Comparing support vector machines with logistic regression for calibrating cellular automata land use change models

Comparing support vector machines with logistic regression for calibrating cellular automata land use change models

Land use change models enable the exploration of the drivers and consequences of land use dynamics. A broad array of modeling approaches are available and each type has certain advantages and disadvantages depending on the objective of the research. This paper presents an approach combining cellular...

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Bibliographic Details
Main Authors: Ahmed Mustafa, Andreas Rienow, Ismaïl Saadi, Mario Cools, Jacques Teller
Format: Article
Language:English
Published: Taylor & Francis Group 2018-01-01
Series:European Journal of Remote Sensing
Subjects:
Land use change
urban expansion
cellular automata
supported vector machines
logistic regression
Wallonia
Online Access:http://dx.doi.org/10.1080/22797254.2018.1442179

Internet

http://dx.doi.org/10.1080/22797254.2018.1442179

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