Study on the radioactive pollution in urban features using knowledgebased fuzzy classification of VHR satellite imagery

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Arabsaeedi Alireza; Malian Abbass; Arabi Mahdi

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Journal Paper

Paper Information

Journal: EARTH OBSERVATION AND GEOMATICS ENGINEERING Year:2020 | Volume:4 | Issue:1 Page(s): 81-97

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Information Journal Paper

Title

Study on the radioactive pollution in urban features using knowledgebased fuzzy classification of VHR satellite imagery

Author(s)

Arabsaeedi Alireza | Malian Abbass | Arabi Mahdi | Issue Writer Certificate

Keywords

Satellite Imagery

Nuclear Disaster

Fuzzy Logic

Image Segmentation

Rule-Based Classification

Abstract

Safety is of primary principles of living in human communities. Preparation and provision of necessary considerations for encountering hazards are main targets of the crisis management. Nuclear risks are one of hazards threatening in the human life. Since radioactive contaminants sustain for years after the incident, investigation into nuclear hazards and its damage on living environment and urban features is so vital. This study essentially aims at evaluating the risk of radioactive contaminants to urban land uses. Due to high resolution satellite images, remote sensing technology has been considered as an advanced technology to generate information covering urban areas. Information on land cover is one of the most important tools of management during crisis. Land cover maps can be prepared through techniques for high resolution satellite image processing and extracting urban features. In this study, the fuzzy objectoriented method is applied to classify such phenomena. In the proposed method, a fuzzy rule-based strategy and hierarchical model are employed to overcome noise between classes. Fuzzy Rule-Based Classification method is used as well as optimization and improving features of multi-scale analysis. Considering blocks of WorldView2 sensor, 91% of object detection is implemented with an average accuracy. When classification image of urban features is produced, the risk of radioactive contaminants to each recognized object is determined based on EDEM model.

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APA: Copy

Arabsaeedi, Alireza, Malian, Abbass, & Arabi, Mahdi. (2020). Study on the radioactive pollution in urban features using knowledgebased fuzzy classification of VHR satellite imagery. EARTH OBSERVATION AND GEOMATICS ENGINEERING, 4(1), 81-97. SID. https://sid.ir/paper/990330/en

Vancouver: Copy

Arabsaeedi Alireza, Malian Abbass, Arabi Mahdi. Study on the radioactive pollution in urban features using knowledgebased fuzzy classification of VHR satellite imagery. EARTH OBSERVATION AND GEOMATICS ENGINEERING[Internet]. 2020;4(1):81-97. Available from: https://sid.ir/paper/990330/en

IEEE: Copy

Alireza Arabsaeedi, Abbass Malian, and Mahdi Arabi, “Study on the radioactive pollution in urban features using knowledgebased fuzzy classification of VHR satellite imagery,” EARTH OBSERVATION AND GEOMATICS ENGINEERING, vol. 4, no. 1, pp. 81–97, 2020, [Online]. Available: https://sid.ir/paper/990330/en

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