COI code: ICOPMAS13_053
Paper Language: English
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Authors CLASSIFICATION OF SATELLITE IMAGERY WITH TWO APPROACHES OF SPATIAL ATTRACTION (CASE STUDY: PARTS OF HORMOZGAN SHORES)Alireza Tilkoo - Civil engineering Department, Iran University of Science and Technology
Seyed Mostafa Siadatmousavi - Civil engineering Department, Iran University of Science and Technology
Barat Mojaradi - Civil engineering Department, Iran University of Science and Technology
Abstract:A wide range of methods have been evaluated for analyzing aerial and satellite images. Remote sensing data are used in many applications. Typically, the process ofimage classification is started to convert data into meaningful information . In this article, two approaches based on the theory of spatial dependence are described.Spatial dependency is known as attracting the near observations more than the distant observations. The first th eory of spatial dependence was presented by Atkinson in1997 . In spatial attraction models, this spatial dependence is interpreted by attraction between neighboring pixels or subpixels . The results show thatthe modified subpixel/spatial attraction model (MSPSAM) with an overall accuracy of 99.83% and kappa of 0.99 has a good performance for classification. The results confirmthe quality of both methods for the classification of satellite imagery.
COI code: ICOPMAS13_053
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Tilkoo, Alireza; Seyed Mostafa Siadatmousavi & Barat Mojaradi, 2018, CLASSIFICATION OF SATELLITE IMAGERY WITH TWO APPROACHES OF SPATIAL ATTRACTION (CASE STUDY: PARTS OF HORMOZGAN SHORES), 13th International Conference on Coasts, Ports and Marine Structures, تهران, سازمان بنادر و دريانوردي, https://www.civilica.com/Paper-ICOPMAS13-ICOPMAS13_053.htmlInside the text, wherever referred to or an achievement of this article is mentioned, after mentioning the article, inside the parental, the following specifications are written.
First Time: (Tilkoo, Alireza; Seyed Mostafa Siadatmousavi & Barat Mojaradi, 2018)
Second and more: (Tilkoo; Siadatmousavi & Mojaradi, 2018)
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Type: state university
Paper No.: 20248
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