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TanDEM-X and TerraSAR-X platforms form together the first spaceborne single-pass polarimetric interferometer in space. This allows, for the first time, the acquisition of spaceborne polarimetric ...synthetic aperture radar interferometry (Pol-InSAR) data without the disturbing effect of temporal decorrelation. This paper aims to assess the potential of such data for forest applications. For this, single- and dual-pol data acquired over a boreal, a temperate, and a tropical site were investigated to characterize X-band penetration and polarization diversity of the interferometric coherence measurements. Pol-InSAR forest height inversion schemes have been proposed and implemented for the singleand dual-pol cases and cross validated against LIDAR reference measurements for all sites. The single-pol inversion relies on an external ground digital terrain model (DTM) and performed well for all sites with correlation coefficients r 2 between 0.80 and 0.98. The dual-pol inversion does not require an external DTM but depends on the visibility of the whole forest layer. Accordingly, its performance varied with forest structure and season: The best performance was achieved for the summer acquisition of the boreal test site (r 2 = 0.86) and for the winter acquisition of the temperate test site (r 2 = 0.77). For the tropical test site, only a weak correlation (r 2 = ~0.50) could be established.
The three-pass differential synthetic aperture radar interferometry (DInSAR) is one of the approaches in radar interferometry applications for measuring the deformation of the earth surface. The ...conventional three-pass DInSAR needs a successful single-baseline (SB) phase unwrapping (PU) procedure on each interferogram to ensure accurate deformation monitoring. Because of the limitation of the phase continuity assumption, the SB PU becomes a challenging processing step when the study area has strong phase variation. In this paper, the multibaseline (MB) InSAR PU methodology, which can eliminate the phase continuity assumption by means of the baseline diversity, is transplanted into the conventional three-pass DInSAR domain. Based on MB PU, a novel terrain deformation estimation approach is developed. Both theoretical analysis and experimental results demonstrate that the proposed method is an effective surface deformation estimation method.
Earth's sinking surface Nicholls, Robert J; Shirzaei, Manoochehr
Science (American Association for the Advancement of Science),
2024-Apr-19, 2024-04-19, 20240419, Letnik:
384, Številka:
6693
Journal Article
Recenzirano
China's major cities show considerable subsidence from human activities.
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.
•BIOMASS will be the first spaceborne P-band mission.•Global estimates of forest biomass and height, subject to US DoD restrictions•The first systematic use of Pol-InSAR to measure forest height from space•The first systematic use of spaceborne SAR tomography•Sub-surface imaging, icesheet motion estimation and a bias-free DTM
The proper use of distributed scatterer (DS) can improve both the density and quality of synthetic aperture radar (SAR) interferometry (InSAR) measurements. A critical step in DS interferometry (DSI) ...is the restoration of a consistent phase series from SAR interferogram stacks. Most state-of-the-art algorithms adopt an approximate likelihood function to calculate the likelihood by replacing the true coherence matrix with its estimation, more specifically, the sample coherence matrix (SCM). However, this approximation has a drawback in that the coherence estimates are greatly biased when the coherence is low. In this study, we derive a new likelihood function without such an approximation. Accordingly, a DSI framework using this function for phase estimation and point selection is provided. In this framework, the new likelihood function serves as a cost function for phase estimation and a quality measure for DS selection. Its performance is investigated by experiments in a simulation study and a real-world case study using Sentinel-1 data over Shenzhen airport in China. The results reveal that the proposed DSI framework outperforms the existing state-of-the-art approaches in different scenarios, in terms of providing a more accurate estimation and improving DS density and coverage.
The Hong Kong International Airport (HKIA) was constructed on a platform mainly reclaimed from the sea. The platform has experienced some significant settlement since its operation in 1998 due mainly ...to consolidation of the materials used in the land reclamation. Although some studies have been carried out to measure the settlement with techniques such as Interferometric Synthetic Aperture Radar (InSAR), the past studies have each only covered some limited time periods. Therefore, a complete history of settlement since the operation of the Airport has never been available to aid the understanding of the spatiotemporal behavior of the land settlement. We attempt for the first time to make full use of most of the available SAR data from multiple SAR sensors (ERS-2, ENVISAT ASAR, COSMO-SkyMed (CSK), and Sentinel-1A) to generate a settlement time series of the HKIA over 1998–2018 with an improved multi-temporal InSAR technique. In order to fill the time gaps between the different SAR datasets, a settlement model is developed based on the InSAR measurements. The results reveal both the spatial and temporal variations of the land settlement. They also show for the first time that the accumulative settlement reaches up to 40 cm over the past two decades. The settlement is largely associated with the material types used in the landfill works and the underlying alluvial sediments as some earlier research has indicated, and the stages of the reclamation works. The results are validated through cross-validation between the datasets and with leveling and GPS measurements on the Airport platform.
•Two decades of land settlement history of HKIA is retrieved for the first time.•Land settlement correlates strongly to landfill materials and reclamation methods.•Research results inform future land reclamation practice.
The cloud-free, wide-swath, day-and-night observation capability of synthetic aperture radar (SAR) has an important role in rapid landslide monitoring to reduce economic and human losses. Although ...interferometric SAR (InSAR) analysis is widely used to monitor landslides, it is difficult to use that for rapid landslide detection in mountainous forest areas because of significant decorrelation. We combined polarimetric SAR (PolSAR), InSAR, and digital elevation model (DEM) analysis to detect landslides induced by the July 2017 Heavy Rain in Northern Kyushu and by the 2018 Hokkaido Eastern Iburi Earthquake. This study uses fully polarimetric L-band SAR data from the ALOS-2 PALSAR-2 satellite. The simple thresholding of polarimetric parameters (alpha angle and Pauli components) was found to be effective. The study also found that supervised classification using PolSAR, InSAR, and DEM parameters provided high accuracy, although this method should be used carefully because its accuracy depends on the geological characteristics of the training data. Regarding polarimetric configurations, at least dual-polarimetry (e.g., HH and HV) is required for landslide detection, and quad-polarimetry is recommended. These results demonstrate the feasibility of rapid landslide detection using L-band SAR images.
Interferometric phase denoising is a vital procedure for interferometric synthetic aperture radar (InSAR)-based remote sensing techniques because it can improve the accuracy of the final InSAR ...product. Here, we propose a deep convolutional neural network (DCNN)-based InSAR phase denoising method, abbreviated PDNet. Given an ideal wrapped phase, <inline-formula> <tex-math notation="LaTeX">\bar {\varphi } </tex-math></inline-formula>, the PDNet learns the self-similarity function (SSF) of <inline-formula> <tex-math notation="LaTeX">\bar {\varphi } </tex-math></inline-formula> from the input interferogram. After training, the PDNet obtains filtered wrapped phases using the maximum-likelihood approach by exhausting all <inline-formula> <tex-math notation="LaTeX">\bar {\varphi }\text{s} </tex-math></inline-formula> from <inline-formula> <tex-math notation="LaTeX">-\pi </tex-math></inline-formula> to <inline-formula> <tex-math notation="LaTeX">\pi </tex-math></inline-formula>. Unlike a boxcar-based filtering method, the PDNet does not consist of an "averaging operation" on the spatial domain, and the resolution loss and interferometric fringe distortion will not directly affect the PDNet result. Thus, PDNet can be considered a nonlocal (NL) phase denoising approach. Analyses and results show that PDNet is an almost near-real-time denoising algorithm. Its denoising accuracy is higher than that of the available model- and learning-based InSAR phase denoising methods.
The combined application of continuous Global Positioning System data (high temporal resolution) with spaceborne interferometric synthetic aperture radar data (high spatial resolution) can reveal ...much more about the complexity of large landslide movement than is possible with geodetic measurements tied to only a few specific measurement sites. This approach is applied to an ~4 km2 reactivated translational landslide in the Columbia River Gorge (Washington State), which moves mainly during the winter rainy season. Results reveal the complex three‐dimensional shape of the landslide mass, how onset of sliding relates to cumulative rainfall, how surface velocity during sliding varies with location on the topographically complex landslide surface, and how the ground surface subsides slightly in weeks prior to downslope sliding.
Key Points
Sentinel‐1A InSAR and GPS results reveal rainfall‐triggered landslide‐body surface subsidence prior to downslope sliding
3D deformation measurements provide insights on the temporal and spatial complexity of landslide dynamics
Spaceborne InSAR‐derived displacement fields can be used to invert for active landslide thickness variation based on mass conservation
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