Visualization of and Software for Omnibus Test Based Change Detected in a Time Series of Polarimetric SAR Data

Based on an omnibus likelihood ratio test statistic for the equality of several variance-covariance matrices following the complex Wishart distribution and a factorization of this test statistic with associated p-values, change analysis in a time series of multilook polarimetric synthetic aperture radar data in the covariance matrix representation is carried out. The omnibus test statistic and its factorization detect if and when change occurs. Using airborne EMISAR and spaceborne RADARSAT-2 data, this article focuses on change detection based on the p-values, on visualization of change at pixel as well as segment level, and on computer software

Deep learning in remote sensing: a review

Standing at the paradigm shift towards data-intensive science, machine learning techniques are becoming increasingly important. In particular, as a major breakthrough in the field, deep learning has proven as an extremely powerful tool in many fields. Shall we embrace deep learning as the key to all? Or, should we resist a 'black-box' solution? There are controversial opinions in the remote sensing community. In this article, we analyze the challenges of using deep learning for remote sensing data analysis, review the recent advances, and provide resources to make deep learning in remote sensing ridiculously simple to start with. More importantly, we advocate remote sensing scientists to bring their expertise into deep learning, and use it as an implicit general model to tackle unprecedented large-scale influential challenges, such as climate change and urbanization.Comment: Accepted for publication IEEE Geoscience and Remote Sensing Magazin

Trace Coherence: A New Operator for Polarimetric and Interferometric SAR images

Quadratic forms play an important role in the development of several Polarimetric and Interferometric Synthetic Aperture Radar (Pol-InSAR) methodologies, which are very powerful tools for Earth Observation. This work investigates integrals of Pol-InSAR operators based on quadratic forms, with special interest for the Pol-InSAR coherence. A new operator is introduced, namely Trace Coherence, that provides an approximation for the center of mass of the Coherence Region (CoRe). The latter is the locus of points on the polar plot containing all the possible coherence values. Such center of mass can be calculated as the integral of Pol-InSAR coherences over the scattering mechanisms. The Trace Coherence provides a synthetic information regarding the partial target as one single entity. Therefore, it provides a representation, which is not dependent on the selection of one specific polarization channel. It may find application in change detection (e.g. Coherent Change Detection and differential DEM), classification (e.g. building structure parameters) and modeling (e.g. for the retrieval of forest height). In calculating the integral of the Pol-InSAR coherences, an approximate Trace Coherence expression is derived and shown to improve the calculation speed by several orders of magnitude. The Trace Coherence approximation is investigated using Monte Carlo simulations and validated ESA (DLR) L-band quad-polarimetric data acquired during the AGRISAR 2006 campaign. The result of the analysis using simulated and real data is that the average error in approximating the integral of the Coherence Region is 0.025 in magnitude and 3° in phase (in scenarios with sufficiently high coherence)

A change detector based on an optimization with polarimetric SAR imagery

The possibility to detect changes in land cover with remote sensing is particularly valuable considering the current availability of long time series of data. SAR can play an important role in this context, since it can acquire complete time series without limitations of cloud cover. Additionally, polarimetry has the potential to improve significantly the detection capability allowing the discrimination between different polarimetric targets. This paper is focused on developing two new methodologies for testing the stability of observed targets (i.e. Equi-Scattering Mechanisms hypothesis) and change detection. Both the algorithms adopt a Lagrange optimization, which can be performed with two eigen-problems. Interestingly, the two optimizations share the same eigenvectors. Three statistical tests are proposed to set the threshold for the change detector. Two of them are mostly aimed at point targets and one is more suited for distributed targets. All the algorithms and procedures developed in this paper are tested on two different quad-polarimetric dataset acquired by the E-SAR DLR system in L-band (SARTOM 2006 and AGRISAR 2006 campaigns). The dataset are accompanied by ground surveys. The detectors are able to identify targets and areas with validated changes or showing clear differences in the images. The theoretical pdf exploited to model the optimum ratio fits adequately the data and therefore has been used for the statistical tests. Regarding the output of the tests, two of them provided good results, while one needs more care and adjustments

A Depolarization Ratio Anomaly Detector to identify icebergs in sea ice using dual-polarization SAR images

Icebergs represent hazards to maritime traffic and offshore operations. Satellite Synthetic Aperture Radar (SAR) is very valuable for the observation of polar regions and extensive work was already carried out on detection and tracking of large icebergs. However, the identification of small icebergs is still challenging especially when these are embedded in sea ice. In this work, a new detector is proposed based on incoherent dual-polarization SAR images. The algorithm considers the limited extension of small icebergs, which are supposed to have a stronger cross polarization and higher cross- over co-polarization ratio compared to the surrounding sea or sea ice background. The new detector is tested with two satellite systems. Firstly, RADARSAT-2 quad-polarimetric images are analyzed to evaluate the effects of high resolution data. Subsequently a more exhaustive analysis is carried out using dual-polarization ground detected Sentinel-1a Extra Wide swath images acquired over the time span of two months. The test areas are on the East Coast of Greenland, where several icebergs have been observed. A quantitative analysis and a comparison with a detector using only the cross polarization channel is carried out exploiting grounded icebergs as test targets. The proposed methodology improves the contrast between icebergs and sea ice clutter by up to 75 times. This returns an improved probability of detection

Validating a notch filter for detection of targets at sea with ALOS-PALSAR data: Tokyo Bay

The surveillance of maritime areas is a major topic for security aimed at fighting issues as illegal trafficking, illegal fishing, piracy, etc. In this context, Synthetic Aperture Radar (SAR) has proven to be particularly beneficial due to its all-weather and night time acquisition capabilities. Moreover, the recent generation of satellites can provide high quality images with high resolution and polarimetric capabilities. This paper is devoted to the validation of a recently developed ship detector, the Geometrical Perturbations Polarimetric Notch Filter (GP-PNF) exploiting L-band polarimetric data. The algorithm is able to isolate the return coming from the sea background and trigger a detection if a target with different polarimetric behavior is present. Moreover, the algorithm is adaptive and is able to account for changes of sea clutter both in polarimetry and intensity. In this work, the GP-PNF is tested and validated for the first time ever with L-band data, exploiting one ALOS-PALSAR quad-pol dataset acquired on the 9th of October 2008 in Tokyo Bay. One of the motivations of the analysis is also the attempt of testing the suitability of GP-PNF to be used with the new generations of L-band satellites (e.g. ALOS-2). The acquisitions are accompanied by a ground truth performed with a video survey. A comparison with two other detectors is presented, one exploiting a single polarimetric channel and the other considering quad-polarimetric data. Moreover, a test exploiting dual-polarimetric modes (HH/VV and HH/HV) is performed. The GP-PNF shows the capability to detect targets presenting pixel intensity smaller than the surrounding sea clutter in some polarimetric channels. Finally, the quad-polarimetric GP-PNF outperformed in some situations the other two detectors