Using GEOBIA for feature extraction from multitemporal SAR images: Preliminary results

Donato Amitrano; Francesca Cecinati; Gerardo Di Martino; Antonio Iodice; Pierre Philippe Mathieu; Daniele Riccio; Giuseppe Ruello

doi:10.1109/RTSI.2017.8065940

Using GEOBIA for feature extraction from multitemporal SAR images: Preliminary results

Donato Amitrano, Francesca Cecinati, Gerardo Di Martino, Antonio Iodice, Pierre Philippe Mathieu, Daniele Riccio, Giuseppe Ruello

Department of Architecture & Civil Engineering

Research output: Chapter or section in a book/report/conference proceeding › Chapter in a published conference proceeding

Abstract

In this paper, we explore the possibility to exploit GEOBIA concepts for extracting features from multitemporal SAR images. The proposed processing chain is feed by the recently introduced products of the Level-1a and Level-1β families and aims at providing an unsupervised tool for information extraction particularly oriented toward the end-user community. The principal characteristics and the effectiveness of the framework are illustrated through two examples concerning urban area mapping and small reservoir extraction in semiarid environment.

Original language	English
Title of host publication	RTSI 2017 - IEEE 3rd International Forum on Research and Technologies for Society and Industry, Conference Proceedings
Publisher	IEEE
Number of pages	4
ISBN (Electronic)	9781538639061
ISBN (Print)	978-1-5386-3907-8
DOIs	https://doi.org/10.1109/RTSI.2017.8065940
Publication status	Published - 11 Oct 2017
Event	3rd IEEE International Forum on Research and Technologies for Society and Industry, RTSI 2017 - Modena, Italy Duration: 11 Sept 2017 → 13 Sept 2017

Conference

Conference	3rd IEEE International Forum on Research and Technologies for Society and Industry, RTSI 2017
Country/Territory	Italy
City	Modena
Period	11/09/17 → 13/09/17

ASJC Scopus subject areas

Computer Networks and Communications
Computer Science Applications
Energy Engineering and Power Technology
Industrial and Manufacturing Engineering
Health(social science)
Management of Technology and Innovation
Artificial Intelligence

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/RTSI.2017.8065940

Cite this

Amitrano, D., Cecinati, F., Di Martino, G., Iodice, A., Mathieu, P. P., Riccio, D., & Ruello, G. (2017). Using GEOBIA for feature extraction from multitemporal SAR images: Preliminary results. In RTSI 2017 - IEEE 3rd International Forum on Research and Technologies for Society and Industry, Conference Proceedings Article 8065940 IEEE. https://doi.org/10.1109/RTSI.2017.8065940

Using GEOBIA for feature extraction from multitemporal SAR images: Preliminary results. / Amitrano, Donato; Cecinati, Francesca; Di Martino, Gerardo et al.
RTSI 2017 - IEEE 3rd International Forum on Research and Technologies for Society and Industry, Conference Proceedings. IEEE, 2017. 8065940.

Research output: Chapter or section in a book/report/conference proceeding › Chapter in a published conference proceeding

Amitrano, D, Cecinati, F, Di Martino, G, Iodice, A, Mathieu, PP, Riccio, D & Ruello, G 2017, Using GEOBIA for feature extraction from multitemporal SAR images: Preliminary results. in RTSI 2017 - IEEE 3rd International Forum on Research and Technologies for Society and Industry, Conference Proceedings., 8065940, IEEE, 3rd IEEE International Forum on Research and Technologies for Society and Industry, RTSI 2017, Modena, Italy, 11/09/17. https://doi.org/10.1109/RTSI.2017.8065940

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AU - Iodice, Antonio

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PB - IEEE

Y2 - 11 September 2017 through 13 September 2017

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Using GEOBIA for feature extraction from multitemporal SAR images: Preliminary results

Abstract

Conference

ASJC Scopus subject areas

UN SDGs

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