Radar polarimetry and interferometry for remote sensing of boreal forest

Forest biomass is a key parameter of the global biosphere which is linked to many fields of research. Modeling addressing climate, ecology, and economics as well as many other prediction frameworks require an accurate assessment of global forest biomass. Methods for producing forest information are rapidly developing and traditional forest inventory by visual estimation has been gradually replaced by the use of airborne and spaceborne instruments. Nevertheless, the estimation of biomass on a global basis including boreal, temperate, and tropical forests, is still a major challenge. Among other spaceborne sensors, synthetic aperture radar (SAR) is one of the most suitable tools for large scale mapping and it has also been often used for forest mapping. However, commonly used backscattering intensity based methods do not provide a satisfactory accuracy for biomass estimation; hence, the scientific radar community has been developing more accurate means based on advanced SAR imaging and analyzing techniques, such as SAR polarimetry and interferometry. The work within this thesis contributes to this effort specifically in the field of remote sensing with the emphasis on SAR polarimetry and interferometry for boreal forest applications. The study concentrates on three main topics: polarimetric SAR image analysis, retrieval of forest height by means of SAR interferometry, and modeling of radar backscattering from trees. The main contributions of this work include a new effective approach in polarimetric target decomposition, novel polarimetric visualization schemes, an improved interferometric tree height estimation method suitable for boreal forest, interferometric tree height estimation capability demonstration for X-band, a novel method for relating SAR measurements to single tree scattering modeling, and taking the scattering modeling from a pine tree to the single needle level with accurate field models. Furthermore, the forest height estimation scheme proposed in this work potentially enables tree height estimation with existing spaceborne interferometric X-band SAR systems. The proposed method uses an interferometric coherence model and a ground elevation model to produce accurate tree height maps from single polarization interferometric SAR data. The method is demonstrated with airborne SAR measurements and will be tested in the near future with satellite data. Since tree height is related to forest biomass through tree allometry, tree height measurements from space would enable more accurate global forest biomass maps

First Demonstration of Space-Borne Polarization Coherence Tomography for Characterizing Hyrcanian Forest Structural Diversity

Structural diversity is recognized as a complementary aspect of biological diversity and plays a fundamental role in forest management, conservation, and restoration. Hence, the assessment of structural diversity has become a major effort in the primary international processes, dealing with biodiversity and sustainable forest management. Because of prohibitive costs associated with the ground measurements of forest structure, despite their high accuracy, space-borne polarization coherence tomography (PCT) can introduce an alternative approach given its ability to provide a vertical reflectivity profile and spatiotemporal resolutions related to detecting forest structural changes. In this study, for the first time ever, the potential of space-borne PCT was evaluated in a broad-leaved Hyrcanian forest of Iran over 308 circular sample plots with an area of 0.1 ha. Two aspects of horizontal structure diversity, including standard deviation of diameter at breast height (σdbh) and the number of trees (N), were predicted as important characteristics in wood production and biomass estimation. In addition, the performance of prediction algorithms, including multiple linear regression (MLR), k-nearest neighbors (k-NN), random forest (RF), and support vector regression (SVR) were compared. We addressed the issue of temporal decorrelation in space-borne PCT utilizing the single-pass TanDEM-X interferometer. The data were acquired in standard DEM mode with single polarization of HH. Consequently, airborne laser scanning (ALS) was used to estimate initial values of height hv and ground phase φ0. The Fourier–Legendre series was used to approximate the relative reflectivity profile of each pixel. To link the relative reflectivity profile averaged within each plot with corresponding ground measurements of σdbh and N, thirteen geometrical and physical parameters were defined (P1−P13). Leave-one-out cross validation (LOOCV) showed a better performance of k-NN than the other algorithms in predicting σdbh and N. It resulted in a relative root mean square error (rRMSE) of 32.80%, mean absolute error (MAE) of 4.69 cm, and R2* of 0.25 for σdbh, whereas only 22% of the variation in N was explained using the PCT algorithm with an rRMSE of 41.56%. This study revealed promising results utilizing TanDEM-X data even though the accuracy is still limited. Hence, an entire assessment of the used framework in characterizing the reflectivity profile and the possible effect of the scale is necessary for future studies

A Study of Landfast Ice with Sentinel-1 Repeat-Pass Interferometry over the Baltic Sea

Mapping of fast ice displacement and investigating sea ice rheological behavior is a major open topic in coastal ice engineering and sea ice modeling. This study presents first results on Sentinel-1 repeat-pass space borne synthetic aperture radar interferometry (InSAR) in the Gulf of Bothnia over the fast ice areas. An InSAR pair acquired in February 2015 with a temporal baseline of 12 days has been studied here in detail. According to our results, the surface of landfast ice in the study area was stable enough to preserve coherence over the 12-day baseline, while previous InSAR studies over the fast ice used much shorter temporal baselines. The advantage of longer temporal baseline is in separating the fast ice from drift ice and detecting long term trends in deformation maps. The interferogram showed displacement of fast ice on the order of 40 cm in the study area. Parts of the displacements were attributed to forces caused by sea level tilt, currents, and thermal expansion, but the main factor of the displacement seemed to be due to compression of the drift ice driven by southwest winds with high speed. Further interferometric phase and the coherence measurements over the fast ice are needed in the future for understanding sea ice mechanism and establishing sustainability of the presented InSAR approach for monitoring dynamics of the landfast ice with Sentinel-1 data.Peer reviewe

First Demonstration of Space-Borne Polarization Coherence Tomography for Characterizing Hyrcanian Forest Structural Diversity

Structural diversity is recognized as a complementary aspect of biological diversity and plays a fundamental role in forest management, conservation, and restoration. Hence, the assessment of structural diversity has become a major effort in the primary international processes, dealing with biodiversity and sustainable forest management. Because of prohibitive costs associated with the ground measurements of forest structure, despite their high accuracy, space-borne polarization coherence tomography (PCT) can introduce an alternative approach given its ability to provide a vertical reflectivity profile and spatiotemporal resolutions related to detecting forest structural changes. In this study, for the first time ever, the potential of space-borne PCT was evaluated in a broad-leaved Hyrcanian forest of Iran over 308 circular sample plots with an area of 0.1 ha. Two aspects of horizontal structure diversity, including standard deviation of diameter at breast height (σdbh) and the number of trees (N), were predicted as important characteristics in wood production and biomass estimation. In addition, the performance of prediction algorithms, including multiple linear regression (MLR), k-nearest neighbors (k-NN), random forest (RF), and support vector regression (SVR) were compared. We addressed the issue of temporal decorrelation in space-borne PCT utilizing the single-pass TanDEM-X interferometer. The data were acquired in standard DEM mode with single polarization of HH. Consequently, airborne laser scanning (ALS) was used to estimate initial values of height hv and ground phase φ0. The Fourier–Legendre series was used to approximate the relative reflectivity profile of each pixel. To link the relative reflectivity profile averaged within each plot with corresponding ground measurements of σdbh and N, thirteen geometrical and physical parameters were defined (P1−P13). Leave-one-out cross validation (LOOCV) showed a better performance of k-NN than the other algorithms in predicting σdbh and N. It resulted in a relative root mean square error (rRMSE) of 32.80%, mean absolute error (MAE) of 4.69 cm, and R2* of 0.25 for σdbh, whereas only 22% of the variation in N was explained using the PCT algorithm with an rRMSE of 41.56%. This study revealed promising results utilizing TanDEM-X data even though the accuracy is still limited. Hence, an entire assessment of the used framework in characterizing the reflectivity profile and the possible effect of the scale is necessary for future studies

Automated SEA ICE Classification Over the Baltic SEA using Multiparametric Features of Tandem-X Insar Images

In this study, bistatic interferometric Synthetic Aperture Radar (InSAR) data acquired by the TanDEM-X mission were used for automated classification of sea ice over the Baltic Sea, in the Bothnic Bay. A scene acquired in March of 2012 was used in the study. Backscatter-intensity, coherence-magnitude and InSAR-phase, as well as their different combinations, were used as informative features in several classification approaches. In order to achieve the best discrimination between open water and several sea ice types (new ice, thin smooth ice, close ice, very close ice, ridged ice, heavily ridged ice and ship-track), Random Forests (RF) and Maximum likelihood (ML) classifiers were employed. The best overall accuracies were achieved using combination of backscatter-intensity & InSAR-phase and backscatter-intensity & coherence-magnitude, and were 76.86% and 75.81% with RF and ML classifiers, respectively. Overall, the combination of backscatter-intensity & InSAR-phase with RF classifier was suggested due to the highest overall accuracy (OA) and smaller computing time in comparison to ML. In contrast to several earlier studies, we were able to discriminate water and the thin smooth ice.Peer reviewe

TanDEM-X multiparametric data features in sea ice classification over the Baltic sea

In this study, we assess the potential of X-band Interferometric Synthetic Aperture Radar imagery for automated classification of sea ice over the Baltic Sea. A bistatic SAR scene acquired by the TanDEM-X mission over the Bothnian Bay in March of 2012 was used in the analysis. Backscatter intensity, interferometric coherence magnitude, and interferometric phase have been used as informative features in several classification experiments. Various combinations of classification features were evaluated using Maximum likelihood (ML), Random Forests (RF) and Support Vector Machine (SVM) classifiers to achieve the best possible discrimination between open water and several sea ice types (undeformed ice, ridged ice, moderately deformed ice, brash ice, thick level ice, and new ice). Adding interferometric phase and coherence-magnitude to backscatter-intensity resulted in improved overall classification performance compared to using only backscatter-intensity. The RF algorithm appeared to be slightly superior to SVM and ML due to higher overall accuracies, however, at the expense of somewhat longer processing time. The best overall accuracy (OA) for three methodologies were achieved using combination of all tested features were 71.56, 72.93, and 72.91% for ML, RF and SVM classifiers, respectively. Compared to OAs of 62.28, 66.51, and 63.05% using only backscatter intensity, this indicates strong benefit of SAR interferometry in discriminating different types of sea ice. In contrast to several earlier studies, we were particularly able to successfully discriminate open water and new ice classes.Peer reviewe

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Analysis and Design of Integrated Magnetorquer Coils for Attitude Control of Nanosatellites

The nanosatellites typically use either magnetic rods or coil to generate magnetic moment which consequently interacts with the earth magnetic field to generate torque. In this research, we present a novel design which integrates printed embedded coils, compact coils and magnetic rods in a single package which is also complaint with 1U CubeSat. These options provide maximum flexibility, redundancy and scalability in the design. The printed coils consume no extra space because the copper traces are printed in the internal layers of the printed circuit board (PCB). Moreover, they can be made reconfigurable by printing them into certain layers of the PCB, allowing the user to select any combination of series and parallel coils for optimized design. The compact coil is wound around the available space in a 1U complaint CubeSat panel and it can accommodate much more number of turns compared to printed coil; consequently generating more torque. The magnetic rod is made complaint with the existing available options and can easily be integrated in the panel. This design gives a lot of flexibility because one can choose to optimize power, optimized torque or rotation time by choosing among the available magnetorquer options. The proposed design approach occupies very low space, consume low power and is cost effective. The analysis in terms of generated torque with certain applied voltages, trace widths. The analysis results in terms of selection of optimized parameters including torque to power ratio will be presented

A Feasibility Study for Signal-in-Space Design for LEO-PNT Solutions With Miniaturized Satellites

The global navigation satellite systems (GNSSs) are increasingly suffering from interferences, such as coming from jammers and spoofers, and their performance is still modest in challenging urban and indoor scenarios. Therefore, there are efforts worldwide to develop complementary positioning, navigation, and timing (PNT) solutions. One such complementary method under current research is the so-called LEO-PNT, namely, PNT solutions based on low-Earth orbit (LEO) satellites, and in particular on small-sized or miniaturized satellites. Such satellites have low-to-moderate costs of building, launching, and maintenance. Several challenges are to be overcome when designing a new LEO-PNT solution, concerning all three satellite segments: 1) the signal-in-space (SIS) or space segment; 2) the ground segment; and 3) the user/receiver segment. This article presents a survey of the SIS design challenges under the inherent constraints of wireless-channel propagation impairments as well as some design recommendations for SIS features. We address different constellation types, achievable coverage limits, and geometric dilution of precision (GDOP) bounds, as well as achievable carrier-to-noise ratios (CNRs) under a realistic wireless channel model, based on a MATLAB Quadriga simulator. We also discuss several optimization criteria regarding LEO-PNT SIS design, by taking into account the tradeoff between a low cost/low number of satellites in orbit on the one hand, and a sufficient coverage and good CNR for PNT purposes on the other hand.publishedVersionPeer reviewe