Polarimetric SAR Techniques and Applications / Carlos López-Martínez, Juan Manuel Lopez-Sanchez, editor.

Format:

Book

Contributor:

Lopez-Sanchez, Juan Manuel, editor.

López-Martínez, Carlos, editor.

Language:

English

Subjects (All):

Synthetic aperture radar.

Physical Description:

1 online resource (174 pages) : illustrations

Place of Publication:

Basel, Switzerland : MDPI - Multidisciplinary Digital Publishing Institute, 2017.

Summary:

Annotation An increasing number of spaceborne Synthetic Aperture Radar (SAR) systems have been equipped with polarimetric capabilities: ALOS and ALOS-2, Radarsat-2, TerraSAR-X, Envisat-ASAR, Sentinel-1a/b, etc. Future mission will still present this type of diversity: RCM, SAOCOM, Cosmo-Skymed 2nd generation or PAZ. Polarimetry allows sensitivity to the structural and geometric properties of the scene, making it possible a more accurate identification and classification than non-polarimetric systems. Then, polarimetry makes possible new applications, especially in quantitative extraction of bio and geophysical variables. Also, the combination of polarimetry and interferometry allows also to explore the vertical structure of semi-transparent media, like crops and forests. SAR polarimetry is an active field of research in Earth observation. Besides the development of applications, researchers have also focused in theory or physical modelling to make SAR polarimetry an operational technique. This book presents the state of the art in SAR polarimetry, from theory and physical modelling to final applications, but also the current and futures challenges. This book puts also the emphasis on studies for the exploitation of data provided by the new polarimetric space borne SAR sensors, which include additional frequency bands, interferometric capability, enlarged spatial coverage, high spatial resolution and/or shorter revisit times.

Contents:

About the Special Issue Editors .v

Carlos Lopez-Martinez and Juan M. Lopez-Sanchez Special Issue on Polarimetric SAR Techniques and Applications Reprinted from: Appl. Sci. 2017, 7(8), 768; doi: 10.3390/app7080768 1

Xianyuan Wang, Zongjie Cao, Yao Ding and Jilan Feng Composite Kernel Method for PolSAR Image Classification Based on Polarimetric-Spatial Information Reprinted from: Appl. Sci. 2017, 7(6), 612; doi: 10.3390/app7060612 4

Homa Zakeri, Fumio Yamazaki and Wen Liu Texture Analysis and Land Cover Classification of Tehran Using Polarimetric Synthetic Aperture Radar Imagery Reprinted from: Appl. Sci. 2017, 7(5), 452; doi: 10.3390/app7050452 18

Fei Gao, Teng Huang, Jun Wang, Jinping Sun, Amir Hussain and Erfu Yang Dual-Branch Deep Convolution Neural Network for Polarimetric SAR Image Classification Reprinted from: Appl. Sci. 2017, 7(5), 447; doi: 10.3390/app7050447 36

Yuta Izumi, Sevket Demirci, Mohd Zafri bin Baharuddin, Tomoro Watanabe and Josaphat Tetuko Sri Sumantyo Analysis of Dual- and Full-Circular Polarimetric SAR Modes for Rice Phenology Monitoring: An Experimental Investigation through Ground-Based Measurements Reprinted from: Appl. Sci. 2017, 7(4), 368; doi: 10.3390/app7040368 54

Onur Yuzugullu, Esra Erten and Irena Hajnsek A Multi-Year Study on Rice Morphological Parameter Estimation with X-Band Polsar Data Reprinted from: Appl. Sci. 2017, 7(6), 602; doi: 10.3390/app7060602 71

Tobias Ullmann, Sarah N. Banks, Andreas Schmitt and Thomas Jagdhuber Scattering Characteristics of X-, C- and L-Band PolSAR Data Examined for the Tundra Environment of the Tuktoyaktuk Peninsula, Canada Reprinted from: Appl. Sci. 2017, 7(6), 595; doi:10.3390/app7060595 .80

Hamdan Omar, Muhamad Afizzul Misman and Abd Rahman Kassim Synergetic of PALSAR-2 and Sentinel-1A SAR Polarimetry for Retrieving Aboveground Biomass in Dipterocarp Forest of Malaysia Reprinted from: Appl. Sci. 2017, 7(7), 675; doi: 10.3390/app7070675 109

Yuanzhi Zhang, Yu Li, X. San Liang and Jinyeu Tsou Comparison of Oil Spill Classifications Using Fully and Compact Polarimetric SAR Images Reprinted from: Appl. Sci. 2017, 7(2), 193; doi: 10.3390/app7020193 129

Dongfang Lin, Jianjun Zhu, Haiqiang Fu, Qinghua Xie and Bing Zhang A TSVD-Based Method for Forest Height Inversion from Single-Baseline PolInSAR Data Reprinted from: Appl. Sci. 2017, 7(5), 435; doi: 10.3390/app7050435 151.

Notes:

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