1,498 research outputs found
Vegetation Characterization through the Use of Precipitation-Affected SAR Signals
No full textCurrent space-based SAR offers unique opportunities to classify vegetation types and to monitor vegetation growth due to its frequent acquisitions and its sensitivity to vegetation geometry. However, SAR signals also experience frequent temporal fluctuations caused by precipitation events, complicating the mapping and monitoring of vegetation. In this paper, we show that the influence of a priori known precipitation events on the signals can be used advantageously for the classification of vegetation conditions. For this, we exploit the change in Sentinel-1 backscatter response between consecutive acquisitions under varying wetness conditions, which we show is dependent on the state of vegetation. The performance further improves when a priori information on the soil type is taken into account.After publication of the research paper [1], the authors wish to make the following correction. The link to the affiliation of Ramon F. Hanssen should have been (1). Hence, the affiliation of Ramon F. Hanssen is Geoscience and Remote Sensing at Delft University of Technology. The authors would like to apologize for any inconvenience caused. The change does not affect the scientific results. The manuscript will be updated and the original will remain online on the article webpage, with a reference to this correction. Reference 1. Molijn, R.A.; Iannini, L.; López Dekker, P.; Magalhães, P.S.; Hanssen, R.F. Vegetation Characterization through the Use of Precipitation-Affected SAR Signals. Remote Sens. 2018, 10, 1647. [CrossRef]Mathematical Geodesy and PositioningOptical and Laser Remote Sensin
Dr. Shanesha R.F. Brooks-Tatum, RWWL AUC, July 2011
No full textThis video is a conversation with Dr. Shanesha R.F. Brooks-Tatum. Dr. Brooks-Tatum talks about her book, "The Encyclopedia of Hip Hop Literature." Daniel Le, AUC Woodruff Library, is the interviewer
Geodetic network design for InSAR: Application to ground deformation monitoring
No full textFor the past two decades, interferometric synthetic aperture radar (InSAR) has been used to monitor ground deformation with subcentimetric precision from space. But the applicability of this technique is limited in regions with a low density of naturally-occurring phase-coherent radar targets, e.g. vegetated nonurbanized areas. Third-party end-users of InSAR survey results cannot, in a systematic way, determine a priori whether these coherent targets have adequate spatial distribution to estimate the parameters of their interest. Additionally, InSAR deformation estimates are referred to a local datum, meaning that the technique is sensitive only to the relative deformation occurring within the SAR images. This makes it difficult to compare these estimates with those from other techniques, e.g. historical levelling data or changes in the sea level. Here we propose the design of a geodetic network for InSAR, aimed at densifying the naturally-occurring measurement network and converting from a local datum to a global one. A practical solution for improving spatial sampling is to deploy coherent target devices such as corner reflectors or transponders on ground, tailored to the specific monitoring application under consideration. The proposed method (1) provides a generic description of any deformation phenomenon; (2) determines whether the naturally-occurring InSAR measurements are adequate in terms of user-defined criteria; (3) finds the minimum number of additional devices to be deployed (if required); and (4) finds their optimal ground locations. It digests, as inputs, any prior knowledge of the deformation signal, the expected locations and quality of the existing coherent targets, and the quality of the deployed devices. The method is based on comparing different covariance matrices of the final parameters of interest with a criterion matrix (i.e., the ideal desired covariance matrix) using a predefined metric. The resulting measurement network is optimized with respect to precision, reliability and economic criteria; this is demonstrated via synthetic examples and a case of subsidence in the Netherlands. As a basis for the choice and number of deployed devices, we evaluate the measurement precision of compact active transponders and demonstrate their viability as alternatives to passive corner reflectors through three field experiments, using different satellite data and geodetic validation techniques. Transponders are shown to be usable for subcentimetre-precision geodetic applications, while improving upon the drawbacks of corner reflectors in terms of size, shape, weight and conspicuousness. For transforming the spatially-relative InSAR deformation estimates (local datum) to a standard terrestrial reference frame (global datum), we introduce a new concept involving the collocation of transponders with Global Navigation Satellite System (GNSS) measurements. The displacement of such a transponder is consequently determined in the standard reference frame used by GNSS, eliminating the need for any assumptions on reference-point stability in applications where the InSAR deformation estimates are compared with results from other techniques. The considerations, results and practical lessons learnt at several permanent GNSS stations in the Netherlands are described.Geoscience and Remote SensingCivil Engineering and Geoscience
Satellite radar interferometry: Estimation of atmospheric delay
No full textGeoscience and Remote ControlAerospace Engineerin
Monitoring civil infrastructure using satellite radar interferometry
No full textSatellite radar interferometry (InSAR) is a precise and efficient technique to monitor deformation on Earth with millimeter precision. Most InSAR applications focus on geophysical phenomena, such as earthquakes, volcanoes, or subsidence. Monitoring civil infrastructure with InSAR is relatively new, with potential for operational applications, but currently not exploited to full advantage. Here we investigate how to optimally assess and monitor the structural health of civil infrastructure using InSAR, and develop methodology to improve its capability for operational monitoring. InSAR kinematic time series analysis involves the processing of extremely large datasets to estimate the relative movements of points on the infrastructure. The estimated movements may expose strain in the structure, potentially revealing structural health problems. However, the optimal mathematical model relating the satellite observations to the kinematic parameters of interest is unknown. We propose multiple hypothesis testing as a means to identify the most probable mathematical model. For each target, the null-hypothesis of ‘steady-state’ motion is considered as default, which is tested against a multitude of potential temporal models, built based on a library of canonical functions. If the null hypothesis is sustained, there is no (significant) anomaly in the data. If the null hypothesis is rejected, we test the entire library of potential alternative models with different physically realistic parameters against the null hypothesis using the B-method of testing. Finally, using test-ratios, we select the most likely model for each target, update the quality description of the estimates, while avoiding overfitting. InSAR processing strategies are designed and implemented for structural health assessment of railway infrastructure and buildings. The Qinghai-Tibet railway, at 5000m altitude, is suspected to be affected by dynamic changes in permafrost environments. Using medium resolution SAR data, we apply an ‘all-pixel’ approach based on statistical similarity to tackle geometric decorrelation and maximize the density of InSAR measurement points over the track. Seasonal changes in deformation are detected, most likely due to freezing and thawing of the permafrost’s active layer. To explore the capability of railway infrastructure monitoring using multi-track high-resolution SAR data, we estimate the 3D temporal behavior of the Betuwe railway, the Netherlands, in a track-fixed reference system in the transversal, longitudinal, and normal direction using 248 TerraSAR-X images acquired from ascending and descending orbits. For building monitoring, we study a shopping mall in Heerlen, the Netherlands. Due to a developing sinkhole below, the building lost its structural support, leading to a sudden evacuation and a near-collapse. Using consecutive InSAR data time series acquired by four different SAR satellites between 1992 and 2011, we find significant precursory motion. We integrate these InSAR data time series and improve the precision of geolocation of the InSAR measurement points using additional lidar-based data. The detected localized strain appears to be related to an upward migrating cavity. The analysis demonstrates the feasibility of an early detection of anomalous processes in the underground. This study reveals the high potential of structural health monitoring using observations from satellites, either for forensic analysis—investigating the behavior of a structure after a failure manifested itself—or for preventive monitoring—to identify anomalies in behavior that may be indicative for impending structural failure.Department of Geoscience and Remote SensingCivil Engineering and Geoscience
Improving radar interferometry for monitoring fault-related surface deformation: Applications for the Roer Valley Graben and coal mine induced displacements in the southern Netherlands
No full textRadar interferometry (InSAR) is a valuable tool to measure surface motion. Applying time series techniques such as Persistent Scatterer Interferometry (PSI), InSAR is able to provide surface displacements maps with mm-precision. However, InSAR can still be further optimized, e.g. by exploiting spatial characteristics of the signal of interest. This study addresses surface deformation associated with geological faults. In principle, this signal is generally spatially smooth but with significant-to-large gradients at fault locations. We first focus on optimizing InSAR time series analysis, in particular the PSI method, for this specific class of ground deformation processes. Secondly, we apply the improved technique to study fault-related motion in the southern Netherlands, with special interest in detecting neotectonic motion in the Roer Valley Graben and deformation in the abandoned mines of South Limburg. The proposed optimization adapts PSI to analyze in an iterative manner the signal of interest to estimate spatially the probability density function of displacements. Since the signal is expected to change quickly near faults, we do not restrict this distribution to be unimodal but we allow it to have any shape. Finally, we use the determined distribution to constrain, through Bayesian inference, phase unwrapping (the operation of unfolding the phase outside its natural range of (?pi, pi] radians). We demonstrate a substantial benefit of the Bayesian approach as we show a decrease in the number of unwrapping errors. This thesis also suggests a method that analyzes interferometric phases to estimate noise variance. It is built upon the assumption that coherence can be spatially correlated. The estimated stochastic parameters are used in phase unwrapping by assigning lower weights to noisy observations. The improved methodology is applied to study fault-related motion in the southern Netherlands, exploiting data from three satellite missions: ERS-1, ERS-2 and Envisat. In particular, we focus on two main areas: the Roer Valley Graben and the abandoned mines of south Limburg. In the Roer Valley Graben area, a deformation signal associated with geological faults is detected. However, we do not observe any significant indication to atribute a tectonic origin to this signal for two main reasons. First, during large part of the studied period the most of the graben uplifts with respect to adjacent horsts at rates of ~1 mm/yr, behaving opposite to predicted by tectonics. Second, the deformation signal in this area appears to be largely related to water pumping. For example, we observe an uplift signal of about +4 mm/yr that matches in time and space with the cease of pumping in the Erkelenz Coal District, which is located in the Peel horst, adjacent to the Roer Valley Graben. Concerning the mines of South Limburg, we detect strong surface displacements (uplift) which appear to be centered on the old mines and constrained by tectonic faults. The signal is variable in space and time, with uplift rates up to 20 cm in 18 years, and relatively large gradients across faults (~5 cm/km), in the same time span. Laterally the uplift signal propagates towards the west in this period. The comparison of surface displacements with rising groundwater levels reveal a strong correlation between the two, suggesting the groundwater to be the cause of the uplift. Assuming that rising ground water levels in the abandoned mines are responsible for the uplift, we estimate the relation between the groundwater and the associated uplift. The skeletal storage coefficient, which directly depends on porosity, is on average 0.5±0.1·10?3, implying that 1 m of water level increase produces 0.5 mm uplift. As we expect that the water may rise many tens of meters, especially in the western side, this may result in several additional centimeters of future uplift. Essentially, the surface displacements that we observe in the southern Netherlands seem to be mainly caused by fluctuations in groundwater flow, which appear to be constrained by faults.Geoscience & Remote SensingCivil Engineering and Geoscience
Letter: R.F. Pettigrew to H.L. Loucks, May 30, 1916
No full textR.F. Pettigrew articulates to H.L. Loucks his distaste for the book that Loucks recommended to him. Pettigrew also mentions that he would prefer to remain distanced from any conference with the author of the book. Pettigrew expresses great admiration and interest in Loucks' manuscript and desire to read it further
The evolution of fat grafting : from soft tissue augmentation to regenerative medicine
No full textThe Author traces the evolution of fat grafting over the years from the first publication in 1893, to the systematization of the technique thanks to the contribution of Sydney Coleman. In recent years studies on the nature of adipose tissue have shown that besides multiple resident cells, fat tissue contains stem cells (ADSCs) capable of differentiating in multiple lineages, such as bone, cartilage, muscle, nerve, etc. Thus, in addition to the traditional notion that fat is a high energy reservoir, it becomes apparent that fat is a repair organ providing the basis for soft tissue regeneration. Manipulation of ADSCs promises to affect different fields of medicine and provide the physician with a variety of regenerative medical therapies
Persistent Scatterer Interferometry based on geodetic estimation theory
No full textThe Earth's surface is continuously deforming due to natural and anthropogenic processes, such as tectonics, landslides, oil and gas extraction, and groundwater level changes. Persistent Scatterer Interferometry is a technique that provides measurements of this surface motion based on satellite radar images. The technique uses the persistent radar reflection from certain objects on the Earth's surface to estimate their deformation time series. However, since the location of these objects is unknown, Persistent Scatterer Interferometry comprises both an estimation and a detection problem. In this contribution a Persistent Scatterer Interferometry algorithm is presented that resolves this estimation and detection problem based on geodetic estimation theory. The complete processing procedure, from the original radar images to the geolocated Persistent Scatterers, is described. Herein, the estimation of the unknown phase ambiguities, both in the time and space domain, forms a key component. The developed algorithm is characterized by a continuous update of the stochastic model of the phase observations after the estimation and removal of error sources, a direct testing of the estimated phase ambiguities, and the ability to apply local deformation models to improve the number of detected Persistent Scatterers and the reliability of the estimated time series.Geoscience and Remote SensingCivil Engineering and Geoscience
Displacement parameter estimation using permanent scatterer interferometry
No full textCivil Engineering and Geoscience
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