Fusion of Markov Chain and SAX Method for Drought Probability Analysis (Case Study: Eastern District of Isfahan, Iran)

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Jouybari Moghaddam Yaser; Rostami Seyyed Qasem

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Journal: ENVIRONMENTAL HAZARDS MANAGEMENT Year:2018 | Volume:5 | Issue:3 Page(s): 295-311

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Information Journal Paper

Title

Fusion of Markov Chain and SAX Method for Drought Probability Analysis (Case Study: Eastern District of Isfahan, Iran)

Author(s)

Jouybari Moghaddam Yaser | Rostami Seyyed Qasem | Issue Writer Certificate

Keywords

SAXQ2

Markov ChainQ2

DroughtQ1

Remote SensingQ1

IsfahanQ1

Abstract

Drought is one of the most powerful natural disasters, which are affected on different aspects of the environment. Most of the time this phenomenon is immense in the arid and semi-arid area. Monitoring and prediction the severity of the Drought can be useful in the management of the natural disaster caused by Drought. Many indices were used in predicting Droughts such as SPI, VCI, and TVX. In this paper, based on three data sets (rainfall, NDVI, and land surface temperature) which are acquired from MODIS satellite imagery, time series of SPI, VCI, and TVX in time-limited between winters 2000 to summer 2015 for the east region of Isfahan province were created. Using these indices and fusion of symbolic aggregation approximation and hidden Markov Chain Drought was predicted for fall 2015. For this purpose, at first, each time series was transformed into the set of quality data based on the state of Drought (5 group) by using SAX. Algorithm then the probability matrix for the future state was created by using Markov hidden chain. The fall Drought severity was predicted by fusion the probability matrix and state of Drought severity in summer 2015. The prediction based on the likelihood for each state of Drought includes severe Drought, middle Drought, normal Drought, severe wet and middle wet. The analysis and experimental result from proposed algorithm show that the product of this algorithm is acceptable and the proposed algorithm is appropriate and efficient for predicting Drought using remote sensor data...

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APA: Copy

Jouybari Moghaddam, Yaser, & Rostami, Seyyed Qasem. (2018). Fusion of Markov Chain and SAX Method for Drought Probability Analysis (Case Study: Eastern District of Isfahan, Iran). ENVIRONMENTAL HAZARDS MANAGEMENT, 5(3 ), 295-311. SID. https://sid.ir/paper/386472/en

Vancouver: Copy

Jouybari Moghaddam Yaser, Rostami Seyyed Qasem. Fusion of Markov Chain and SAX Method for Drought Probability Analysis (Case Study: Eastern District of Isfahan, Iran). ENVIRONMENTAL HAZARDS MANAGEMENT[Internet]. 2018;5(3 ):295-311. Available from: https://sid.ir/paper/386472/en

IEEE: Copy

Yaser Jouybari Moghaddam, and Seyyed Qasem Rostami, “Fusion of Markov Chain and SAX Method for Drought Probability Analysis (Case Study: Eastern District of Isfahan, Iran),” ENVIRONMENTAL HAZARDS MANAGEMENT, vol. 5, no. 3 , pp. 295–311, 2018, [Online]. Available: https://sid.ir/paper/386472/en

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