Land_uses_prediction

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Land_uses_prediction

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A Cellular Automata Markov (CAM) model for land use change prediction using GIS and Python

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# Land_uses_prediction
A Cellular Automata Markov (CAM) model for land use change prediction using GIS and Python
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In this repository, a Cellular Automata Markov (CAM) model is presented and applied through a combination of Geographic Information Systems (GIS) and Python, 
to predict land changes and provide future land use maps.
The inputs are historical land use maps at a five-year time-step from 2006 to 2021, and the outputs include future land use maps until 2051, again at a five-year time-step.
Various validation techniques are explored for the predicted maps, based on the historical data, including Accuracy, Mean Absolute Error (MAE), Root Mean Square Error (RMSE), 
the Kappa coefficient (κ), and Confusion Matrix statistics. 
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The main file is the pdf with the background information and the process. 
There is a more detailed pdf (supporting info) with step-by-step guidance and screenshots from GIS and the Python script to execute the model.
The Python script and the data of the model are also provided.
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Reference:
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Alamanos, A. (2023). A Cellular Automata Markov (CAM) model for future land use change prediction using GIS and Python. DOI: 10.13140/RG.2.2.20309.19688. Available at: https://github.com/Alamanos11/Land_uses_prediction

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