Estimation of Canopy Height from a Multi-SINC Model in Mediterranean Forest with Single-baseline TanDEM-X InSAR Data

TanDEM-X interferometric synthetic aperture radar (InSAR) data have demonstrated promising advantages and potential in recent years for the inversion of forest height. InSAR coherence becomes the primary input feature when a precise digital terrain model (DTM) is unavailable, but the relationship between InSAR coherence and forest height remains uncertain because of the complexity of forest scenes. In this paper, a method for retrieving canopy height in Mediterranean forests, characterised by short and sparse trees, using a single-pass bistatic TanDEM-X InSAR dataset is proposed. To improve the accuracy of forest height inversion from the uncertain correlation between InSAR coherence and canopy height, we begin by using the established SINC model with two semi-empirical parameters and then expand the single curve into a collection of three curves, forming the Multi-SINC model. To determine the optimal relationship (curve) between TanDEM-X InSAR coherence and canopy height, the problem is shifted from parameter inversion to classification. To solve the problem, we used optical remote sensing data, a small amount of LiDAR data, and TanDEM-X InSAR data in combination with machine learning for classification. As a proof-of-concept, we conducted forest height retrieval at two study sites in Spain with complex terrain and diverse forest types. The results were verified by comparing them with LiDAR product forest height, which demonstrated improved performance (RMSE = 2.49 m and 1.7 m) compared to the SeEm-SINC model (RMSE = 3.28 m and 2.36 m).This work was funded by the National Key Research and Development Program of China (No. 2022YFB3902605), the National Natural Science Foundation of China (No. 42227801), the Natural Science Foundation for Excellent Young Scholars of Hunan Province (No. 2023JJ20061), the Spanish Ministry of Science and Innovation (State Agency of Research, AEI), and the European Funds for Regional Development under Project PID2020-117303GB-C22/AEI/10.13039/501100011033

Utilization of bistatic TanDEM-X data to derive land cover information

Forests have significance as carbon sink in climate change. Therefore, it is of high importance to track land use changes as well as to estimate the state as carbon sink. This is useful for sustainable forest management, land use planning, carbon modelling, and support to implement international initiatives like REDD+ (Reducing Emissions from Deforestation and Degradation). A combination of field measurements and remote sensing seems most suitable to monitor forests. Radar sensors are considered as high potential due to the weather and daytime independence. TanDEM-X is a interferometric SAR (synthetic aperture radar) mission in space and can be used for land use monitoring as well as estimation of biophysical parameters. TanDEM-X is a X-band system resulting in low penetration depth into the forest canopy. Interferometric information can be useful, whereas the low penetration can be considered as an advantage. The interferometric height is assumable as canopy height, which is correlated with forest biomass. Furthermore, the interferometric coherence is mainly governed by volume decorrelation, whereas temporal decorrelation is minimized. This information can be valuable for quantitative estimations and land use monitoring. The interferometric coherence improved results in comparison to land use classifications without coherence of about 10% (75% vs. 85%). Especially the differentiation between forest classes profited from coherence. The coherence correlated with aboveground biomass in a R² of about 0.5 and resulted in a root mean square error (RSME) of 14%. The interferometric height achieved an even higher correlation with the biomass (R²=0.68) resulting in cross-validated RMSE of 7.5%. These results indicated that TanDEM-X can be considered as valuable and consistent data source for forest monitoring. Especially interferometric information seemed suitable for biomass estimation

The GRSS standard for GNSS-reflectometry

In February 2019 a Project Authorization Request was approved by the Institute of Electrical and Electronics Engineers (IEEE) Standards Association with the title “Standard for Global Navigation Satellite System Reflectometry (GNSS-R) Data and Metadata Content”. A Working Group has been assembled to draft this standard with the purpose of unifying and documenting GNSS-R measurements, calibration procedures, and product level definitions. The Working Group (http://www.grss-ieee.org/community/technical-committees/standards-or-earth-observations/) includes members, collaborators, and contributors from academia, international space agencies, and private industry. In a recent face-to-face meeting held during the ARSI+KEO 2019 Conference, the need was recognized to develop a standard with a wide range of operations, providing procedure guidelines independently of constraints imposed by current limitations on geophysical parameters retrieval algorithms. As such, this effort aims to establish the fundamentals of a potential virtual network of satellites providing inter-comparable data to the scientific community.Peer ReviewedPostprint (author's final draft

Simultaneous Estimation of Sub-canopy Topography and Forest Height with Single-baseline Single-polarization TanDEM-X Interferometric Data Combined with ICESat-2 Data

To address the challenge of retrieving sub-canopy topography using single-baseline single-polarization TanDEM-X InSAR data, we propose a novel InSAR processing framework. Our methodology begins by employing the SINC model to estimate the penetration depth (PD). Subsequently, we establish a linear relationship between PD and phase center height (PCH) to generate a wall-to-wall PCH product. To achieve this, space-borne LiDAR data are employed to capture the elevation bias between actual ground elevation and InSAR-derived elevation. Finally, the sub-canopy topography is derived by subtracting the PCH from the conventional InSAR-based DEM. Moreover, this approach enables the simultaneous estimation of forest height from single-baseline TanDEM-X data by combining the estimated PD and PCH components. The approach has been validated against Airborne Lidar Scanning data over four diverse sites encompassing different forest types, terrain conditions, and climates. The derived sub-canopy topography in the boreal and hemi-boreal forest sites (Krycklan and Remningstorp) demonstrated notable improvement in accuracy. Additionally, the winter acquisitions outperformed the summer ones in terms of inversion accuracy. The achieved RMSEs for the winter scenarios were 2.45 m and 3.83 m, respectively, representing a 50% improvement over the InSAR-based DEMs. And the forest heights are also close to the ALS measurements, with RMSEs of 2.70 m and 3.33 m, respectively. For the Yanguas site in Spain, characterized by rugged terrain, sub-canopy topography in forest areas was estimated with an accuracy of 4.27m, a 35% improvement over the original DEM. For the denser tropical forest site, only an average elevation bias could be corrected.This work is funded by the National Key R&D Program of China (No. 2022YFB3902605), the National Natural Science Foundation of China (Nos. 42227801, 42030112, 42204024, 42104016, 42330717), the Spanish Ministry of Science and Innovation (State Agency of Research, AEI) and the European Funds for Regional Development under Project PID2020-117303GB-C22/AEI/10.13039/501100011033, the Natural Science Foundation for Excellent Young Scholars of Hunan Province (No. 2023JJ20061), and in part by the China Scholarship Council Foundation to the Joint Ph.D. Studies at University of Alicante (No. 202106370125)

The Global Water Body Layer from TanDEM-X Interferometric SAR Data

The interferometric synthetic aperture radar (InSAR) data set, acquired by the TanDEM-X (TerraSAR-X add-on for Digital Elevation Measurement) mission (TDM), represents a unique data source to derive geo-information products at a global scale. The complete Earth's landmasses have been surveyed at least twice during the mission bistatic operation, which started at the end of 2010. Examples of the delivered global products are the TanDEM-X digital elevation model (DEM) (at a final independent posting of 12 m × 12 m) or the TanDEM-X global Forest/Non-Forest (FNF) map. The need for a reliable water product from TanDEM-X data was dictated by the limited accuracy and difficulty of use of the TDX Water Indication Mask (WAM), delivered as by-product of the global DEM, which jeopardizes its use for scientific applications, as well. Similarly as it has been done for the generation of the FNF map, in this work, we utilize the global data set of TanDEM-X quicklook images at 50 m × 50 m resolution, acquired between 2011 and 2016, to derive a new global water body layer (WBL), covering a range from -60° to +90° latitudes. The bistatic interferometric coherence is used as the primary input feature for performing water detection. We classify water surfaces in single TanDEM-X images, by considering the system's geometric configuration and exploiting a watershed-based segmentation algorithm. Subsequently, single overlapping acquisitions are mosaicked together in a two-step logically weighting process to derive the global TDM WBL product, which comprises a binary averaged water/non-water layer as well as a permanent/temporary water indication layer. The accuracy of the new TDM WBL has been assessed over Europe, through a comparison with the Copernicus water and wetness layer, provided by the European Space Agency (ESA), at a 20 m × 20 m resolution. The F-score ranges from 83%, when considering all geocells (of 1° latitudes × 1° longitudes) over Europe, up to 93%, when considering only the geocells with a water content higher than 1%. At global scale, the quality of the product has been evaluated, by intercomparison, with other existing global water maps, resulting in an overall agreement that often exceeds 85% (F-score) when the content in the geocell is higher than 1%. The global TDM WBL presented in this study will be made available to the scientific community for free download and usage

Measurements of Sea Surface Currents in the Baltic Sea Region Using Spaceborne Along-Track InSAR

The main challenging problems in ocean current retrieval from along-track interferometric (ATI)-synthetic aperture radar (SAR) are phase calibration and wave bias removal. In this paper, a method based on differential InSAR (DInSAR) technique for correcting the phase offset and its variation is proposed. The wave bias removal is assessed using two different Doppler models and two different wind sources. In addition to the wind provided by an atmospheric model, the wind speed used for wave correction in this work is extracted from the calibrated SAR backscatter. This demonstrates that current retrieval from ATI-SAR can be completed independently of atmospheric models. The retrieved currents, from four TanDEM-X (TDX) acquisitions over the 6resund channel in the Baltic Sea, are compared to a regional ocean circulation model. It is shown that by applying the proposed phase correction and wave bias removal, a good agreement in spatial variation and current direction is achieved. The residual bias, between the ocean model and the current retrievals, varies between 0.013 and 0.3 m/s depending on the Doppler model and wind source used for wave correction. This paper shows that using SAR as a source of wind speed reduces the bias and root-mean-squared-error (RMSE) of the retrieved currents by 20% and 15%, respectively. Finally, the sensitivity of the sea current retrieval to Doppler model and wind errors are discussed

Study of the speckle noise effects over the eigen decomposition of polarimetric SAR data: a review

This paper is focused on considering the effects of speckle noise on the eigen decomposition of the co- herency matrix. Based on a perturbation analysis of the matrix, it is possible to obtain an analytical expression for the mean value of the eigenvalues and the eigenvectors, as well as for the Entropy, the Anisotroopy and the dif- ferent a angles. The analytical expressions are compared against simulated polarimetric SAR data, demonstrating the correctness of the different expressions.Peer ReviewedPostprint (published version

Formation Flying SAR: Analysis of Imaging Performance by Array Theory

This article analyzes the process of image synthesis for a formation flying synthetic aperture radar (FF-SAR), which is a multistatic synthetic aperture radar (SAR) based on a cluster of receiving-only satellites flying in a close formation, in the framework of the array theory. Indeed, the imaging properties of different close receivers, when analyzed as isolated items, are very similar and form the so-called common array. Moreover, the relative positions among the receivers implicitly define a physical array, referred to as spatial diversity array. FF-SAR imaging can be verified as a result of the spatial diversity array weighting the common array. Hence, different approaches to beamforming can be applied to the spatial diversity array to provide the FF-SAR with distinctive capabilities, such as coherent resolution enhancement and high-resolution wide-swath imaging. Simulation examples are discussed which confirm that array theory is a powerful tool to quickly and easily characterize FF-SAR imaging performance

Radar Backscatter Modeling Based on Global TanDEM-X Mission Data

Radarrückstreuung bezeichnet den Teil eines ausgesendeten elektromagnetischen Signals, der von einem Ziel am Boden wieder zurück zur Antenne gerichtet ist. Die Eigenschaften des zurückgestreuten Signals ändern sich in Abhängigkeit von Frequenz und Polarisation des Radarsignals, der Aufnahmegeometrie, sowie vom Zustand des Erdbodens und der Art der Bodenbedeckung. Informationen über das Radarrückstreuverhalten sind von höchster Wichtigkeit für die Auslegung von SAR-Missionen und werden verbreitet zur Entwicklung wissenschaftlicher Modelle genutzt, beispielsweise bei der Erforschung der Biosphäre und Kryosphäre. Hauptziel dieser Arbeit ist die Auswertung und Nutzung des globalen TanDEM-X-Datensatzes zur Modellierung der Radarrückstreuung im X-Band unter Berücksichtigung unterschiedlicher Aufnahmeparameter und Landnutzungsarten, sowie die Bereitstellung einer Reihe von globalen Rückstreumodellen, die auf aktuellen Daten basieren, für die wissenschaftliche Gemeinschaft. Es wurde ein neuer Ansatz zur statistischen Modellierung der Rückstreuinformation entwickelt, der die Qualität der zugrunde liegenden Messungen berücksichtigt. Daraus ergeben sich gewichtete polynomiale Modelle für die verschiedenen Landnutzungsarten, wie sie in der GlobCover-Karte der ESA definiert sind. Darüber hinaus wird ein eigener Validierungsansatz vorgestellt, mit zusätzlicher Betrachtung der saisonalen Variation der Rückstreuung und einer separaten Analyse des Rückstreuverhaltens des Tropischen Regenwaldes. Der nächste Schwerpunkt ist die Betrachtung des Grönländischen Eisschildes, das gekennzeichnet ist durch das Vorhandensein verschiedener Arten von Schneebedeckung, die von trockenem bis hin zu sehr feuchtem Schnee variiert. Der begrenzte Detailgrad, den die GlobCover Karte in Grönland aufweist (nur eine Klasse für das gesamte Eisschild), erlaubt dort keine verlässliche Modellierung der Rückstreuung. Diese Schwierigkeit lieferte die Motivation für die Entwicklung eines neuen Ansatzes zur Analyse des Informationsgehalts der interferometrischen TanDEM-X-Daten mit dem Ziel, unterschiedliche Schnee-Fazien mit Hilfe des sog. C-Means Fuzzy Clustering Algorithmus zu lokalisieren. Aus dieser Untersuchung konnte die Existenz von vier unterschiedlichen Klassen von Schnee-Fazien abgeleitet werden, deren Eigenschaften anschließend mit Hilfe externer Referenzdaten interpretiert wurden. Die daraus entstandene Karte wurde zur Erstellung eines einfallswinkelabhängigen Rückstreumodells genutzt, separat für jede der vier Klassen, wobei eine modifizierte Version des entwickelten Algorithmus zur Generierung globaler Rückstreumodelle eingesetzt wurde. Darüber hinaus wurde als Nebenprodukt zusätzlich die Eindringtiefe von TanDEM-X in die Eisschicht geschätzt, durch Inversion des von Weber Hoen und Zebker vorgeschlagenen "Ein-chicht Volumendekorrelationsmodells". Die Ergebnisse wurden mit dem Höhenunterschied zwischen dem globalen TanDEM-X-DEM und ICESat-Messungen verglichen. Abschließend wird ein neu entwickelter Algorithmus zur Generierung von Rückstreukarten großer Gebiete vorgestellt. Dieser erlaubt unter Verwendung von Rückstreumodellen das Angleichen der erstellten Karten anhand eines Referenzeinfallswinkels, was dann das Füllen verbleibender Lücken ermöglicht, die aufgrund fehlender Eingangsdaten vorhanden sind