Remote sensing and GIS for mapping and monitoring land cover and land use changes using support vector machine algorithm (Case study: Ilam dam watershed)

Journal Title: International Research Journal of Applied and Basic Sciences - Year 2014, Vol 8, Issue 4

Abstract

Presently, unplanned changes of land use have become a major problem. Most land use changes occur without a clear and logical planning with little attention to their environmental impact. Since those changes in land use take place in large and extensive areas, so, remote sensing technology is a necessary and valuable tool for land use change detection. In this study, images of TM (1988), ETM+ (2001) and ASTER (2007) are processed using Support Vector Machine (SVM) in Ilam dam watershed with 476.751 square kilometer and possible changes are investigated in two time periods, from 1988 to 2001 and 2001 to 2007. For accuracy assessment of this method, after collecting ground truth data, which are carried out through field visiting, Google Earth images and aerial photographs, overall accuracy and Kappa coefficient are used. Overall accuracies of the maps obtained through classification using SVM method for TM, ETM+ and ASTER images are 93%, 95% and 94%, respectively, that state high accuracy of this algorithm in classification of satellites images. During 1988 to 2001, lake was created due to dam construction and decreasing rangeland and in the second period from 2001 to 2007, change in cultivation method from horticulture to cropland and increasing rangeland and forest lands area was the most obvious change which occurred in this watershed.

Authors and Affiliations

Esmail Shahkooeei| Geography Department, Golestan University, Gorgan, Iran., Saleh Arekhi *| Geography Department, Golestan University, Gorgan, Iran. email: arekhi1348@yahoo.com, Aliakbar Najafi Kani| Gography Department, Golestan University, Gorgan, Iran.

Keywords

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  • EP ID EP6589
  • DOI -
  • Views 343
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How To Cite

Esmail Shahkooeei, Saleh Arekhi *, Aliakbar Najafi Kani (2014). Remote sensing and GIS for mapping and monitoring land cover and land use changes using support vector machine algorithm (Case study: Ilam dam watershed). International Research Journal of Applied and Basic Sciences, 8(4), 464-473. https://europub.co.uk/articles/-A-6589