Pariaman City is one of cities in Indonesia that has a very high incidence of earthquakes both on land and under the sea. This is caused the Pariaman City region is directly adjacent to the Indian Ocean which is the convergence for two tectonic plates, namely the Eurasian Plate and the Indo-Australian Plate. One of these plates goes down into the other plate then it happens the subduction. Subduction earthquakes that result from convergence two plates very active in generating tsunami waves. This study aims to analyze the spatial dynamics model for tsunami prone areas in Pariaman City by using the Cellular Automata-Markov Chains (CA-MC) method, this method is used to modeling tsunami prone areas in Pariaman City in 2030 based on driving factors that given to models. Driving factors used In this study are elevation, slope, distance from the coastline, distance from the road, and distance from the river. CA-MC presents land cover changes depend on neighboring cells. After the model is generated, then analyzed based on Pariaman City spatial plan in 2030 to be compared. To obtain tsunami prone areas, the prediction model for 2030 land cover is overlaid with tsunami hazard. The results showed that from 2018 to 2030, there was an increase in tsunami prone areas with low, medium and high classes in settlements areas.
|Number of pages||18|
|Journal||Journal of Computational and Theoretical Nanoscience|
|Publication status||Published - Feb 2020|
- Cellular Automata Markov Chains
- Land Cover
- Pariaman City
- Tsunami Prone Areas