The European Space Agency BIOMASS mission: Measuring forest above-ground biomass from space

The primary objective of the European Space Agency's 7th Earth Explorer mission, BIOMASS, is to determine the worldwide distribution of forest above-ground biomass (AGB) in order to reduce the major uncertainties in calculations of carbon stocks and fluxes associated with the terrestrial biosphere, including carbon fluxes associated with Land Use Change, forest degradation and forest regrowth. To meet this objective it will carry, for the first time in space, a fully polarimetric P-band synthetic aperture radar (SAR). Three main products will be provided: global maps of both AGB and forest height, with a spatial resolution of 200 m, and maps of severe forest disturbance at 50 m resolution (where “global” is to be understood as subject to Space Object tracking radar restrictions). After launch in 2022, there will be a 3-month commissioning phase, followed by a 14-month phase during which there will be global coverage by SAR tomography. In the succeeding interferometric phase, global polarimetric interferometry Pol-InSAR coverage will be achieved every 7 months up to the end of the 5-year mission. Both Pol-InSAR and TomoSAR will be used to eliminate scattering from the ground (both direct and double bounce backscatter) in forests. In dense tropical forests AGB can then be estimated from the remaining volume scattering using non-linear inversion of a backscattering model. Airborne campaigns in the tropics also indicate that AGB is highly correlated with the backscatter from around 30 m above the ground, as measured by tomography. In contrast, double bounce scattering appears to carry important information about the AGB of boreal forests, so ground cancellation may not be appropriate and the best approach for such forests remains to be finalized. Several methods to exploit these new data in carbon cycle calculations have already been demonstrated. In addition, major mutual gains will be made by combining BIOMASS data with data from other missions that will measure forest biomass, structure, height and change, including the NASA Global Ecosystem Dynamics Investigation lidar deployed on the International Space Station after its launch in December 2018, and the NASA-ISRO NISAR L- and S-band SAR, due for launch in 2022. More generally, space-based measurements of biomass are a core component of a carbon cycle observation and modelling strategy developed by the Group on Earth Observations. Secondary objectives of the mission include imaging of sub-surface geological structures in arid environments, generation of a true Digital Terrain Model without biases caused by forest cover, and measurement of glacier and icesheet velocities. In addition, the operations needed for ionospheric correction of the data will allow very sensitive estimates of ionospheric Total Electron Content and its changes along the dawn-dusk orbit of the mission

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)

Uncertainties and Perspectives on Forest Height Estimates by Sentinel-1 Interferometry

Forest height is a key parameter in forestry. SAR interferometry (InSAR) techniques have been extensively adopted to retrieve digital elevation models (DEM) to give a representation of the continuous variation of the Earth’s topography, including forests. Unfortunately, InSAR has been proven to fail over vegetation due to low coherence values; therefore, all phase unwrapping algorithms tend to avoid these areas, making InSAR-derived DEM over vegetation unreliable. In this work, a sensitivity analysis was performed with the aim of properly initializing the relevant operational parameters (baseline and multilooking factor) to maximize the theoretical accuracy of the height difference between the forest and reference point. Some scenarios were proposed to test the resulting “optimal values”, as estimated at the previous step. A simple model was additionally proposed and calibrated, aimed at predicting the optimal baseline value (and therefore image pair selection) for height uncertainty minimization. All our analyses were conducted using free available data from the Copernicus Sentinel-1 mission to support the operational transfer into the forest sector. Finally, the potential uncertainty affecting resulting height measures was quantified, showing that a value lower than 5 m can be expected once all user-dependent parameters (i.e., baseline, multilooking factor, temporal baseline) are properly tuned

Monitoring von Hangbewegungen mit InSAR Techniken im Gebiet Ciloto, Indonesien

In this doctoral thesis, the InSAR techniques are applied to detect the ground movement phenomenon and to assess the InSAR result geometrically in the Ciloto area, Indonesia. Mainly, one of those techniques, the SB-SDFP algorithm, overcomes the limitations of conventional InSAR in monitoring rural and agricultural areas and can observe extremely slow landslides. The InSAR strategy is positively known as a promising option to detect and quantify the kinematics of active landslides on a large areal scale. To minimize the bias of the InSAR displacement result, the correction of the tropospheric phase delay was carried out in a first step. This procedure is demonstrated in experiments both in the small study area in Ciloto and in a larger area. The latter is an area located in Northern Baja California, Mexico and is dominated by tectonic activity as well as groundwater-induced subsidence. A detailed investigation of the slope movement's behavior in the Ciloto district was conducted utilizing multi-temporal and multi-band SAR data from ERS1/2 (1996-1999), ALOS PALSAR (2007-2009) and Sentinel-1 (2014-2018) satellites. The region was successfully identified as a permanent active landslide prone area, especially in the vicinity of the Puncak Pass and Puncak Highway. The full 3D velocity field and the displacement time series were estimated using the inversion model. The velocity rate was classified from extremely slow to slow movement. To comprehend the landslide's behavior, a further examination of the relationship between InSAR results and physical characteristics of the area was carried out. For the long period of a slow-moving landslide, the relationship between precipitation and displacement trend shows a weak correlation. It is concluded that the extremely slow to slow deformation is not directly influenced by the rainfall intensity, yet it effectuates the subsurface and the groundwater flow. The run-off process with rainfall exceeding a soil's infiltration capacity was suspected as the main driver of the slow ground movement phenomenon. However, when analyzing rapid and extremely rapid landslide events at Puncak Pass, a significant increase in the correlation coefficient between precipitation and displacement rate could be observed.In dieser Doktorarbeit wird die Anwendung von erweiterten Verarbeitungsstrategien von InSAR Daten zur Erkennung und geometrischen Bewertung der Bodenbewegungen im Ciloto - Indonesien dargestellt. Dieser Ansatz überwindet die Beschränkungen konventioneller SAR-Interferometrie und ermöglicht sowohl ein kontinuierliches Monitoring dieses landwirtschaftich geprägten Gebietes als auch die Erfassung extrem langsamer Hangrutschungen. Um eine Verzerrung der InSAR Deformationsergebnisse zu minimieren, wurde zunächst eine Korrektur der troposphärischen Phase durchgeführt. Diese neuartige Strategie wird sowohl im Forschungsgebiet Ciloto als auch an einem größeren Gebiet demonstriert. Bei letzterem handelt es sich um einen Küstenstreifen im nördlichen Niederkalifornien, Mexiko, welcher durch hohe tektonische Aktivität und grundwasserinduzierte Landsetzungen charakterisiert ist. Die detaillierte Untersuchung des Verhaltens von Hangrutschungen im Ciloto erfolgte durch die Verarbeitung multi-temporaler SAR-Daten unter Nutzung verschiedener Frequenzbänder, darunter ESR1/2 (1996-1999), ALOS PALSAR (2007-2009) und Sentinel-1 (2014-2018) Daten. Die Region konnte erfolgreich als permanent aktives Hangrutschungsgebiet identifiziert werden, wobei der Puncak Pass und der Puncak Highway ein erhöhtes Gefahrenpotential aufweisen. Ein 3D- Geschwindig-keitsfeld der Deformation und die zugehörigen Zeitreihen wurden mit dem Inversionsmodell berechnet. Die Geschwindigkeitsrate wurde als langsam bis extrem langsam klassifiziert. Um das dynamische Verhalten der Hangrutschung zu verstehen wurde, in einer weiteren Untersuchung die Beziehung zwischen dem InSAR-Ergebnis und den physikalischen Begebenheiten im Forschungsgebiet analysiert. Es wird der Schluss gezogen, dass die langsame bis extrem langsame Verformung nicht direkt von der Niederschlagsintensität beeinflusst wird, diese sich aber auf den Untergrund und die Grundwasserströmung auswirkt. Es wird vermutet, dass der Oberflächenablauf, welcher die Infiltrationskapazität des Bodens übersteigt, ausschlaggebend für das Phänomen der langsamen Bodenbewegung ist. Für die schnellen und extrem schnellen Hangrutschungen jedoch konnte eine signifikante Erhöhung des Korrelationskoeffizienten zwischen Niederschlag und Verschiebungsrate bei Untersuchungen der Hangrutschung am Puncak-Pass nachgewiesen werden

Estimation of biophysical parameters in boreal forests from ERS and JERS SAR interferometry

The thesis describes investigations concerning the evaluation of ERS and JERS SAR images and repeat-pass interferometric SAR images for the retrieval of biophysical parameters in boreal forests. The availability of extensive data sets of images over several test sites located in Sweden, Finland and Siberia has allowed analysis of temporal dynamics of ERS and JERS backscatter and coherence, and of ERS interferometric phase. Modelling of backscatter, coherence and InSAR phase has been performed by means of the Water Cloud Model (WCM) and the Interferometric Water Cloud Model (IWCM); sensitivity analysis and implications for the retrieval of forest biophysical parameters have been thoroughly discussed. Model inversion has been carried out for stem volume retrieval using ERS coherence, ERS backscatter and JERS backscatter, whereas for tree height estimation the ERS interferometric phase has been used. Multi-temporal combination of ERS coherence images, and to a lesser extent of JERS backscatter images, can provide stem volume estimates comparable to stand-wise ground-based measurements. Since the information content of the interferometric phase is strongly degraded by phase noise and uncorrected atmospheric artefacts, the retrieved tree height shows large errors

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

Hemiboreaalsete metsade kaardistamine interferomeetrilise tehisava-radari andmetelt

Väitekirja elektrooniline versioon ei sisalda publikatsioone.Käesolev doktoritöö uurib tehisavaradari (SAR) kasutusvõimalusi metsa kõrguse hindamiseks hemiboreaalsete metsade vööndis. Uurimistöö viidi läbi Tartu Üli¬kooli, Tartu Observatooriumi, Aalto Ülikooli, Euroopa Kosmoseagentuuri (ESA) kaugseire keskuse ESRIN ja Reach-U koostöös. Uurimistöös kasutatud satelliidi¬andmed on pärit Saksa Kosmosekeskuse (DLR) kõrglahutusega bistaatilise X-laineala tehisavaradari TanDEM-X satelliidipaarilt. Sagedasti uuenevad satelliidiandmed, nende globaalne katvus ja kõrge ruumi¬line lahutus võimaldavad tehisavaradari abil kaardistada metsi ning nendes toimu¬vaid muutusi suurtel maa-aladel. Radari abil on võimalik saada kõrge lahutusvõimega pilte, mis on tundlikud taimestikule, maapinna karedusele ja dielektrilistele omadustele. Sünkroonis lendava radaripaari samaaegselt tehtud pildid elimineerivad võimalikud ajalised muutused taimestikus ning tänu sellele on radariandmetest võimalik tuletada metsade vertikaalset struktuuri ja kõrgust. Uurimistöös käsitletakse tehisavaradari interferomeetrilise koherentsuse tund¬likkust metsa kõrguse suhtes ning analüüsitakse, millised keskkonna ja klimaati¬lised tingimused ning satelliidi orbiidiga seotud parameetrid mõjutavad radari¬piltidelt erinevate puuliikide kõrguse hindamise täpsust. Lisaks keskendub väitekiri interferomeetrilisele koherentsusele tuginevate mudelite analüüsi¬misele ning nende täpsuse hindamisele operatiivse metsa kõrguse kaardistamise raken-duseks. Vaatluse alla on võetud kolm testala, mis asuvad Soomaa rahvuspargis, Võrtsjärve idakaldal Rannus ja Peipsiveere looduskaitsealal ning katavad kokku 2291 hektarit metsa. 23 TanDEM-X satelliidipildi koherentsuspilte võrreldakse samadel testaladel aerolaserskaneerimise (LiDAR) abil mõõdetud puistute kõrgu¬sega, mis on omakorda jagatud kolme rühma (kuused, männid ja laia¬lehised segametsad). RVoG (Random Volume over Ground) taimekatte mudel ning sellest tule¬tatud lihtsamad pooleempiirilised mudelid sobituvad olemasolevate TanDEM-X koherentsuse ning LiDARi metsa puistute kõrgusandmetega hästi. Töö tule¬mused kinnitavad, et tulevikus on suurte ja erinevatest metsatüüpidest koosne¬vate metsade kõrguse kosmosest kaardistamisel otstarbekas kasutusele võtta esmalt just soovitatud lihtsamad ja universaalsemad mudelid.This thesis presents research in the field of radar remote sensing and contributes to the forest monitoring application development using space-borne synthetic aperture radar (SAR). Satellite data is particularly useful for large-scale forestry applications making high revisit monitoring of the state of forests worldwide possible. The sensitivity of SAR to the dielectric and geometrical properties of the targets, penetration capacity and coherent imaging properties make it a unique tool for mapping and monitoring forest biomes. SAR satellites are also capable of retrieving additional information about the structure of the forest, tree height and biomass estimates as an essential input for monitoring the changes in the carbon stocks. Interferometric SAR (InSAR) is an advanced SAR imaging technique that allows the retrieval of forest parameters while working in nearly all weather conditions, independently of daylight and cloud cover. This research concen¬trates on assessing the impact of different variables affecting hemiboreal forest height estimation from space-borne X-band interferometric SAR coherence data. In particular, the research analyses the changes in coherence dynamics related to seasonal conditions, tree species and imaging properties using a large collection of interferometric SAR images from different seasons over a four-year period. The study is carried out over three test sites in Estonia using the extensive multi-temporal dataset of 23 TanDEM-X images, covering 2291 hectares of forests to describe the relation between the interferometric SAR coherence mag¬nitude and forest parameters. The work demonstrates how the correlation of interferometric coherence and Airborne LiDAR Scanning (ALS)-derived forest height varies for pine and deciduous tree species, for summer (leaf-on) and winter (leaf-off) conditions and for flooded forest floor. A simple semi-empirical modelling approach is proposed as being suitable for wide area forest mapping with limited a priori information under a range of seasonal and environ¬¬mental conditions. A Random Volume over Ground (RVoG) model and three semi-empirical models are compared and validated against a large dataset of coherence magnitude and ALS-measured data over hemiboreal forests in Estonia. The results show that all proposed models perform well in describing the relationship between hemiboreal forest height and interferometric coherence, allowing in future to derive forest stand height with an accuracy suitable for a wide range of applications