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035 _a.b10157311
099 9 _aAIT Thesis no. CS-94-41
100 1 _aBahani, Pervin Ong
245 1 2 _aA computer assisted interpretation system for land cover classification with NOAA AVHRR data
260 _aBangkok :
_bAsian Institute of Technology,
_c1994
300 _a56 leaves
490 1 _aThesis ;
_vno. CS-94-41
500 _aA thesis submitted in partial fulfillment of the requirements for the degree of Master of Science, School of Engineering and Technology
502 _aThesis (M.Sc.) - Asian Institute of Technology, 1994
520 _aIn this study, a technique for land cover classification was proposed and implemented. The proposed method uses a combination of supervised and unsupervised classification. Split and merge clustering is applied to the selected training data and the output clusters will be used in the assignment of the unknown pixel of the image to be classified. Two existing conventional methods namely, maximum likelihood classification method (MLC) and minimum distance classification method (MDC) were also implemented. The first method is based on statistical probabilities, the second method uses distance as a discriminant to classify an unknown input pixel. Test sites were selected and the performances of the three implemented classification methods were compared. The test sites were classified into four types. The classification results showed that the proposed method can give better classification accuracy, however classification time is longer for the proposed classification method compared to both MLC and MDC.
650 0 _aRemote sensing
700 1 _aMurai, Shunji,
_eChairperson
700 0 _aVilas Wuwongse,
_eExamination Committee
700 1 _aOchi, Shiro,
_eExamination Committee
710 2 _aThe Government of Japan,
_eScholarship Donor
810 2 _aAsian Institute of Technology.
_tThesis ;
_vno. CS-94-41
856 _3Full-Text
_uhttp://203.159.5.9/ait-thesis/detail.php?q=B15767
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909 _aBarcode : 30050003102398
_bCREATED : 1994-05-16
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909 _aBarcode : 30050120356448
_bCREATED : 2016-06-14
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