Elevation and Deformation Extraction from TomoSAR

3D SAR tomography (TomoSAR) and 4D SAR differential tomography (Diff-TomoSAR) exploit multi-baseline SAR data stacks to provide an essential innovation of SAR Interferometry for many applications, sensing complex scenes with multiple scatterers mapped into the same SAR pixel cell. However, these are still influenced by DEM uncertainty, temporal decorrelation, orbital, tropospheric and ionospheric phase distortion and height blurring. In this thesis, these techniques are explored. As part of this exploration, the systematic procedures for DEM generation, DEM quality assessment, DEM quality improvement and DEM applications are first studied. Besides, this thesis focuses on the whole cycle of systematic methods for 3D & 4D TomoSAR imaging for height and deformation retrieval, from the problem formation phase, through the development of methods to testing on real SAR data. After DEM generation introduction from spaceborne bistatic InSAR (TanDEM-X) and airborne photogrammetry (Bluesky), a new DEM co-registration method with line feature validation (river network line, ridgeline, valley line, crater boundary feature and so on) is developed and demonstrated to assist the study of a wide area DEM data quality. This DEM co-registration method aligns two DEMs irrespective of the linear distortion model, which improves the quality of DEM vertical comparison accuracy significantly and is suitable and helpful for DEM quality assessment. A systematic TomoSAR algorithm and method have been established, tested, analysed and demonstrated for various applications (urban buildings, bridges, dams) to achieve better 3D & 4D tomographic SAR imaging results. These include applying Cosmo-Skymed X band single-polarisation data over the Zipingpu dam, Dujiangyan, Sichuan, China, to map topography; and using ALOS L band data in the San Francisco Bay region to map urban building and bridge. A new ionospheric correction method based on the tile method employing IGS TEC data, a split-spectrum and an ionospheric model via least squares are developed to correct ionospheric distortion to improve the accuracy of 3D & 4D tomographic SAR imaging. Meanwhile, a pixel by pixel orbit baseline estimation method is developed to address the research gaps of baseline estimation for 3D & 4D spaceborne SAR tomography imaging. Moreover, a SAR tomography imaging algorithm and a differential tomography four-dimensional SAR imaging algorithm based on compressive sensing, SAR interferometry phase (InSAR) calibration reference to DEM with DEM error correction, a new phase error calibration and compensation algorithm, based on PS, SVD, PGA, weighted least squares and minimum entropy, are developed to obtain accurate 3D & 4D tomographic SAR imaging results. The new baseline estimation method and consequent TomoSAR processing results showed that an accurate baseline estimation is essential to build up the TomoSAR model. After baseline estimation, phase calibration experiments (via FFT and Capon method) indicate that a phase calibration step is indispensable for TomoSAR imaging, which eventually influences the inversion results. A super-resolution reconstruction CS based study demonstrates X band data with the CS method does not fit for forest reconstruction but works for reconstruction of large civil engineering structures such as dams and urban buildings. Meanwhile, the L band data with FFT, Capon and the CS method are shown to work for the reconstruction of large manmade structures (such as bridges) and urban buildings

Elevation Extraction from Spaceborne SAR Tomography Using Multi-Baseline COSMO-SkyMed SAR Data

SAR tomography (TomoSAR) extends SAR interferometry (InSAR) to image a complex 3D scene with multiple scatterers within the same SAR cell. The phase calibration method and the super-resolution reconstruction method play a crucial role in 3D TomoSAR imaging from multi-baseline SAR stacks, and they both influence the accuracy of the 3D SAR tomographic imaging results. This paper presents a systematic processing method for 3D SAR tomography imaging. Moreover, with the newly released TanDEM-X 12 m DEM, this study proposes a new phase calibration method based on SAR InSAR and DEM error estimation with the super-resolution reconstruction compressive sensing (CS) method for 3D TomoSAR imaging using COSMO-SkyMed Spaceborne SAR data. The test, fieldwork, and results validation were executed at Zipingpu Dam, Dujiangyan, Sichuan, China. After processing, the 1 m resolution TomoSAR elevation extraction results were obtained. Against the terrestrial Lidar ‘truth’ data, the elevation results were shown to have an accuracy of 0.25 ± 1.04 m and a RMSE of 1.07 m in the dam area. The results and their subsequent validation demonstrate that the X band data using the CS method are not suitable for forest structure reconstruction, but are fit for purpose for the elevation extraction of manufactured facilities including buildings in the urban area

Land Cover Classification using Sentinel-1 Radar Mission Interferometry

Synthetic Aperture Radar (SAR) has been widely used for many years in the field of remote sensing. SAR has valuable contribution due to its ability to provide complementary information to optical systems, penetration of radar waves through volumetric targets and high-resolution. SAR has the ability to operate during day and night. It provides operational services under all weather conditions. SAR imagery has many applications including land cover changes, environmental monitoring, climate change and military surveillance. This work focuses on land cover classification with SAR interferometry (InSAR) technique using Sentinel-1 space radar image pair. Sentinel-1 data were collected over the southern part of Estonia. Two SLC SAR images were acquired from both Sentinel-1A and Sentinel-1B with six days temporal difference. In this study, interferometric coherence and backscattering intensity processing chains have been set up and applied to Sentinel-1 SAR image pair. The Sentinel Application Platform (SNAP) has been used for processing of single pair for Sentinel-1 mission. The SNAP is an European Space Agency (ESA) software. The Sentinel-1 image pair processing has been done using Sentinel-1 Toolbox (S1TBX) which is a part of SNAP. Corine Land Cover (CLC) 2012 database has been used as a reference data with 20 m resolution. The CLC2012 contains land use/cover information for most of the European countries. A single optical image from Sentinel-2A was additionally used for feature extraction. An overall accuracy of 68% to 73% was achieved when performing classification into five classes (Urban, Field, Forest, Peat-land, Water) using supervised classification with k-nearest neighbour (kNN) algorithm. The accuracy assessment was done by using confusion matrices

Využití družicové SAR interferometrie pro identifikaci a mapování sesuvů ve městě Sánchez, Dominikánské republice

The landscapes we see today are the result of constant changes during millions of years. Mass movement is one of the principal geomorphology process responsible for these changes and occurs in different scales around the world, causing disaster in populated areas. Sánchez is a municipality located in Samaná province, Dominican Republic, where continuous motion had created an atmosphere of uncertainness among the inhabitants, that observed day after day the deterioration of infrastructures, loss of agricultural capability and potential life-threatening situations. Slope instability has been increased by anthropogenic activity and triggers factors as: elimination of forest for coconut plantation, lack of proper wasted drainage and drinking water supply system, growth of community, change of construction material, meteorological phenomena and seismic events. This investigation aims to identify slope movement and map it, using SENTINEL-1 satellite SAR interferometry (InSAR). By applying multi-temporal techniques to a series of SENTINEL-1 scenes, it is possible to recognize a continuous surface deformation in the area. The results will help authorities to develop short and long-term risk management plans.Zeměpisy, které dnes vidíme, jsou výsledkem neustálých změn v průběhu několika miliónů let. Masový pohyb je jedním z hlavních geomorfologických procesů zodpovědných za tyto změny a probíhá v různých měřítkách po celém světě a způsobuje katastrofu v osídlených oblastech. Sánchez je obec ležící v provincii Samaná, Dominikánská republika, kde neustálý pohyb vytvářel atmosféru nejistoty mezi obyvateli, která každodenně pozorovala zhoršování infrastruktury, ztrátu zemědělské kapacity a potenciální život ohrožující situace. Nestabilita svahu byla zvýšena antropogenní aktivitou a spouští faktory jako: odstranění lesů pro kokosové plantáže, nedostatek správného odpadního kanalizace a zásobování pitnou vodou, růst obce, změna stavebního materiálu, meteorologické jevy a seismické události. Cílem tohoto šetření je identifikovat pohyb svahu a mapovat ho pomocí SARINEL-1 satelitní SAR interferometrie (InSAR). Aplikací multičasových technik na řadu scén SENTINEL-1 je možné rozpoznat kontinuální povrchovou deformaci v oblasti. Výsledky pomohou orgánům vypracovat krátkodobé a dlouhodobé plány řízení rizik.548 - Katedra geoinformatikyvýborn

Digital Canopy Model Estimation from TanDEM-X Interferometry using High-Resolution Lidar DEM

Interferometric TanDEM-X data are used together with high-resolution, airborne lidar-derived digital elevation models (DEMs) to produce digital canopy models (DCMs) for the boreal forests of Remningstorp and Krycklan, situated in southern and northern Sweden, respectively. An overview of interferometric data processing is given. First results showing the potential of TanDEM-X-based forest canopy mapping are presented. It is concluded that baselines giving height-of-ambiguity values in the order of 50-80 meters are preferable, although factors such as angle of incidence and along-track baseline are also of importance. Clear-cuts can easily be detected thanks to the high resolution of TanDEM-X imagery. Seasonal variations of scattering height are most visible for deciduous trees, where the scattering height is significantly lower in the winter, probably due to the lack of leaves. \ua9 2013 IEEE

Interferometric Processing of TanDEM-X Images for Forest Height Estimation

Biomass is one of the most desired parameters for applications like climate modelling, resource assessment or wood industry. By using allometry equations (82) it is possible to obtain biomass information from canopy height. Some studies have demonstrated that current interferometric techniques applied to airborne Synthetic Aperture Radar (SAR) images can provide fairly accurate estimates of tree height (45, 52, 53, 54). Space based interferometric methods can provide global estimates of canopy height but they require very accurate orbit information. In this work the ability of the recently launched SAR satellites TerraSAR-X and TanDEM-X to estimate canopy height is evaluated.To do this, a complete interferometric processing chain is created including SAR data reading into memory, complex interferogram calculation, interferogram flattening by at Earth approximation and image transformation to geographical coordinates.Finally the resulting phase height maps are compared with a digital elevation model and a canopy height model of the terrain under study as well as with X-band E-SAR data from the FINSAR campaign (52, 53, 54) of the same area

Land Deformation Monitoring using Synthetic Aperture Radar Interferometry

Master'sMASTER OF ENGINEERIN

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

Retrieval of Ocean Surface Currents and Winds Using Satellite SAR backscatter and Doppler frequency shift

Ocean surface winds and currents play an important role for weather, climate, marine life, ship navigation, oil spill drift and search and rescue. In-situ observations of the ocean are sparse and costly. Satellites provide a useful complement to these observations. Synthetic aperture radar (SAR) is particularly attractive due to its high spatial resolution and its capability to extract both sea surface winds and currents day and night and almost independent of weather.The work in this thesis involves processing of along-track interferometric SAR (ATI-SAR) data, analysis of the backscatter and Doppler frequency shift, and development of wind and current retrieval algorithms. Analysis of the Doppler frequency shift showed a systematic bias. A calibration method was proposed and implemented to correct for this bias. Doppler analysis also showed that the wave contribution to the SAR Doppler centroid often dominates over the current contribution. This wave contribution is estimated using existing theoretical and empirical Doppler models. For wind and current retrieval, two methods were developed and implemented.The first method, called the direct method, consists of retrieval of the wind speed from SAR backscatter using an empirical backscatter model. In order to retrieve the radial current, the retrieved wind speed is used to correct for the wave contribution. The current retrieval was assessed using two different (theoretical and empirical) Doppler models and wind inputs (model and SAR-derived). It was found that the results obtained by combining the Doppler empirical model with the SAR-derived wind speed were more consistent with ocean models.The second method, called Bayesian method, consists of blending the SAR observables (backscatter and Doppler shift) with an atmospheric and an oceanic model to retrieve the total wind and current vector fields. It was shown that this method yields more accurate estimates, i.e. reduces the models biases against in-situ measurements. Moreover, the method introduces small scale features, e.g. fronts and meandering, which are weakly resolved by the models.The correlation between the surface wind vectors and the SAR Doppler shift was demonstrated empirically using the Doppler shift estimated from over 300 TanDEM-X interferograms and ECMWF reanalysis wind vectors. Analysis of polarimetric data showed that theoretical models such as Bragg and composite surface models over-estimate the backscatter polarization ratio and Doppler shift polarization difference. A combination of a theoretical Doppler model and an empirical modulation transfer function was proposed. It was found that this model is more consistent with the analyzed data than the pure theoretical models.The results of this thesis will be useful for integrating SAR retrievals in ocean current products and assimilating SAR observables in the atmospheric, oceanic or coupled models. The results are also relevant for preparation studies of future satellite missions