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Information Journal Paper

Title

Comparison of Performance in Image Classification Algorithms of Satellite in Detection of Sarakhs Sandy zones

Pages

  19-36

Abstract

 1-Introduction: Wind erosion as an “ environmental threat” has caused serious problems in the world. Identifying and evaluating areas affected by wind erosion can be an important tool for managers and planners in the sustainable development of different areas. nowadays there are various methods in the world for zoning lands affected by wind erosion. One of the most important methods is the use of satellite images and various classification methods. Satellite imagery with features such as wide coverage, repeatability and continuous updating is particularly important in determining land cove. classification methods include Pixel based, Object oriented and map decision tree. Field studies on the spatial development of wind erosion sites are difficult and expensive to replicate and monitoring studies in these areas are not possible. the purpose of this study is to evaluate the classification methods in the detection of the Sarakhs plain Sandy zones in order to identify endangered sources of these zones. . . .

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    APA: Copy

    GOHARI, ZAHRA, ARA, HAIDEH, & Memarian, Hadi. (2019). Comparison of Performance in Image Classification Algorithms of Satellite in Detection of Sarakhs Sandy zones. ENVIRONMENTAL EROSION RESEARCHES, 9(2 (34) ), 19-36. SID. https://sid.ir/paper/377946/en

    Vancouver: Copy

    GOHARI ZAHRA, ARA HAIDEH, Memarian Hadi. Comparison of Performance in Image Classification Algorithms of Satellite in Detection of Sarakhs Sandy zones. ENVIRONMENTAL EROSION RESEARCHES[Internet]. 2019;9(2 (34) ):19-36. Available from: https://sid.ir/paper/377946/en

    IEEE: Copy

    ZAHRA GOHARI, HAIDEH ARA, and Hadi Memarian, “Comparison of Performance in Image Classification Algorithms of Satellite in Detection of Sarakhs Sandy zones,” ENVIRONMENTAL EROSION RESEARCHES, vol. 9, no. 2 (34) , pp. 19–36, 2019, [Online]. Available: https://sid.ir/paper/377946/en

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