Dr. Fabio Bovenga Profile

Dr. Fabio Bovenga

Senior Researcher

SPIE Involvement:

Conference Chair | Editor | Author

Area of Expertise:

SAR , SAR Interferometry , Earth Observation , Signal Processing

Websites:

Personal Website | Company Website

Profile Summary

He received the laurea degree and the Ph.D. degree in Physics from the University of Bari (Italy). His research activity started in 1999 at Physics department of the same University, and in 2008 he joined the National Research Council (CNR) of Italy at ISSIA institute. Presently, he is with CNR IREA institute as senior researcher. His main research interests concern advanced processing techniques for SAR imaging and SAR interferometry, and the application of multi-temporal / multi-frequencies analysis to ground monitoring. He participated to many scientific projects (also as principal investigator) funded by national ad international institutions. He attends international symposia on remote sensing and signal processing as speaker, chair and member of scientific committee. He has been invited as lecturer for tutorials on SAR Interferometry and its applications, in foreign universities and international conferences. He has been co-advisor for several degree theses in Physics and Electronic Engineering. From 2003 to 2015 he has been lecturer on SAR / InSAR principles and techniques at the Master on "Spaceborne Remote Sensing" of Bari University. Since 2020 is adjunct professor on “Satellite Systems for Remote Sensing and Geolocation” at Polytechnic University of Bari. He is in the editorial board of Sensors and Mathematical Problems in Engineering, and he served as guest editor for two special issues for Sensors e Geosciences. He has co-authored more than 150 among journal papers, book chapters and conference communications, and serves as paper reviewer for several international peer-reviewed journals. He is also in the board of the IEEE Geoscience and Remote Sensing South Italy Chapter.

Publications (28)

Proceedings Article | 20 October 2023 Presentation

Presentation

Detection of badland erosion by exploring time series of interferometric coherence and phase

Alberto Refice, Fabio Bovenga, Francesco Lovergine, L. Partipilo, D. Capolongo, Raffaele Nutricato, Davide Nitti

Proceedings Volume PC12732, PC1273201 (2023) https://doi.org/10.1117/12.3007787

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Proceedings Article | 20 October 2023 Presentation

Presentation

Alpine rock glacier deformation estimation by using SAR multifrequency data

Giovanni Cuozzo, Melisa Soledad Heredia, Mattia Callegari, Fabio Bovenga, Ludovica De Gregorio, Abraham Mejia-Aguilar, Aldo Bertone, Ilienia Argentiero, Antonella Belmonte, Alberto Refice, Claudia Notarnicola

Proceedings Volume PC12732, PC1273205 (2023) https://doi.org/10.1117/12.2683972

KEYWORDS: Synthetic aperture radar, Glaciers, Deformation, Temporal resolution, Global Positioning System, Spatial resolution, Objectives, Image analysis, Correlation coefficients

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Proceedings Article | 20 October 2023 Presentation

Presentation

Differential SAR interferometry for snow water equivalent estimation over Alpine mountains

Fabio Bovenga, Antonella Belmonte, Alberto Refice, Ilenia Argentiero

Proceedings Volume PC12732, PC1273204 (2023) https://doi.org/10.1117/12.2680508

KEYWORDS: Synthetic aperture radar, Interferometry, L band, Phase interferometry, Error analysis, Data modeling, Atmospheric modeling, Aliasing, X band, Process modeling

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The differential SAR interferometry (DInSAR) phase can be approximated as a linear function of the snow water equivalent (SWE) changes in snow depth and density. The SWE estimation from DInSAR phase presents some criticalities related both to the penetration of the SAR signal into the snowpack, and the nature of interferometric measurements. This work revises some of the issues related to the SWE estimation, and experiments the use of multifrequency SAR data for deriving SWE maps over Alpine areas. Preliminarily, we performed a theoretical analysis aimed at assessing the performance of DInSAR-based SWE estimation at X, C and L bands. According to the indications coming from this analysis C and L band are the more promising to overcome some of the factors limiting the SWE estimation. A dataset of 345 Sentinel-1 images was selected with the aim to explore the interferometric coherence over time and to exploit the short revisit time of the Sentinel-1 constellation. SAOCOM data were also used, for taking advantage of the long L-band wavelength, which should guarantee SAR penetration into the snowpack, snow homogeneity, suitable values of interferometric coherence, and low probability of phase aliasing. The datasets were processed by adopting a “cascaded” interferogram formation approach. Atmosphere artifacts were removed by using the zenith total delay maps derived by GACOS. In order to select pixels suitable for performing a valuable SWE estimation, a sensibility map was generated for each interferometric pair. Both Sentinel-1 and SAOCOM datasets selected over the test cases were processes according to described processing strategy. The SWE estimations resulting from C- and L-band data were combined and analysed looking at their behavior in space and time. - Acknowledgments - This work was carried out in the framework of the project “CRIOSAR: Applicazioni SAR multifrequenza alla criosfera”, funded by ASI under grant agreement n. ASI N. 2021-12-U.0.

Proceedings Article | 17 October 2023 Presentation + Paper

Presentation + Paper

Exploiting artificial reflectors for SAR interferometry applications

Davide Oscar Nitti, Raffaele Nutricato, Khalid Tijani, Fabio Bovenga, Alberto Refice, Roberto Bellotti, Giovanni Preziosa, Antonio Mongelli

Proceedings Volume 12732, 1273204 (2023) https://doi.org/10.1117/12.2680622

KEYWORDS: Reflectors, Chromium, Synthetic aperture radar, Signal processing, Interferometry, X band, Backscatter, Sensors, Image processing, Transponders

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Proceedings Article | 12 September 2021 Presentation

Presentation

Identification and analysis of nonlinear trends in InSAR displacement time series

Fabio Bovenga, Alberto Refice, Guido Pasquariello, Raffaele Nutricato, Davide Nitti

Proceedings Volume 11861, 118610G (2021) https://doi.org/10.1117/12.2600135

KEYWORDS: Interferometric synthetic aperture radar, Synthetic aperture radar, Landslides, Kinematics, Statistical modeling, Statistical analysis, Satellites, Nonlinear optics, Interferometry, Interference (communication)

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Multi-temporal SAR interferometry (MTInSAR) allows analysing wide areas, identifying critical ground instabilities, and studying the phenomenon evolution in a long time-scale. Nowadays satellite SAR constellations provide datasets covering time periods of several years with short revisit times, which allow investigating ground displacements showing non-linear kinematics. These are particularly interesting since they include warning signals related to pre-failure of natural and artificial structures. Recently, approaches have been proposed for recognising and analysing nonlinear displacements, which use different strategies. The authors have introduced two innovative indexes for characterising MTInSAR time series: one relies on the fuzzy entropy and measures the disorder in a time series, the other performs a statistical test based on the Fisher distribution for selecting the polynomial model that more reliably approximate the displacement trend. This work reviews the theoretical formulation of these indexes and evaluate their performances by simulating time series with different characteristics in terms of kinematic, level of noise, signal length and temporal sampling. Finally, the proposed procedures are used for analysing displacement time series derived by processing real datasets acquired by both Sentinel-1 and COSMO-SkyMed constellations. In particular the hilly villages of Pomarico and Montescaglioso have been investigated, which are located in Southern Italian Apennine (Basilicata region), in an area where several landslides occurred in the recent past, causing damages to houses, commercial buildings, and infrastructures. The MTInSAR displacement time series have been analysed by using the proposed methods, searching for nonlinear trends that are possibly related to relevant ground instabilities and, in particular, to potential early warning signals for the landslide events affecting Mtescaglioso in 2013 and Pomarico in 2019. Acknowledgments - This work was supported in part by the Italian Ministry of Education, University and Research, D.D. 2261 del 6.9.2018, Programma Operativo Nazionale Ricerca e Innovazione (PON R&I) 2014–2020 under Project OT4CLIMA.

Proceedings Article | 12 September 2021 Presentation

Presentation

Welcome and Introduction to Conference 11861

Fabio Bovenga, Claudia Notarnicola, Nazzareno Pierdicca, Emanuele Santi

Proceedings Volume 11861, 1186102 (2021) https://doi.org/10.1117/12.2613763

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Proceedings Article | 18 October 2019 Presentation

Presentation

Analysis of displacement time series from multitemporal SAR interferometry (Conference Presentation)

Guido Pasquariello, Fabio Bovenga, Alberto Refice

Proceedings Volume 11154, 1115402 (2019) https://doi.org/10.1117/12.2533608

KEYWORDS: Synthetic aperture radar, Interferometry, Kinematics, Nonlinear optics, Computer simulations, Spatial resolution, Interferometric synthetic aperture radar, Spatial analysis, Statistical analysis, Target recognition

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Multi-temporal SAR interferometry (MTInSAR) techniques are able to derive displacement maps and displacement time series over coherent objects on the Earth, used for monitoring either geophysical ground deformation or structural instabilities. Nowadays, several datasets are available at different wavelengths, spatial resolutions, and revisit time, collectively covering long time periods (even more than 20 years). In particular, short revisit times, by improving the temporal sampling, make theoretically possible to catch high-rate and non-linear kinematics, which typically characterize warning signals like, for instance, those related to pre-failure of artificial infrastructures. However, MTInSAR algorithms generally fit the displacement signal by using a linear model, which is computationally convenient, and also, more robust than higher-order models for what concerns the errors affecting the InSAR phase. Moreover, the analysis of the MTInSAR products is often performed by only considering the mean displacement rate, computed over the monitoring period, which is the information typically displayed on the displacement maps. However, this approach suffer for two main limitations: 1) by analysing time series covering long time periods (as more and more common with the datasets available nowadays), it is more probable that nonlinear displacements occur; 2) the mean displacement rate, though useful for distinguishing between stable and unstable areas on the ground, often mask interesting nonlinear signals, useful for early warning. Therefore, in order to fully exploit the content of MTInSAR products, methods are needed for automatically identifying relevant changes along displacement time series, and, consequently, classifying the targets on the ground according to their kinematic regime. This also allows performing a more reliable ground deformation spatial analysis, by distinguishing among spatial patterns of different kinematics. Recently, approaches have been proposed to tackle this problem, which use different strategies. This work presents some general considerations and a possible new procedure based on statistical characterization of displacement time series, which allows, under certain constraints, recognising automatically different kinematic classes, and estimating the relevant parameters useful for target characterization in time. The theoretical formulation of the proposed method is introduced, then the algorithm performance is evaluated under simulated scenarios, by varying simulation parameters such as type of kinematic model, temporal sampling rate, number of observations, and signal to noise ratio. Finally, some results of the analysis of displacement time series derived by MTInSAR processing of real datasets are presented.

Proceedings Article | 18 October 2019 Presentation

Presentation

PRAT-Pseudo Random Active Transmitter: a viable alternative to compact active transponders (Conference Presentation)

Cataldo Guaragnella, Fabio Bovenga

Proceedings Volume 11154, 1115406 (2019) https://doi.org/10.1117/12.2533633

KEYWORDS: Transmitters, Transponders, Interference (communication), Synthetic aperture radar, Radar, Interferometry, Inspection, Reflectors, Distortion, Switching

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Compact active transponders have been recently proposed as a powerful and cost effective solution to monitor motion of critical geological areas. Continuous monitoring of the ground deformation can be pursued by the recourse to SAR interferometry; precise measurements can be obtained when time coherence persists over long times on the inspected zone at least in a few points (permanent scatterers). Sometimes the introduction of coherent radar targets can be a good solution to overcome the problem of phase instability, especially in vegetated and/or unurbanized areas. In the past, passive devices such as corner reflectors were used in such areas but their drawbacks due to their large size and weight and loss of time coherence due to geometric deformations and material degradation has limited their use. The availability of smaller, lighter, and less complex radar transponders is a recently presented as an alternative to passive devices, but also such compact and low cost devices can suffer some drawbacks, such as misplacement of the focused source on the ground due to the internal HW delay and distortion of many ground points due to the strong impulse response of the transponder that creates the typical cross pattern on the focused image. It would be desirable to have the phase precise information on the ground facilitated by the presence of compact active transponders with the possibility of switching on and off the visibility of the transponder on the acquired raw image. In this paper we propose a noise like pure transmitter to be used as a phase reference system, emitting a pseudo noise known signal at the background noise level. The presence of the transmitter can be extracted properly focusing the pseudo-noise transmitted sequence, stored on the sensor on-board memory. The correlation based range processing allows to focus the single transmitter, neglecting the influence of other ground returns, and the azimuthal chirp and range walk are preserved in the range focused transmitter signal, as they result dependent on the Doppler shift due to the SAR platform relative motion with respect to the ground. Once extracted the phase information of single point scatterer, the raw data image can be obtained by a standard focusing algorithm. In this case, the presence of the transmitter is not evident in the scene as it is seen as a noise source by the focusing algorithm. There are several problems to be addressed in the definition of the system but some simplification of the required hardware can be pursued. Preliminary simulation results of the proposed approach are presented in the paper.

Proceedings Article | 18 October 2019 Presentation

Presentation

Investigating slope instabilities through SAR interferometry: examples on hilly villages in Southern Italy (Conference Presentation)

Fabio Bovenga, Alberto Refice, Guido Pasquariello, Giuseppe Spilotro, Raffaele Nutricato, Davide Nitti, Maria Chiaradia, Ilenia Argentiero, Roberta Pellicani

Proceedings Volume 11154, 1115403 (2019) https://doi.org/10.1117/12.2533639

KEYWORDS: Synthetic aperture radar, Interferometry, Spatial resolution, Satellites, Interferometric synthetic aperture radar, X band, Data acquisition, Target detection, Space operations, Temporal resolution

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Multi-temporal SAR interferometry (MTInSAR), by providing both mean displacement maps and displacement time series over coherent objects on the Earth, allows analysing wide areas, identifying critical ground instabilities, and studying the phenomenon evolution in a long time-scale. This technique has been proved to be very useful for detecting and monitoring also slope instabilities. Nowadays, several satellite missions are available providing InSAR data at different wavelengths, spatial resolutions, and revisit time. The high-resolution X-Band COSMO-SkyMed constellation, acquires data with spatial resolution reaching metric values, and provides revisit times of up to a few days, leading to an increase in the density of the measurable targets, thus improving the monitoring of local scale events as well as the detection of non-linear displacements. The recent Sentinel-1 C-band mission from the European Space Agency (ESA), provides a spatial resolution comparable to the previous ESA missions, but a nominal revisit time reduced to 6 days. By offering regular global-scale coverage, better temporal resolution and freely available imagery, Sentinel-1 improves the performance of MTInSAR for ground displacement investigations. In particular, the short revisit time allows a better time series analysis by improving the temporal sampling and the chances to catch pre-failure signals characterised by high rate and non-linear behaviour signals. Moreover, it allows collecting large data stacks in a short time period, thus improving the MTInSAR performance in emergency (post-event) scenarios. These characteristics are very promising for early warning of slope failure events and monitoring subsequent displacements trends. In this work, we present the results obtained by using both COSMO-SkyMed and Sentinel-1 data for investigating the ground stability of hilly villages located in Southern Italian Apennine (Basilicata region). In the area of interest, several landslides occurred in the recent past (e.g. on Montescaglioso in 2013) and also very recently (e.g. on Pomarico in 2019), causing damages to houses, commercial buildings, and infrastructures. SAR datasets acquired by COSMO-SkyMed and Sentinel-1 from both ascending and descending orbits have been processed by using SPINUA MTInSAR algorithm, in order to exploit the potentials of these two satellite missions to investigate ground displacements related to the slope instabilities. Mean velocity maps and displacement time series have been analysed looking, in particular, to non-linear trends that are possibly related to relevant ground instabilities and, thanks to the high spatial resolution, useful in terms of early warning, in the case of rigid soil masses. Results are presented and discussed in relation to the well know events occurred in the area of interest.

Proceedings Article | 11 October 2018 Presentation

Presentation

Preliminary assessment of side-lobe mitigation techniques for proper coherent targets selection in MTInSAR applications (Conference Presentation)

Paolo Locorotondo, Andrea Guerriero, Maria Teresa Chiaradia, Davide Nitti, Raffaele Nutricato, Fabio Bovenga

Proceedings Volume 10788, 1078804 (2018) https://doi.org/10.1117/12.2325542

KEYWORDS: Synthetic aperture radar, Interferometry, Radar, Backscatter, Picosecond phenomena, Apodization, Target detection, Buildings, Detection and tracking algorithms, Nonlinear filtering

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Multi-temporal Synthetic Aperture Radar Interferometry (MTInSAR) techniques allow detecting and monitoring millimetric displacements occurring on selected targets exhibiting coherent radar backscattering properties. Because of the bandwidth limitation of Synthetic Aperture Radar images, pulse responses are significantly affected by sidelobes that should be identified and masked out before the selection of coherent targets candidates. In fact, sidelobes often exhibit a coherent backscattering behavior and can be hence erroneously identified as persistent scatterers (PS). These artifacts can be also clearly visible in the images, in case of strong scatterers embedded in a surrounding weak clutter environment, such as the echoes generated by ships or buildings. The actual large amount of Geospatial Big Data fosters the implementation of automatic tools for sidelobe detection and cancelation. A number of algorithms have been proposed in the scientific literature for sidelobe reduction in Single-Look-Complex images, ranging from apodization methods to target extraction techniques. In this study we deal in particular with the Spatially Variant Apodization (SVA), a nonlinear filter based on cosine-on-pedestal weighting functions. This approach is attractive because it is able – in theory – to achieve a total sidelobe cancelation, without degrading the original image resolution, and for its computational efficiency. However, as shown in recent works, SVA suffers from several drawbacks: (i) it modifies the statistics of speckle-dominated areas, (ii) a negative bias is introduced in the reflectivity images over homogeneous areas, (iii) the amplitude and phase of the original images could be distorted by the SVA filtering. In particular, it has been demonstrated that SVA filtering compromise the quality of MTInSAR outcomes. Therefore, recent works propose the use of SVA for just identifying and masking out the radar coordinates of the detected side-lobes in the PS candidates position map. In this work we apply SVA for proper coherent target selection in COSMO-SkyMed STRIPMAP co-polarized interferometric data takes, acquired in onshore and offshore environments. In order to highlight both advantages and limitations of this technique, we analyze the performances of SVA approaches in terms of computational efficiency and robustness to focusing artifacts (responsible of non-ideal pulse responses). In particular, we test the SVA filtering both in simulation and in complex real scenarios, where sidelobes of close strong scatterers are mixed and superimposed upon each other. We show the outcomes of MTInSAR techniques before and after the application of SVA filtering. Acknowledgments The research is partly co-funded by the Italian Space Agency in the framework of the FAST4MAP project (“Fast & Advanced SAR Techniques for Monitoring & Alerting Processes” - ASI Contract n. 2015-020-R.0). CSK® Products© of ASI delivered by ASI under a license to use.

Proceedings Article | 9 October 2018 Presentation + Paper

Presentation + Paper

Analysis of the 2018 Hualien earthquake (Taiwan) by using SAR interferometry and pixel offset techniques

Chih-Heng Lu, Fabio Bovenga, Jiun-Yee Yen, Chung-Pai Chang

Proceedings Volume 10788, 107880K (2018) https://doi.org/10.1117/12.2325838

KEYWORDS: Global Positioning System, Earthquakes, Synthetic aperture radar, Interferometry, Image resolution, Satellites, Interferometric synthetic aperture radar

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The local magnitude (ML) scale 6.22 earthquake struck eastern Taiwan on 6 February 2018. The epicenter was on the coastline near Hualien and caused a maximum shaking intensity of 7 in Hualien City, which was the most severely affected area. The crushed buildings and main surface cracks are distributed along the Milun fault, which is a oblique-slip fault. The earthquake is the largest of a sequence of events that affected the area over a period of days. In order to identify the surface deformation from Milun fault to coastal mountain range of Taiwan, we processed C-band Sentinel-1 and L-band ALOS-2 interferometric pairs acquired across the earthquake date, from both ascending and descending orbits. The Generic Mapping Tools Synthetic Aperture Radar (GMTSAR), and SNAPHU tools were used. According to the interferometric line-of-sight (LOS) displacement maps, the northwestern Milun fault moved of about 40 cm in the descending geometry, and about 0-10 cm in the ascending one, while the southwestern part of the fault moved 15-20 cm in the ascending geometry and is stable in the descending one. By combining interferometric LOS displacements derived from both ascending and descending acquisition geometries, just E-W and vertical displacement components can be derived. However, GPS and field survey results show northwards movements ranging from 50 and 70 cm over the Milun tableland, which is located on the eastern side of Milun fault. In order to provide SAR-based displacement measurements along north-south direction, we adopted the pixel-off set technique. The offsets along the azimuth direction were derived by computing the maximum of the amplitude cross-correlation of two SAR images, by using estimation windows of 128 x 128 pixel size. The 3D displacement was then computed by combining through least-square method the interferometric LOS displacements from ascending and descending acquisition geometry, and azimuth displacement component derived though pixel offset. Results indicate that, in the northern part of Milun tableland the maximum of E-W displacement reaches 60 cm, and that the whole Milun tableland moves northwards (up to about 60 cm) and upwards (up to about 40 cm). Moreover, the western side of Milun fault shows westwards movement, while Hualien city is affected by subsidence. The correlation coefficients in three directions between GPS data and 3D displacement are 0.81 (E-W), 0.89 (N-S), and 0.91 (U-D).

Proceedings Article | 3 October 2017 Paper

Paper

Investigating ground instabilities in Indonesia through SAR interferometry

Fabio Bovenga, Alberto Refice, Antonella Belmonte, Raffaele Nutricato, Davide Oscar Nitti, Maria Teresa Chiaradia, Sotirios Valkaniotis, Sofia Gkioni, Chrysanthi Kosma, Athanassis Ganas, Paolo Manunta, Elizar, Darusman , Philippe Bally

Proceedings Volume 10426, 1042602 (2017) https://doi.org/10.1117/12.2277838

KEYWORDS: Global Positioning System, Synthetic aperture radar, Interferometry, Satellite navigation systems, Interferometric synthetic aperture radar, Image segmentation, Earthquakes, Motion models

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Proceedings Article | 18 October 2016 Presentation + Paper

Presentation + Paper

Comparative analysis of recent satellite missions for multi-temporal SAR interferometry

Fabio Bovenga, Alberto Refice, Antonella Belmonte, Guido Pasquariello

Proceedings Volume 10003, 100030B (2016) https://doi.org/10.1117/12.2240490

KEYWORDS: Synthetic aperture radar, Satellites, Interferometry, Spatial resolution, Sensors, Interferometric synthetic aperture radar, Target detection, Picosecond phenomena, X band, Data modeling

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Proceedings Article | 18 October 2016 Paper

Paper

Rheticus: an automatic cloud-based geo-information service platform for territorial monitoring

Sergio Samarelli, Antonio Pio Lorusso, Luigi Agrimano, Raffaele Nutricato, Fabio Bovenga, Davide Oscar Nitti, Maria Teresa Chiaradia

Proceedings Volume 10003, 100030M (2016) https://doi.org/10.1117/12.2241285

KEYWORDS: Synthetic aperture radar, Interferometry, Buildings, Image processing, Radar, Picosecond phenomena, Information technology, 3D image processing, 3D image reconstruction, Image sensors

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Proceedings Article | 15 October 2015 Paper

Paper

On the geolocation accuracy of COSMO-SkyMed products

Davide Nitti, Raffaele Nutricato, Rino Lorusso, Nunzia Lombardi, Fabio Bovenga, Maria Bruno, Maria Chiaradia, Giovanni Milillo

Proceedings Volume 9642, 96420D (2015) https://doi.org/10.1117/12.2196870

KEYWORDS: Avalanche photodetectors, Synthetic aperture radar, Chromium, Sensors, Satellites, Calibration, Error analysis, Inspection, Electroluminescence, Reflectors

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Proceedings Article | 21 October 2014 Paper

Paper

Suitability of COSMO-SkyMed constellation for radargrammetric DEM generation

Domenico Conte, Fabio Bovenga, Alberto Refice, Davide Nitti, Raffaele Nutricato, Maria Chiaradia

Proceedings Volume 9243, 924302 (2014) https://doi.org/10.1117/12.2066846

KEYWORDS: Synthetic aperture radar, Interferometry, Image processing, Interferometric synthetic aperture radar, Error analysis, Satellites, Chromium, Data acquisition, Neodymium, Picosecond phenomena

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Proceedings Article | 21 October 2014 Paper

Paper

Corner reflectors and multi-temporal SAR inteferometry for landslide monitoring

Fabio Bovenga, Alberto Refice, Guido Pasquariello, Davide Nitti, Raffaele Nutricato

Proceedings Volume 9243, 92430I (2014) https://doi.org/10.1117/12.2066833

KEYWORDS: Chromium, Synthetic aperture radar, Landslide (networking), Picosecond phenomena, Reflectors, Interferometry, Vegetation, Sensors, Neodymium, Autoregressive models

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Proceedings Article | 21 October 2014 Paper

Paper

Exploitation of a large COSMO-SkyMed interferometric dataset

Raffaele Nutricato, Davide Nitti, Fabio Bovenga, Alberto Refice, Maria Chiaradia

Proceedings Volume 9243, 92430C (2014) https://doi.org/10.1117/12.2067156

KEYWORDS: LIDAR, Synthetic aperture radar, Picosecond phenomena, Avalanche photodetectors, Sensors, Satellites, Interferometry, Error analysis, Earthquakes, Data acquisition

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Proceedings Article | 17 October 2013 Paper

Paper

Multi-chromatic analysis of SAR images for target analysis

Fabio Bovenga, Dominique Derauw, Christian Barbier, Fabio Rana, Alberto Refice, Nicola Veneziani, Raffaele Vitulli

Proceedings Volume 8891, 889104 (2013) https://doi.org/10.1117/12.2028962

KEYWORDS: Spectral coherence, Picosecond phenomena, Synthetic aperture radar, Interferometry, Image processing, Scattering, Temporal coherence, Image analysis, Error analysis, Target detection

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Proceedings Article | 17 October 2013 Paper

Paper

C/X-band SAR interferometry applied to ground monitoring: examples and new potential

Raffaele Nutricato, Davide Nitti, Fabio Bovenga, Alberto Refice, Janusz Wasowski, Maria Chiaradia

Proceedings Volume 8891, 88910C (2013) https://doi.org/10.1117/12.2029096

KEYWORDS: Synthetic aperture radar, X band, Picosecond phenomena, Sensors, Landslides, Interferometry, Spatial resolution, Data acquisition, Interferometric synthetic aperture radar, Buildings

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Proceedings Article | 17 October 2013 Paper

Paper

DEM generation by using COSMO/SkyMed tandem pairs and weather models

Davide Nitti, Fabio Bovenga, Raffaele Nutricato, Francesca Intini, Maria Teresa Chiaradia

Proceedings Volume 8891, 88910E (2013) https://doi.org/10.1117/12.2048902

KEYWORDS: Interferometry, Synthetic aperture radar, Atmospheric modeling, Sensors, Global Positioning System, Interferometric synthetic aperture radar, Atmospheric sensing, 3D modeling, Statistical analysis, Satellites

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Proceedings Article | 21 November 2012 Paper

Paper

Multi-chromatic analysis of a single SAR image for absolute ranging

Fabio Bovenga, Leonardo Gallitelli, Davide Nitti

Proceedings Volume 8536, 853604 (2012) https://doi.org/10.1117/12.973722

KEYWORDS: Synthetic aperture radar, Image processing, Satellites, Roentgenium, Chromium, Sensors, Atmospheric modeling, Error analysis, Reflectors, Ranging

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Proceedings Article | 19 October 2012 Paper

Paper

On the use of SAR interferometry to aid navigation of UAV

Davide Nitti, Fabio Bovenga, Alberto Morea, Fabio Rana, Luciano Guerriero, Mario Greco, Gianpaolo Pinelli

Proceedings Volume 8532, 853203 (2012) https://doi.org/10.1117/12.974563

KEYWORDS: Interferometry, Synthetic aperture radar, Interferometric synthetic aperture radar, Phase interferometry, Unmanned aerial vehicles, Error analysis, Interferometers, Global Positioning System, Data modeling, Radar

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Proceedings Article | 23 October 2010 Paper

Paper

Multi-temporal DInSAR analysis with X-band high resolution SAR data: examples and potential

Fabio Bovenga, Davide Oscar Nitti, Alberto Refice, Raffaele Nutricato, Maria Teresa Chiaradia

Proceedings Volume 7829, 78290I (2010) https://doi.org/10.1117/12.866459

KEYWORDS: X band, Sensors, Synthetic aperture radar, Picosecond phenomena, Image sensors, Data modeling, Interferometry, Image processing, Remote sensing, Atmospheric modeling

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Proceedings Article | 5 October 2009 Paper

Paper

C- and X-band multi-pass InSAR analysis over alpine areas (ITALY)

Davide Oscar Nitti, Fabio Bovenga, Raffaele Nutricato, Fabio Rana, Crescenza D'Aprile, Paolo Frattini, Giovanni Crosta, Maria Teresa Chiaradia, Giovanna Ober, Laura Candela

Proceedings Volume 7477, 74771Q (2009) https://doi.org/10.1117/12.849210

KEYWORDS: Synthetic aperture radar, X band, Interferometry, Landslide (networking), Picosecond phenomena, Interferometric synthetic aperture radar, Satellites, Image processing, Spatial resolution, Sensors

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In the present work we present first results of ground deformation measurements inferred through repeat-pass Synthetic Aperture Radar (SAR) Interferometry (InSAR) in C- and X-band over an Italian Alpine area, in Lombardia region. The activity was carried out in the framework of the MORFEO (MOnitoraggio e Rischio da Frana mediante dati EO) project founded by the Italian Spatial Agency (ASI) and dedicated to landslide risk assessment. A number of areas affected by hydrogeological instabilities have been selected and studied in detail by processing both C- and X-band SAR data through SPINUA, a Persistent Scatterer like algorithm. In particular, two stacks of 30 Ascending ENVISAT SAR images (October 2004 - January 2009) and 32 Descending ENVISAT SAR images (December 2004 - January 2009) have been independently processed to ensures the detection of movements occurring along both west and east facing slopes. Moreover, further deformation measurements have been obtained by processing a set of 12 COSMO-SkyMED ascending HIMAGE interferometric acquisitions (Satellite CSKS1; Beam HI-03; POL: HH; Incidence Angle: 29°) provided by ASI. After a proper tuning of the interferometric algorithmic solutions, even with very high normal baselines, we are able to appreciate the potentials of X-band interferometry. Although the number of COSMO-SkyMED acquisitions is quite limited, spanning a period of only 10 months (August 2008 - June 2009), SPINUA was capable to retrieve preliminary ground displacement patterns that are in good agreement with those previously estimated in C-band. Quite impressive is to realize that, because of the tenfold improved resolution of X-band images, multi-temporal InSAR techniques may be successfully applied for the estimation of the displacement maps with a number of acquisitions much lower than in C-band. InSAR-derived displacements provided on areas of hydrogeological interest are going to be validated in the framework of MORFEO project by the geological partnership thanks to the availability of ground truths. In the present work, we present the results obtained on the towns of Garzeno, Catasco and Germasino which are affected by landslide phenomena. We provide a first validation by comparing the deformation maps derived from ENVISAT C-band data, from COSMO-SkyMED X-band data as well as from ERS and RADARSAT C-band data freely available on the GeoIFFI web-catalogue.

Proceedings Article | 29 September 2009 Paper

Paper

TerraSAR-X InSAR multipass analysis on Venice (Italy)

D. Nitti, R. Nutricato, F. Bovenga, A. Refice, M. Chiaradia, L. Guerriero

Proceedings Volume 7477, 74771I (2009) https://doi.org/10.1117/12.832047

KEYWORDS: Synthetic aperture radar, Interferometry, Interferometric synthetic aperture radar, X band, Sensors, Picosecond phenomena, Stanford Linear Collider, Image processing, Satellites, Spatial resolution

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The TerraSAR-X (copyright) mission, launched in 2007, carries a new X-band Synthetic Aperture Radar (SAR) sensor optimally suited for SAR interferometry (InSAR), thus allowing very promising application of InSAR techniques for the risk assessment on areas with hydrogeological instability and especially for multi-temporal analysis, such as Persistent Scatterer Interferometry (PSI) techniques, originally developed at Politecnico di Milano. The SPINUA (Stable Point INterferometry over Unurbanised Areas) technique is a PSI processing methodology which has originally been developed with the aim of detection and monitoring of coherent PS targets in non or scarcely-urbanized areas. The main goal of the present work is to describe successful applications of the SPINUA PSI technique in processing X-band data. Venice has been selected as test site since it is in favorable settings for PSI investigations (urban area containing many potential coherent targets such as buildings) and in view of the availability of a long temporal series of TerraSAR-X stripmap acquisitions (27 scenes in all). The Venice Lagoon is affected by land sinking phenomena, whose origins are both natural and man-induced. The subsidence of Venice has been intensively studied for decades by determining land displacements through traditional monitoring techniques (leveling and GPS) and, recently, by processing stacks of ERS/ENVISAT SAR data. The present work is focused on an independent assessment of application of PSI techniques to TerraSAR-X stripmap data for monitoring the stability of the Venice area. Thanks to its orbital repeat cycle of only 11 days, less than a third of ERS/ENVISAT C-band missions, the maximum displacement rate that can be unambiguously detected along the Line-of-Sight (LOS) with TerraSAR-X SAR data through PSI techniques is expected to be about twice the corresponding value of ESA C-band missions, being directly proportional to the sensor wavelength and inversely proportional to the revisit time. When monitoring displacement phenomena which are known to be within the C-band rate limits, the increased repeat cycle of TerraSAR-X offers the opportunity to decimate the stack of TerraSAR-X data, e.g. by doubling the temporal baseline between subsequent acquisitions. This strategy can be adopted for reducing both economic and computational processing costs. In the present work, the displacement rate maps obtained through SPINUA with and without decimation of the number of Single Look Complex (SLC) acquisitions are compared. In particular, it is shown that with high spatial resolution SAR data, reliable displacement maps could be estimated through PSI techniques with a number of SLCs much lower than in C-band.

Proceedings Article | 10 October 2008 Paper

Paper

Evaluation of DEM-assisted SAR coregistration

D. Nitti, R. Hanssen, A. Refice, F. Bovenga, G. Milillo, R. Nutricato

Proceedings Volume 7109, 710919 (2008) https://doi.org/10.1117/12.802767

KEYWORDS: Synthetic aperture radar, Satellites, Interferometry, X band, Sensors, Spherical lenses, Picosecond phenomena, Error analysis, Radar, Stanford Linear Collider

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Image alignment is without doubt the most crucial step in SAR Interferometry. Interferogram formation requires images to be coregistered with an accuracy of better than 1/8 pixel to avoid significant loss of phase coherence. Conventional interferometric precise coregistration methods for full-resolution SAR data (Single-Look Complex imagery, or SLC) are based on the cross-correlation of the SLC data, either in the original complex form or as squared amplitudes. Offset vectors in slant range and azimuth directions are computed on a large number of windows, according to the estimated correlation peaks. Then, a two-dimensional polynomial of a certain degree is usually chosen as warp function and the polynomial parameters are estimated through LMS fit from the shifts measured on the image windows. In case of rough topography and long baselines, the polynomial approximation for the warp function becomes inaccurate, leading to local misregistrations. Moreover, these effects increase with the spatial resolution and then with the sampling frequency of the sensor, as first results on TerraSAR-X interferometry confirm. An improved, DEM-assisted image coregistration procedure can be adopted for providing higher-order prediction of the offset vectors. Instead of estimating the shifts on a limited number of patches and using a polynomial approximation for the transformation, this approach computes pixel by pixel the correspondence between master and slave by using the orbital data and a reference DEM. This study assesses the performance of this approach with respect to the standard procedure. In particular, both analytical relationships and simulations will evaluate the impact of the finite vertical accuracy of the DEM on the final coregistration precision for different radar postings and relative positions of satellites. The two approaches are compared by processing real data at different carrier frequencies and using the interferometric coherence as quality figure.

Proceedings Article | 7 March 2003 Paper

Paper

Phase unwrapping by means of scaling information and global optimization algorithms

Fabio Bovenga, Alberto Refice, Sebastiano Stramaglia, Domenico Conte

Proceedings Volume 4883, (2003) https://doi.org/10.1117/12.463178

KEYWORDS: Interferometry, Optimization (mathematics), Synthetic aperture radar, Stochastic processes, Phase measurement, Data modeling, Interferometric synthetic aperture radar, Phase interferometry, Algorithms, Computer simulations

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Showing 5 of 28 publications

Proceedings Volume Editor (7)

SPIE Conference Volume | 4 December 2024

Microwave Remote Sensing: Data Processing and Applications III

SPIE Conference Volume | 7 November 2023

Microwave Remote Sensing: Data Processing and Applications II

SPIE Conference Volume | 4 November 2022

Image and Signal Processing for Remote Sensing XXVIII

SPIE Conference Volume | 18 October 2021

Microwave Remote Sensing: Data Processing and Applications

SPIE Conference Volume | 9 October 2020

Image and Signal Processing for Remote Sensing XXVI

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Microwave Remote Sensing: Data Processing and Applications IV

15 September 2025 | Madrid, Spain

Microwave Remote Sensing: Data Processing and Applications III

18 September 2024 | Edinburgh, United Kingdom

Microwave Remote Sensing: Data Processing and Applications II

6 September 2023 | Amsterdam, Netherlands

Image and Signal Processing for Remote Sensing XXVIII

5 September 2022 | Berlin, Germany

Microwave Remote Sensing: Data Processing and Applications

13 September 2021 | Online Only, Spain

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