Flood Index Estimation Using L-Band Sar Data for Assam Flood Prone Regions

Author(s):  
Samvedya Surampudi ◽  
Vijay Kumar ◽  
Kiran Yarrakula
Keyword(s):  
L Band ◽  
Sar Data ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 360
Author(s):  
Wensheng Wang ◽  
Martin Gade ◽  
Kerstin Stelzer ◽  
Jörn Kohlus ◽  
Xinyu Zhao ◽  
...  

We developed an extension of a previously proposed classification scheme that is based upon Freeman–Durden and Cloude–Pottier decompositions of polarimetric Synthetic Aperture Radar (SAR) data, along with a Double-Bounce Eigenvalue Relative Difference (DERD) parameter, and a Random Forest (RF) classifier. The extension was done, firstly, by using dual-copolarization SAR data acquired at shorter wavelengths (C- and X-band, in addition to the previously used L-band) and, secondly, by adding indicators derived from the (polarimetric) Kennaugh elements. The performance of the newly developed classification scheme, herein abbreviated as FCDK-RF, was tested using SAR data of exposed intertidal flats. We demonstrate that the FCDK-RF scheme is capable of distinguishing between different sediment types, namely mud and sand, at high spatial accuracies. Moreover, the classification scheme shows good potential in the detection of bivalve beds on the exposed flats. Our results show that the developed FCDK-RF scheme can be applied for the mapping of sediments and habitats in the Wadden Sea on the German North Sea coast using multi-frequency and multi-polarization SAR from ALOS-2 (L-band), Radarsat-2 (C-band) and TerraSAR-X (X-band).


2003 ◽  
Vol 41 (12) ◽  
pp. 2735-2744 ◽  
Author(s):  
P.A. Wright ◽  
S. Quegan ◽  
N.S. Wheadon ◽  
C.D. Hall
Keyword(s):  
L Band ◽  

2009 ◽  
Vol 64 (5) ◽  
pp. 458-463 ◽  
Author(s):  
Wagner F. Silva ◽  
Bernardo F.T. Rudorff ◽  
Antonio R. Formaggio ◽  
Waldir R. Paradella ◽  
José C. Mura

Author(s):  
Nicolas Longépé ◽  
Masanobu Shimada ◽  
Sophie Allain ◽  
Eric Pottier
Keyword(s):  
L Band ◽  

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