the structure of the shared space, which is expected to be the solution to the grid lock problem. The main purpose of this study is to investigate the structural change in the university's shared space based on paradigm transition. The theoretical consideration is to analyze the spatial characteristics of university shared space that appear at different stages through a new perspective that compares the gridlock phenomenon and the shared paradigm. The framework of the analysis of the shared space, which has recently been restructured, is classified into the spatial characteristics of collaborative space, the creative space, and the common/complex space. In addition, these spatial characteristics are again analyzed through the division of legislative facility classification, management governance subject, area, building location and layout, exposure to the outside as well as the analysis of student and staff entry and exit, sharing structure of site and space, and the classification of program characteristics. The results are as follows: The restructured space is systemized so that the management governance of each space would be connected to each other to share information and space. Furthermore, the spatial boundary between colleges or between campus spaces are not only physically, but categorically clear. The restructured space has semi (or in-between)-spatial characteristics such as the intersection in inside and outside of the pedestrian's circulation and the mixture of programs. This study could serve as principal references in presenting the systematic analysis of directions of the shared spatial structure for the urban campus where new educational space is required due to the changes in the university system.

Multiscale Spatial Position Coding under Locality Constraint for Action Recognition

  • Yang, Jiang-feng;Ma, Zheng;Xie, Mei
    • Journal of Electrical Engineering and Technology
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    • 제10권4호
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    • pp.1851-1863
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    • 2015
  • – In the paper, to handle the problem of traditional bag-of-features model ignoring the spatial relationship of local features in human action recognition, we proposed a Multiscale Spatial Position Coding under Locality Constraint method. Specifically, to describe this spatial relationship, we proposed a mixed feature combining motion feature and multi-spatial-scale configuration. To utilize temporal information between features, sub spatial-temporal-volumes are built. Next, the pooled features of sub-STVs are obtained via max-pooling method. In classification stage, the Locality-Constrained Group Sparse Representation is adopted to utilize the intrinsic group information of the sub-STV features. The experimental results on the KTH, Weizmann, and UCF sports datasets show that our action recognition system outperforms the classical local ST feature-based recognition systems published recently.

Development of the SAR Data Processing Package

  • Kim Kwang-Yong;Jeong Soo;Kim Kyoung-Ok
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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    • pp.526-528
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    • 2004
  • This paper describes the SAR data processing S/W package it will be able to process the SAR image. This package constructs the several modules: SAR Image processing module, measuring module of surface displacement using differential interferometric SAR method, classification module using the POLSAR data, SAR Focusing module. In this paper, briefly describe the algorithm that is adopted to the functions, and module architecture.

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국토변화탐지를 위한 지형분류체계 개선안 (Proposal of Feature Classification System for Land Change Detection)

  • 박준구;노명종;조우석;방기인
    • 대한공간정보학회지
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    • 제19권2호
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    • pp.9-17
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    • 2011
  • 국내 여러 기관에서 토지피복분류체계, 토지이용현황분류체계 등 국토의 정확한 현황 파악을 위해 다양한 지형분류체계를 활용 중에 있다. 그러나 이러한 분류체계로 국토변화를 탐지하기에는 적용성이 떨어지며, 변화지역을 추출하기에도 적합하지 않다는 문제점을 가지고 있다. 본 연구에서는 국토에 대한 자연적, 인위적 변화요소들을 모두 효과적으로 나타낼 수 있는 표준 지형분류체계를 제안하고자 한다. 이를 위해 국내외 유사 지형분류체계에 대한 비교 분석을 수행하고, 이를 바탕으로 표준 지형분류 항목을 제안하였다. 자동 지형분류 적용 가능성을 평가하기 위하여 감독분류 기반의 자동 지형분류와 선행지식 기반의 자동 지형분류를 수행하여 정확도를 평가하였다.

GPS/INS자료와 무감독 분류를 이용한 항공영상 자동 모자이킹 (Automatic Mosaicing of Airborne Multispectral Images using GPS/INS Data and Unsupervised Classification)

  • 장재동
    • 한국지리정보학회지
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    • 제9권1호
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    • pp.46-55
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    • 2006
  • 본 연구에서는 항공기로부터 얻어지는 다수의 다중 분광영상을 자동적인 모자이킹 방법을 개발함으로써 수작업을 최대한 줄이는데 목적을 두었다. DuncanTech MS4100 카메라를 이용하여 2436개의 녹색, 적색, 근적외 삼분광 영상이 획득되었다. 카메라 영상과 함께 관측한 LIDAR(LIght Detection And Ranging)자료와 항공기의 위치와 자세를 측정하기위해 GPS/INS(global positioning system/inertial navigation system)자료도 산출되었다. 다수의 다중 분광 영상은 우선 무감독 분류를 적용하여 영상 패턴으로 변환하였다. 인접한 영상의 패턴을 비교하여 각 영상의 상대적인 공간의 위치를 파악하였다. 모든 항공 영상 중에서 80%의 인접한 영상 패턴의 일치율을 파악하고 모자이킹할 수 있었다. 다음으로 GPS/INS자료와 무감독 분류를 혼합한 방법으로 항공 영상을 자동 모자이킹 수행하였다. GPS/INS자료와 영상 포착시점의 불일치로 연속되는 GPS/INS자료 중에 무감독 분류를 이용한 영상 패턴의 일치율을 조사하여 영상포착시점에 일치하는 GPS/INS자료를 선택하였다. 이 혼합방법으로 96%의 영상을 모자이킹했으며, LIDAR자료와의 검정에서 공간적 정도 RMSE는 1.44 m에 불과했다.

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SHADOW EXTRACTION FROM ASTER IMAGE USING MIXED PIXEL ANALYSIS

  • Kikuchi, Yuki;Takeshi, Miyata;Masataka, Takagi
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.727-731
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    • 2003
  • ASTER image has some advantages for classification such as 15 spectral bands and 15m ${\sim}$ 90m spatial resolution. However, in the classification using general remote sensing image, shadow areas are often classified into water area. It is very difficult to divide shadow and water. Because reflectance characteristics of water is similar to characteristics of shadow. Many land cover items are consisted in one pixel which is 15m spatial resolution. Nowadays, very high resolution satellite image (IKONOS, Quick Bird) and Digital Surface Model (DSM) by air borne laser scanner can also be used. In this study, mixed pixel analysis of ASTER image has carried out using IKONOS image and DSM. For mixed pixel analysis, high accurated geometric correction was required. Image matching method was applied for generating GCP datasets. IKONOS image was rectified by affine transform. After that, one pixel in ASTER image should be compared with corresponded 15×15 pixel in IKONOS image. Then, training dataset were generated for mixed pixel analysis using visual interpretation of IKONOS image. Finally, classification will be carried out based on Linear Mixture Model. Shadow extraction might be succeeded by the classification. The extracted shadow area was validated using shadow image which generated from 1m${\sim}$2m spatial resolution DSM. The result showed 17.2% error was occurred in mixed pixel. It might be limitation of ASTER image for shadow extraction because of 8bit quantization data.

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국립공원의 합리적 공간관리를 위한 비오톱 유형화 및 평가 연구 (Biotope Classification and Evaluation for Rational Spatial-management of National Park)

  • 염정헌;한봉호
    • 한국환경과학회지
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    • 제29권12호
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    • pp.1185-1198
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    • 2020
  • This study aimed to suggest a framework for biotope classification and evaluation based on habitat values to rationally establish management areas of national parks. The factors and indicators related to the biotope classification and evaluation were established based on integration from those of previous studies. The decision tree evaluation process was applied to the classification and evaluation of the biotope type level. The evaluation of the biotope group level was carried out to determine the weight and the AUEM (Adding Up Estimation Matrix) was applied for the final grades. As a result, the biotope type of Seolaksan National Park was classified into 43 types and Odaesan National Park was classified into 41 types. Bukhansan National Park, which is located in a metropolitan city, was classified into 49 types. In terms of biotope evaluation, grade III had a ratio of 50.6%, the highest in Seolaksan national park. The ratios of grade I and grade II, which have great ecological-value, were respectively 12.0% and 36.5%. Grade II was 48.2%, the highest ratio in Odaesan National Park. The ratios of grades I and II were 10.8% and 37.9%, respectively. Grade III was 54.8%, the highest ratio in Bukhansan national park, and the ratios of grade I and grade II, which have great ecological-value were, respectively, 11.4% and 25.7%. The biotope values of major national parks were evaluated according to the type focusing on the actual vegetation. This framework can be considered for application to the spatial management of other types of protected areas.