[ JM13] Robust Reduction Dimension for Mapping of Rice Field

Conférence Internationale avec comité de lecture : World Congress on Engineering, July 2013, Vol. III, pp.1531-1536, Series ISBN 978-988-19252-9-9, London, GB,

Mots clés: C-Step, depth function, minimum vector variance, principal component analysis, remote sensing, robustness

Résumé: Mapping of rice field is done with a conventional two step process: training process and classification.The results of mapping process are highly influenced by accuracy of spectral reference obtained in training process. Robust reduction dimension improvements are proposed for computing estimators. The first improvement consists in a modification of robust subset with preliminary data inspection. The inspection is useful for screening and removing the potential outliers. As a second improvement the replacement of process inversion of covariance matrix with a new depth function is proposed. The case study of research is rice fields located in Karawang, West Java. Data from MODIS (Moderate Resolution Imaging Spectroradiometer) satellite are used for rice field mapping.

Equipe: msdma


@inproceedings {
title="{Robust Reduction Dimension for Mapping of Rice Field}",
author=" D. Herwindiati and L. Jaupi and S. Mulyono ",
booktitle="{World Congress on Engineering}",
series="ISBN 978-988-19252-9-9",
address="London, GB",