Tag: L-band

L-Band SAR Co-Polarized Phase Difference Modeling for Corn Fields

Posted on by Carlos López-Martínez in Publication

Barber, M.E.; Rava, D.S.; López-Martínez, C. “L-Band SAR Co-Polarized Phase Difference Modeling for Corn Fields”. Remote Sens. 2021, 13, 4593, Nov. 2021

Summary

➲ Open access full paper

This paper aims at modeling the microwave backscatter of corn fields by coupling an incoherent, interaction-based scattering model with a semi-empirical bulk vegetation dielectric model. The scattering model is fitted to co-polarized phase difference measurements over several corn fields imaged with fully polarimetric synthetic aperture radar (SAR) images with incidence angles ranging from 20° to 60°. The dataset comprised two field campaigns, one over Canada with the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR, 1.258 GHz) and the other one over Argentina with Advanced Land Observing Satellite 2 (ALOS-2) Phased Array type L-band Synthetic Aperture Radar (PALSAR-2) (ALOS-2/PALSAR-2, 1.236 GHz), totaling 60 data measurements over 28 grown corn fields at peak biomass with stalk gravimetric moisture larger than 0.8 g/g. Co-polarized phase differences were computed using a maximum likelihood estimation technique from each field’s measured speckled sample histograms. After minimizing the difference between the model and data measurements for varying incidence angles by a nonlinear least-squares fitting, well agreement was found with a root mean squared error of 24.3° for co-polarized phase difference measurements in the range of −170.3° to −19.13°. Model parameterization by stalk gravimetric moisture instead of its complex dielectric constant is also addressed. Further validation was undertaken for the UAVSAR dataset on earlier corn stages, where overall sensitivity to stalk height, stalk gravimetric moisture, and stalk area density agreed with ground data, with the sensitivity to stalk diameter being the weakest. This study provides a new perspective on the use of co-polarized phase differences in retrieving corn stalk features through inverse modeling techniques from space.

A Multi-Frequency SDR-Based GBSAR: System Overview and First Results

Posted on by Carlos López-Martínez in Publication

Amézaga, Adrià; López-Martínez, Carlos; Jové, Roger. 2021. “A Multi-Frequency SDR-Based GBSAR: System Overview and First Results” MDPI Remote Sens. 13, no. 9: 1613

➲ Open access full paper

Summary

This work describes a system-level overview of a multi-frequency GBSAR built around a high performance software defined radio (SDR). The main goal of the instrument is to be employed as a demonstrator and experimental platform for multi-frequency GBSAR campaigns. The system is capable of operating in P, L, C and X-bands, and signal generation and digital signal processing are customizable and reconfigurable through software. An overview of the software and hardware and implementations of the system are presented. The operation of the system is demonstrated with two measuring campaigns showing focused amplitude images at different frequencies. It is shown how the usage of SDR for GBSAR systems is a viable design option.

GBSAR system and |S_{vv}| images at P-, L-, C- & X-bands.

A Model-free Four Component Scattering Power Decomposition for Polarimetric SAR Data

Posted on by Carlos López-Martínez in Publication

S. Dey, A. Bhattacharya, A. C. Frery, C. López-Martínez and Y. S. Rao, “A Model-free Four Component Scattering Power Decomposition for Polarimetric SAR Data,” in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Early Access, 2021

➲ Full paper

Summary

Target decomposition methods of polarimetric Synthetic Aperture Radar (PolSAR) data explain scattering information from a target. In this regard, several conventional model-based methods utilize scattering power components to analyze polarimetric SAR data. However, the typical hierarchical process to enumerate power components uses various branching conditions, leading to several limitations. These techniques assume \textit{ad hoc} scattering models within a radar resolution cell. Therefore, the use of several models makes the computation of scattering powers ambiguous. Some common issues of model-based decompositions are related to the compensation of the orientation angle about the radar line of sight and the negative power components’ occurrence. We propose a model-free four-component scattering power decomposition that alleviates these issues. In the proposed approach, we use the non-conventional 3D Barakat degree of polarization to obtain the scattered electromagnetic wave’s polarization state. The degree of polarization is used to obtain the even-bounce, odd-bounce, and diffused scattering power components. Along with this, a measure of target scattering asymmetry is also proposed, which is then suitably utilized to obtain the helicity power. All the power components are roll-invariant, non-negative and unambiguous. In addition to this, we propose an unsupervised clustering technique that preserves the dominance of the scattering power components for different targets. This clustering technique assists in understanding the importance of diverse scattering mechanisms based on target characteristics. The technique adequately captures the clusters’ variations from one target to another according to their physical and geometrical properties.

Second Multi-Frequency GBSAR Test Campaing, Castell de Subirats, Spain

Posted on by Carlos López-Martínez in Campaign

In June 22nd, 2020, we continued the field test of our new multi-frequency GBSAR system, developed in a joint effort of Balamis and the Remote Sensing Laboratory of the Universitat Politècnica de Catalunya, as the PhD of Adrià Amézaga under the aegis of the Industrial Doctorate Programs of the Generalitat de Catalunya and the Spanish Ministry of Science, Innovation and Universities.

This time, the system was fully operational and we tested its performances for forest monitoring at X-, C-, L-band frequencies and finally P-band. The test area is located right next to the Castell de Subirats (Subirats Castle), in the outskirts of the Barcelona city.

The video below shows the four 3-hour time-series of |S_{vv}| images at X-, C-, L- and P-band frequencies measured this day.  One can observe how signal stability increases as the frequency gets lower. This demonstrates that vegetation is transparent at lower frequencies, mainly L- and P-band, so we are observing the soil and the rocky structures under the vegetation.

Multi-Frequency GBSAR Test Campaing, Castell de Subirats, Spain

Posted on by Carlos López-Martínez in Campaign

At the end of May 2020, we resumed our activities to test the new multi-frequency GBSAR system, developed in a joint effort of Balamis and the Remote Sensing Laboratory of the Universitat Politècnica de Catalunya, as the PhD of Adrià Amézaga under the aegis of the Industrial Doctorate Programs of the Generalitat de Catalunya and the Spanish Ministry of Science, Innovation and Universities.

This time, we tested the system performances for forest monitoring at X-, C- and L-band frequencies. The test area is located right next to the Castell de Subirats (Subirats Castle), in the outskirts of the Barcelona city.

The video below shows the three time-series of |S_{vv}| images at X-, C- and L-band frequencies measured this day. It is interesting to observe the effects of data stability at lower frequencies, specially L-band, and how some rocky structures under the vegetation are only visible at this frequency.