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Identification of land use/cover changes mapping in an urban area using satellite imagery & support vector machine algorithm (case study: Some’esara)

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Research Paper 01/07/2015
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Identification of land use/cover changes mapping in an urban area using satellite imagery & support vector machine algorithm (case study: Some’esara)

Neda Musavi
J. Bio. Env. Sci.7( 1), 543-556, July 2015.
Certificate: JBES 2015 [Generate Certificate]
Key: Change detectionGilan provincePost classification methodSome'esara townshipSupport vector machine (SVM)

Abstract

Land-use change processes present a variety of trajectories depending on local conditions, the regional context and external influences. This study is an in-depth analysis of spatial and temporal land-use change in a township mountain area for the data period 1989 to 2014 in northwest of Iran. 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. Some’esara Township with 1254.543 square kilometer and possible changes are investigated in two times, from 1989 to 2014. 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+ images are 93%, 95% respectively, that state high accuracy of this algorithm in classification of satellites images. During 1989 to 2014. The methods enabled four periods to be identified revealing a distinctive evolution in land use, in which urban consolidation is present consistently, together with rotation of the wetland typology e involving marsh degradation, gains from agro-forest land or sparsely vegetated areas and the appearance of urban areas.

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