Abstract
Polarimetric Synthetic Aperture Radar (PolSAR) data is sensitive to physical structure of agricultural crops. In line with this fact radiative transfer theory based backscattering models have been used to explain the complicated interaction between electromagnetic waves and vegetation canopy. However, high degree of computational complexity of such models causes challenging inversion process. In this study, sparse Polynomial Chaos Expansion (PCE) metamodel is used for the inversion and the evaluation of the Global Sensitivity Analysis (GSA) of the model parameters. Finally promising results have been obtained for the estimation of height and diameter of stalks, length and width of leaves and growth stages for X-band PolSAR data.
Translated title of the contribution | Using metamodels for agricultural monitoring |
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Original language | Turkish |
Title of host publication | 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 273-276 |
Number of pages | 4 |
ISBN (Electronic) | 9781509016792 |
DOIs | |
Publication status | Published - 20 Jun 2016 |
Event | 24th Signal Processing and Communication Application Conference, SIU 2016 - Zonguldak, Turkey Duration: 16 May 2016 → 19 May 2016 |
Publication series
Name | 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings |
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Conference
Conference | 24th Signal Processing and Communication Application Conference, SIU 2016 |
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Country/Territory | Turkey |
City | Zonguldak |
Period | 16/05/16 → 19/05/16 |
Bibliographical note
Publisher Copyright:© 2016 IEEE.