• 제목/요약/키워드: Remotely sensed images

검색결과 122건 처리시간 0.026초

Unsupervised segmentation of Multi -Source Remotely Sensed images using Binary Decision Trees and Canonical Transform

  • Mohammad, Rahmati;Kim, Jung-Ha
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.23.4-23
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    • 2001
  • This paper proposes a new approach to unsupervised classification of remotely sensed images. Fusion of optic images (Landsat TM) and radar data (SAR) has beer used to increase the accuracy of classification. Number of clusters is estimated using generalized Dunns measure. Performance of the proposed method is best observed comparing the classified images with classified aerial images.

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USING REMOTELY SENSED DATA TO ESTIMATE THE SURFACE HEAT FLUXES OVER TAIWAN'S CHAIYI PLAIN

  • Chang, Tzu-Yin;Liou, Yuei-An
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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    • pp.422-425
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    • 2007
  • Traditionally, surface energy fluxes are obtained by model simulations or empirical equations with auxiliary meteorological data. These methods may not effectively represent the surface heat fluxes in a regional scale due to scene variability. On the other hand, remote sensing has the advantage to acquire data of a large area in an instantaneous view. The remotely sensed data can be further used to retrieve surface radiation and heat fluxes over a large area. In this study, the airborne and satellite images in conjunction with meteorological data and ground observations were used to estimate the surface heat fluxes over Taiwan's Chaiyi Plain. The results indicate that surface heat fluxes can be properly determined from both airborne and satellite images. The correlation coefficient of surface heat fluxes with in situ corresponding observations is over 0.60. We also observe that the remotely sensed data can efficiently provide a long term monitoring of surface heat fluxes over Taiwan's Chaiyi Plain.

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국립공원관리를 위한 위성영상 활용방안에 관한 연구 -북한산 국립공원을 사례로- (A Study of Application of Remotely Sensed Data for the Management of National Parks - in case of Bukhansan National Park-)

  • 박경;장은미;신상희
    • 환경영향평가
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    • 제10권3호
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    • pp.167-174
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    • 2001
  • National Parks in Korea occupy about four percents of South Korean land. This paper aims to prove the potentiality of the application of remotely sensed data for the effective management of National Parks. Different satellite images such as Landsat TM, IRS-1C, Alternative image, and IKONOS image are analyzed for the detection of changes, the extraction of degraded areas, and the comparison of Normalized Difference Vegetation Index (NDVI) in Bukhansan National Park. The artificial structures such as buildings and paved areas are overvalued in relatively higher resolution data. The result showed that the choice of images should be determined according to specific purposes and the combination of different resolution data may be the solution for the effective management of National Park.

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원격탐사 영상의 퍼지 최대우도 분류결과를 이용한 GIS 데이터베이스 구축 기법 (A Methodology for GIS Database Implementation using Fuzzy Maximum Likelihood Classification Products of Remotely Sensed Images)

  • 양인태;김흥규;최영재;박재훈
    • 한국측량학회지
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    • 제17권2호
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    • pp.189-196
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    • 1999
  • 지금까지 원격탐사 영상의 분류 결과를 GIS에 하나의 레이어 또는 속성항목으로 이용하기 위한 다양한 연구가 진행되어오고 있으나 퍼지분류결과를 GIS에 이용하려는 시도는 그리 많지 않았던 것이 사실이다. 그러므로, 이 연구에서는 기존에 많이 이용되고 있는 원격탐사 영상의 분류방법에 비해 정확도 면에서 보다 신뢰할 수 있고 분류항목별 분류결과를 독립적으로 추출할 수 있는 퍼지감독분류 결과를 GIS에 적용해보고자 하는 의도에서 시작되었다. 이 연구의 진행과정에서 퍼지분류 결과를 GIS 데이터베이스의 그리드 데이터로 변환하였으며, Membership Grade Value 파일들은 지형정보체계의 테이블 데이터로 변환하여 포인터 레이어를 매개로 그리드의 각 셀에 대한 Membership Grade Value를 확인할 수 있도록 함으로써 퍼지 분류 영상을 GIS 데이터베이스로 이용할 수 있도록 하였다.

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퍼지 신경회로망을 이용한 원격감지 영상의 분류 (Classification of remotely sensed images using fuzzy neural network)

  • 이준재;황석윤;김효성;이재욱;서용수
    • 전자공학회논문지S
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    • 제35S권3호
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    • pp.150-158
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    • 1998
  • This paper describes the classification of remotely sensed image data using fuzzy neural network, whose algorithm was obtained by replacing real numbers used for inputs and outputs in the standard back propagation algorithm with fuzzy numbers. In the proposed method, fuzzy patterns, generated based on the histogram ofeach category for the training data, are put into the fuzzy neural network with real numbers. The results show that the generalization and appoximation are better than that ofthe conventional network in determining the complex boundary of patterns.

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Change Detection of Buildings Using High Resolution Remotely Sensed Data

  • Zeng, Yu;Zhang, Jixian;Wang, Guangliang
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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    • pp.530-535
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    • 2002
  • An approach for quickly updating GIS building data using high resolution remotely sensed data is proposed in this paper. High resolution remotely sensed data could be aerial photographs, satellite images and airborne laser scanning data. Data from different types of sensors are integrated in building extraction. Based on the extracted buildings and the outdated GIS database, the change-detection-template can be automatically created. Then, GIS building data can be fast updated by semiautomatically processing the change-detection-temp late. It is demonstrated that this approach is quick, effective and applicable.

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A STUDY ON THE CALCULATING THE AMOUNT OF UPDATING DIGITAL MAP USING REMOTELY SENSED DATA

  • Yoon Yeo-Sang;Cho Hong-Beom;Kang In-Gu
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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    • pp.272-275
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    • 2005
  • The digital map expresses natural topographies and artificial things with 3D position coordinates in the computer such as the road, railway, building, river, mountain, paddy and dryland. Therefore, the digital map is regarded as an important factor in the information-oriented society. However, it is difficult to maintain the most recent topographic information all the times because of restricted budget and time. For that, the efficient method corresponded with the digital map should be presented. This study aims to suggest the way to make an estimate of updating cost for 1:5,000 scale digital map by using remotely sensed data. To predict updating area of the digital map, the screen digitizing method was applied to the overlapped images and digital maps.

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Infrastructure of Grid-based Distributed Remotely Sensed Images Processing Environment and its Parallel Intelligence Algorithms

  • ZHENG, Jiang;LUO, Jian-Cheng;Hu, Cheng;CHEN, Qiu-Xiao
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.1284-1286
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    • 2003
  • There is a growing demand on remotely sensed and GIS data services in modern society. However, conventional WEB applications based on client/server pattern can not meet the criteria in the future . Grid computing provides a promising resolution for establishing spatial information system toward future applications. Here, a new architecture of the distributed environment for remotely sensed data processing based on the middleware technology was proposed. In addition, in order to utilize the new environment, a problem had to be algorithmically expressed as comprising a set of concurrently executing sub-problems or tasks. Experiment of the algorithm was implemented, and the results show that the new environmental can achieve high speedups for applications compared with conventional implementation.

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Increasing Spatial Resolution of Remotely Sensed Image using HNN Super-resolution Mapping Combined with a Forward Model

  • Minh, Nguyen Quang;Huong, Nguyen Thi Thu
    • 한국측량학회지
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    • 제31권6_2호
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    • pp.559-565
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    • 2013
  • Spatial resolution of land covers from remotely sensed images can be increased using super-resolution mapping techniques for soft-classified land cover proportions. A further development of super-resolution mapping technique is downscaling the original remotely sensed image using super-resolution mapping techniques with a forward model. In this paper, the model for increasing spatial resolution of remote sensing multispectral image is tested with real SPOT 5 imagery at 10m spatial resolution for an area in Bac Giang Province, Vietnam in order to evaluate the feasibility of application of this model to the real imagery. The soft-classified land cover proportions obtained using a fuzzy c-means classification are then used as input data for a Hopfield neural network (HNN) to predict the multispectral images at sub-pixel spatial resolution. The 10m SPOT multispectral image was improved to 5m, 3,3m and 2.5m and compared with SPOT Panchromatic image at 2.5m resolution for assessment.Visually, the resulted image is compared with a SPOT 5 panchromatic image acquired at the same time with the multispectral data. The predicted image is apparently sharper than the original coarse spatial resolution image.

An Elliptical Basis Function Network for Classification of Remote-Sensing Images

  • Luo, Jian-Cheng;Chen, Qiu-Xiao;Zheng, Jiang;Leung, Yee;Ma, Jiang-Hong
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.1326-1328
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    • 2003
  • An elliptical basis function (EBF) network is proposed in this study for the classification of remotely sensed images. Though similar in structure, the EBF network differs from the well-known radial basis function (RBF) network by incorporating full covariance matrices and uses the expectation-maximization (EM) algorithm to estimate the basis functions. Since remotely sensed data often take on mixture -density distributions in the feature space, the proposed network not only possesses the advantage of the RBF mechanism but also utilizes the EM algorithm to compute the maximum likelihood estimates of the mean vectors and covariance matrices of a Gaussian mixture distribution in the training phase. Experimental results show that the EM-based EBF network is faster in training, more accurate, and simpler in structure.

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