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

被引:12
作者
Amitrano, Donato [1 ]
Cecinati, Francesca [2 ,3 ]
Di Martino, Gerardo [1 ]
Iodice, Antonio [1 ]
Mathieu, Pierre-Philippe [2 ]
Riccio, Daniele [1 ]
Ruello, Giuseppe [1 ]
机构
[1] Univ Naples Federico II, Dept Elect Engn & Informat Technol, I-80138 Naples, Italy
[2] European Space Agcy, Ctr Earth Observat ESRIN, I-00044 Frascati, Italy
[3] Univ Bristol, Bristol BS8 1TH, Avon, England
来源
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING | 2016年 / 54卷 / 11期
关键词
High-level processing; human-machine interaction; image enhancement; Level-1 beta products; multitemporal synthetic aperture radar (SAR); self-organizing maps (SOMs); Sentinel-1; SELF-ORGANIZING MAPS; HIGH-RESOLUTION SAR; REMOTE-SENSING IMAGES; NEURAL-NETWORKS; L-BAND; FUSION; CLASSIFICATION; SENTINEL-1; TRACKING; MODELS;
D O I
10.1109/TGRS.2016.2586189
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
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 beta 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.
引用
收藏
页码:6545 / 6562
页数:18
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