Multitemporal Level-1β Products: Definitions, Interpretation, and Applications

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

Research output: Contribution to journalArticlepeer-review

14 Citations (SciVal)
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In this paper, we present a new framework for the fusion, representation, and analysis of multitemporal synthetic aperture radar (SAR) data. It leads to the definition of a new class of products representing an intermediate level between the classic Level-1 and Level-2 products. The proposed Level-1 β products are particularly oriented toward nonexpert users. In fact, their principal characteristics are the interpretability and the suitability to be processed with standard algorithms. The main innovation of this paper is the design of a suitable RGB representation of data aiming to enhance the information content of the time-series. The physical rationale of the products is presented through examples, in which we show their robustness with respect to sensor, acquisition mode, and geographic area. A discussion about the suitability of the proposed products with Sentinel-1 imagery is also provided, showing the full compatibility with data acquired by the new European Space Agency sensor. Finally, we propose two applications based on the use of Kohonen's self-organizing maps dealing with classification problems.

Original languageEnglish
Article number7523302
Pages (from-to)6545-6562
Number of pages18
JournalIEEE Transactions on Geoscience and Remote Sensing
Issue number11
Early online date27 Jul 2016
Publication statusPublished - 1 Nov 2016


  • High-level processing
  • human-machine interaction
  • image enhancement
  • Level-1β products
  • multitemporal synthetic aperture radar (SAR)
  • self-organizing maps (SOMs)
  • Sentinel-1

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • General Earth and Planetary Sciences


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