A PROBABILITY MODEL FOR DROUGHT PREDICTION USING FUSION OF MARKOV CHAIN AND SAX METHODS

This article is about using remote sensing data to estimate the date and magnitude of the impending earthquakes. An earthquake can also affect the environment. Damage to the environment can destroy and lose lives and be more dangerous than earthquakes. The damage sustained by earthquakes is due to the secondary effects of man-made materials on the environment. Water pipes are broken and the ground is flooded, and gas, electricity and scattered fuel lines cause fires.

This paper represents a proper input by combining temperature, fault and time for different thermal anomaly detection methods and then using them for estimating earthquake intensity. Results show that the proposed input data has better outcome in each of the thermal anomaly detection methods compared to the ordinary input data and the estimated intensities of most earthquakes are very close to the actual intensities. This approach can be used as a tool for future unknown earthquakes prediction.