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ETD Abstract Container

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Land Cover Classification Using Linear Support Vector Machines

Shakeel, Mohammad Danish
http://rave.ohiolink.edu/etdc/view?acc_num=ysu1231812653

Abstract Details

2008, Master of Science in Mathematics, Youngstown State University, Department of Mathematics and Statistics.
GIS has been an effective tool in identifying and recognizing urban patterns. Various techniques like Support Vector Machines, artificial neural networks have been used with GIS to classify the patterns for urban analysis. Liblinear has emerged as another effective tool which produces results in much lesser time without compromising the accuracy. In this thesis the datasets used were extracted using GIS. The datasets were from the Ohio state counties namely the Delaware, Holmes, Mahoning and Medina counties. Each had over a million records and contained seven independent variables related to urban development and a class label which denotes the urban areas versus the rural areas. Using Liblinear, Libsvm, Rapid Miner and Weka some experiments were carried out over smaller datasets and the results have been shown. It can be seen that Liblinear is as effective as Libsvm while the latter takes much longer time for producing the results. The results can help indentify geographical patterns related to urban land use.
Alina Lazar, PhD (Advisor)
Jamal Tartir, PhD (Committee Member)
Neil Flowers, PhD (Committee Member)
35 p.
Computer Science; Geography
support vector machines; data mining; geographic information systems; urban pattern recognition

Recommended Citations

Citations

  • Shakeel, M. D. (2008). Land Cover Classification Using Linear Support Vector Machines [Master's thesis, Youngstown State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1231812653

    APA Style (7th edition)

  • Shakeel, Mohammad. Land Cover Classification Using Linear Support Vector Machines. 2008. Youngstown State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ysu1231812653.

    MLA Style (8th edition)

  • Shakeel, Mohammad. "Land Cover Classification Using Linear Support Vector Machines." Master's thesis, Youngstown State University, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1231812653

    Chicago Manual of Style (17th edition)

ysu1231812653
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© 2008, all rights reserved.
This open access ETD is published by Youngstown State University and OhioLINK.