An Approach based on Adaptive Decision Tree for Land Cover Change Prediction in Satellite Images

Ahlem Ferchichi, Wadii Boulila, Riadh Farah

2013

Abstract

Decision tree (DT) prediction algorithms have significant potential for remote sensing data prediction. This paper presents an advanced approach for land-cover change prediction in remote-sensing imagery. Several methods for decision tree change prediction have been considered: probabilistic DT, belief DT, fuzzy DT, and possibilistic DT. The aim of this study is to provide an approach based on adaptive DT to predict land cover changes and to take into account several types of imperfection related to satellite images such as: uncertainty, imprecision, vagueness, conflict, ambiguity, etc. The proposed approach applies an artificial neural network (ANN) model to choose the appropriate gain formula to be applied on each DT node. The considered approach is validated using satellite images representing the Saint-Paul region, commune of Reunion Island. Results show good performances of the proposed framework in predicting change for the urban zone.

Paper Citation

in Harvard Style

Ferchichi A., Boulila W. and Farah R. (2013). An Approach based on Adaptive Decision Tree for Land Cover Change Prediction in Satellite Images . In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval and the International Conference on Knowledge Management and Information Sharing - Volume 1: KDIR, (IC3K 2013) ISBN 978-989-8565-75-4, pages 82-90. DOI: 10.5220/0004519700820090

in Bibtex Style

@conference{kdir13,
author={Ahlem Ferchichi and Wadii Boulila and Riadh Farah},
title={An Approach based on Adaptive Decision Tree for Land Cover Change Prediction in Satellite Images},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval and the International Conference on Knowledge Management and Information Sharing - Volume 1: KDIR, (IC3K 2013)},
year={2013},
pages={82-90},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004519700820090},
isbn={978-989-8565-75-4},
}

in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval and the International Conference on Knowledge Management and Information Sharing - Volume 1: KDIR, (IC3K 2013)
TI - An Approach based on Adaptive Decision Tree for Land Cover Change Prediction in Satellite Images
SN - 978-989-8565-75-4
AU - Ferchichi A.
AU - Boulila W.
AU - Farah R.
PY - 2013
SP - 82
EP - 90
DO - 10.5220/0004519700820090