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- W2950685929 abstract "Land use change models have seen a growth in use due to the availability of multi-temporal, high resolution images, and computational power. One such model, SLEUTH, is a popular cellular automata model for studying land use change, especially urban growth. While it is widely adopted and highly regarded, the computational complexity of the brute-force parameter sweep style of execution leads to long run times, which is further exacerbated by large area and high resolution images. In this study, we developed a distributed framework for SLEUTH, called DSLEUTH, for executing and managing subsets of the parameter space on a shared memory machine. This paper describes the framework and a performance study using two different data sets. The framework yielded a 20x speed up on both datasets using 40 processes." @default.
- W2950685929 created "2019-06-27" @default.
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- W2950685929 date "2019-04-01" @default.
- W2950685929 modified "2023-09-25" @default.
- W2950685929 title "Dsleuth: A Distributed Version Of Sleuth Urban Growth Model" @default.
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- W2950685929 doi "https://doi.org/10.23919/springsim.2019.8732879" @default.
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