Multifrequency Spaceborne Synthetic Aperture Radar Data for Backscatter-Based Characterization of Land Use and Land Cover

نویسندگان

چکیده

Polarimetric synthetic aperture radar remote sensing extracts the information about target using decomposition models to separate polarimetric into single-bounce (contributed by smooth surfaces), double-bounce urban structure), and volume (mainly due vegetation cover) scattering components. The penetration capacity of electromagnetic wave surface increases with decrease in its frequency. This study explores compares for scattering-based characterization land use cover multifrequency spaceborne sensor datasets that were acquired over San Francisco, CA, USA. present work parameters coherent (Pauli), roll-invariant (Barnes), eigenvalue–eigenvector (Cloude), compact-polarimetric (Raney) modeling approaches structures, waterbody, cover. use/cover classification was performed based on response scatterers a support vector machine classifier. outputs approach multisensor, multifrequency, multi-polarization data have shown reasonable accuracy classifying fail characterize oriented structures cause misclassification as vegetation. higher-order could improve interpretation different targets classification.

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ژورنال

عنوان ژورنال: Frontiers in Earth Science

سال: 2022

ISSN: ['2296-6463']

DOI: https://doi.org/10.3389/feart.2022.825255