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Fast generation of LULC maps for temporal studies in North-Western Africa
KTH, School of Electrical Engineering (EES), Signal Processing.ORCID iD: 0000-0003-3054-7210
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2014 (English)In: Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International / [ed] IEEE International, IEEE conference proceedings, 2014, 4280-4283 p.Conference paper (Refereed)
Abstract [en]

This paper provides an objective evaluation of six supervised classification techniques and three state of the art features, with the objective of obtaining a single combination of them that provides both robustness and objective performance improvements. As a conclusion, a simple procedure for obtaining LULC maps with four targeted classes is proposed.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2014. 4280-4283 p.
National Category
Signal Processing
Research subject
Electrical Engineering
URN: urn:nbn:se:kth:diva-157117DOI: 10.1109/IGARSS.2014.6947435ISI: 000349688106037ScopusID: 2-s2.0-84911453960OAI: diva2:769182
Joint International Geoscience and Remote Sensing Symposium (IGARSS 2014) / 35th Canadian Symposium on Remote Sensing (35th CSRS), 13-18 July 2014, Quebec City, QC, USA
TELECAN (MAC/3/C181: PCT-MAC 2007/2013)

QC 20141209

Available from: 2014-12-05 Created: 2014-12-05 Last updated: 2015-04-08Bibliographically approved

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FastLULC_delAguila_Pol(13330 kB)79 downloads
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