:: Volume 6, Issue 1 (3-2015) ::
GEJ 2015, 6(1): 31-40 Back to browse issues page
Mapping Changes in Urban Areas Using Satellite Imagery with an Emphasis on Maximum Use of Old Maps
S. Hajahmadi, M. Mokhtarzedeh, A. Mohammadzadeh, M. J. Valadanzoej
Abstract:   (5190 Views)

Due to the rapid transformation of the societies, and the consequent growth of the cities, it is necessary to study these changes in order to achieve better control and management of urban areas and assist the decision-makers. Accordingly it is essential to design a proper solution for image classification. For this purpose, there are numerous methods that can be divided into two general categories pixel-based and object-based methods. Object-based classification and information extraction methods are usually known as being more effective for classification and interpreting purposes especially in urban areas. However supervised object-based classification, like other supervised methods, requires accurate and sufficient training data. Due to these facts it is highly motivated to design a efficient method to provide reliable training data from existing data sets. In this regard, the training samples was extracted from map and purified by using K nearest neighbor and k-means methods. The results of training data editition improved over 15 percents in the classification accuracy. And change map extraction accuracy in the best case was 98.08 percent.

Keywords: Minimum Distance Classification, Change Map Extraction, Training Data Edition, K Nearest Neighbor, k-means
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Type of Study: Research | Subject: Photo&RS


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Volume 6, Issue 1 (3-2015) Back to browse issues page