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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 languageEnglish
Title of host publicationRTSI 2017 - IEEE 3rd International Forum on Research and Technologies for Society and Industry, Conference Proceedings
PublisherIEEE
Number of pages4
ISBN (Electronic)9781538639061
ISBN (Print)978-1-5386-3907-8
DOIs
Publication statusPublished - 11 Oct 2017
Event3rd IEEE International Forum on Research and Technologies for Society and Industry, RTSI 2017 - Modena, Italy
Duration: 11 Sep 201713 Sep 2017

Conference

Conference3rd IEEE International Forum on Research and Technologies for Society and Industry, RTSI 2017
Country/TerritoryItaly
CityModena
Period11/09/1713/09/17

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

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