Deep Learning for InSAR Phase Filtering: An Optimized Framework for Phase Unwrapping

Interferometric Synthetic Aperture Radar (InSAR) data processing applications, such as deformation monitoring and topographic mapping, require an interferometric phase filtering step. Indeed, the filtering quality significantly impacts the deformation and terrain height estimation accuracy. However, the existing classical and deep learning-based phase filtering methods provide artefacts in the filtered areas where a large amount of noise prevents retrieving the original signal. In this way, we can no longer distinguish the underlying informative signal for the next processing step. This paper proposes a deep convolutional neural network filtering method, developing a novel learning strategy to preserve the initial phase noise input into these crucial areas. Thanks to the encoder–decoder powerful phase feature extraction ability, the network can predict an accurate coherence and filtered interferometric phase, ensuring reliable final results. Furthermore, we also address a novel Synthetic Aperture Radar (SAR) interferograms simulation strategy that, using initial parameters estimated from real SAR images, considers physical behaviors typical of a real acquisition. According to the results achieved on simulated and real InSAR data, the proposed filtering method significantly outperforms the classical and deep learning-based ones

Higher-Order Permanent Scatterers Analysis

The permanent scatterers (PS) technique is a multi-interferogram algorithm for DInSAR analyses developed in the late nineties to overcome the difficulties related to the conventional approach, namely, phase decorrelation and atmospheric effects. The successful application of this technology to many geophysical studies is now pushing toward further improvements and optimizations. A possible strategy to increase the number of radar targets that can be exploited for surface deformation monitoring is the adoption of parametric super-resolution algorithms that can cope with multiple scattering centres within the same resolution cell. In fact, since a PS is usually modelled as a single pointwise scatterer dominating the background clutter, radar targets having cross-range dimension exceeding a few meters can be lost (at least in C-band datasets), due to geometrical decorrelation phenomena induced in the high normal baseline interferograms of the dataset. In this paper, the mathematical framework related to higher-order SAR interferometry is presented as well as preliminary results obtained on simulated and real data. It is shown how the PS density can be increased at the price of a higher computational load

shoreline detection capability of cosmo skymed and high resolution multispectral images

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Automatic Generation of Semantic Parts for Face Image Synthesis

Semantic image synthesis (SIS) refers to the problem of generating realistic imagery given a semantic segmentation mask that defines the spatial layout of object classes. Most of the approaches in the literature, other than the quality of the generated images, put effort in finding solutions to increase the generation diversity in terms of style i.e. texture. However, they all neglect a different feature, which is the possibility of manipulating the layout provided by the mask. Currently, the only way to do so is manually by means of graphical users interfaces. In this paper, we describe a network architecture to address the problem of automatically manipulating or generating the shape of object classes in semantic segmentation masks, with specific focus on human faces. Our proposed model allows embedding the mask class-wise into a latent space where each class embedding can be independently edited. Then, a bi-directional LSTM block and a convolutional decoder output a new, locally manipulated mask. We report quantitative and qualitative results on the CelebMask-HQ dataset, which show our model can both faithfully reconstruct and modify a segmentation mask at the class level. Also, we show our model can be put before a SIS generator, opening the way to a fully automatic generation control of both shape and texture. Code available at https://github.com/TFonta/Semantic-VAE.Comment: Preprint, accepted for publication at ICIAP 202

comparison of exhaust emissions at intersections under traffic signal versus roundabout control using an instrumented vehicle

Abstract The traditional approach to the comparison of alternative types of road intersection control has focused mainly on efficiency and safety. In recent years, the increasing importance of air pollution produced by vehicular traffic has suggested that environmental considerations should be added to the above aspects as a criterion for intersection design. This study describes a before-and-after analysis conducted on a road intersection where a roundabout has replaced a traffic signal. Using a Portable Emission Measurement Systems (PEMS) installed on a test car, the instantaneous emissions of CO2, NOX and CO have been measured over repeated trips along a designated route. A total of 396 trips have been carried out in different traffic conditions and in opposite directions along the chosen route. Using statistical methods the existence of significant differences in emissions attributable to the type of intersection control has been investigated based on the experimental data. The results indicate that replacing the traffic signal with the roundabout tends to reduce CO2 emissions, even if the differences are not always statistically significant; on the contrary, the signalized intersection performs better in terms of NOX emissions. Finally, results are less clear for CO emissions, and differences are statistically non significant in most cases

Bio adipic acid production from sodium muconate and muconic acid: a comparison of two systems

sodium muconate and trans,trans‐muconic acid were heterogeneously hydrogenated to adipic acid, a strategic intermediate for the industry of polyamides and high performance polymers. Hydrogen pressure, metal to substrate ratio, substrate concentration and reaction temperature were varied to study the effect of these parameters on the reaction products. Commercial Pd/AC 5 % was used as catalyst and characterized by TEM, BET and XPS analyses. The results revealed that temperature is the parameter which mainly affect the reaction. Moreover, hydrogenation of trans,trans‐muconic acid is faster than sodium muconate reduction. Full conversion and full yield toward adipic acid was obtained using trans,trans‐muconic acid as substrate after 60 min at the following operating conditions: temperature=70 °C, metal/substrate=1/200 (molPd/molsub), trans,trans‐muconic acid concentration=1.42E‐02M and hydrogen pressure=1 bar. In all reactions (2E)hexenedioic acid was detected as main intermediate

Monitoring and understanding crustal deformation by means of GPS and InSAR data

Monitoring deformation of the Earth’s crust by using data acquired by both the GNSS and SAR techniques allows describing crustal movements with high spatial and temporal resolution. This is a key contribution for achieving a deeper and better insight of geodynamic processes. Combination of the two techniques provides a very powerful means, however, before combing the different data sets it is important to properly understand their respective contribution. For this purpose, strictly simultaneous and long time series would be necessary. This is not, in general, a common case due to the relatively long SAR satellites revisit time. A positive exception is represented by the data set of COSMO SKYMed (CSK) images made available for this study by the Italian Space Agency (ASI). The flyover area encompass the city of Bologna and the smaller nearby town of Medicina where permanent GPS stations are operational. At the times of the CSK flyovers, we compared the GPS and SAR Up and East coordinates of a few stations as well as differential tropospheric delays derived by both techniques. The GPS time series were carefully screened and corrected for the presence of discontinuities by adopting a dedicated statistical procedure. The comparisons of both the estimated deformation and the tropospheric delays are encouraging and highlight the need for having available a more evenly sampled SAR data set

on road measurement of co2 vehicle emissions under alternative forms of intersection control

Abstract The environmental impact of road intersection operations, and in particular of alternative types of traffic control, has received increasing attention in recent years as a factor to be considered in addition to efficiency and safety. The purpose of this study is to provide experimental evidence about this issue based on direct measurement of CO2 emissions produced by a vehicle under traffic signal versus roundabout control. Carbon Dioxide was chosen as specific target of the analysis because of its important contribution to the "greenhouse effect". Using data collected with a Portable Emission Measurement System (PEMS) installed on a test car, a before-and-after analysis was conducted on an intersection where a roundabout has replaced a traffic signal. A total of 396 trips were carried out by two drivers in different traffic conditions and in opposite directions along a designated route. Using statistical methods, the existence of significant differences in CO2 emissions in relation to the type of intersection control was investigated based on the collected data, also considering the effect of other explanatory variables and focusing in particular on peak traffic conditions. More precisely, the effect of the type of control has been characterized using descriptive statistics and permutation tests applied to the entire data set, while an analysis based on binary logistic regression has been performed with specific reference to trips carried out under peak traffic conditions. The results of these analyses support the conclusion that converting a signal-controlled intersection to a roundabout may lead to a decrease in CO2 emissions