TOWARDS A SEMANTIC INTERPRETATION OF URBAN AREAS WITH AIRBORNE SYNTHETIC APERTURE RADAR TOMOGRAPHY

In this paper, we introduce a method to detect and reconstruct building parts from tomographic Synthetic Aperture Radar (SAR) airborne data. Our approach extends recent works in two ways: first, the radiometric information is used to guide the extraction of geometric primitives. Second, building facades and roofs are extracted thanks to geometric classification rules. We demonstrate our method on a 3 image L-Band airborne dataset over the city of Dresden, Germany. Experiments show how our technique allows to use the complementarity between the radiometric image and the tomographic point cloud to extract buildings parts in challenging situations

COMPLEMENTARITY OF SAR POLARIMETRY AND TOMOGRAPHY FOR BUILDING DETECTION AND CHARACTERIZATION

In this paper we propose to study the potential of jointly using polarimetric and tomographic SAR data to recognize and localize buildings in complex scenarios. We present extraction methods for both polarimetric and tomographic features. One the one hand, we propose to use the polarimetric bilateral filter that has proved to be a powerful tool to retrieve the polarimetric covariance matrix while reducing speckle and preserving edges. Thus, polarimetric decompositions can be used for physical interpretation. On the other hand, the TomoSNI and TomoSeed algorithms allow to respectively extract interest points and segment geometric primitives in 3D point clouds obtained with tomographic focusing methods. We show how the output of such algorithms could be combined in order to allow the extraction of buildings. We also analyze different issues related to complex scenarios that may impede a correct detection and discuss some possible solutions

Constraining GPR data inversion using hydrodynamic laws for noninvasive soil hydraulic and electric property determination

We constrain full-wave inversion of time-lapse radar data using hydrodynamic modeling to simultaneously identify the shallow subsurface hydraulic properties and continuous vertical electric profiles. Radar data are acquired in the frequency domain using a vector network analyzer combined with an off-ground monostatic antenna. This permits to accurately Alter antenna effects and to derive Green functions from which the inversion is initiated. In order to demonstrate that enough information is contained in the radar data so as to ensure unique estimates, hydrodynamic events were simulated for three different textured soils, namely, coarse, medium, and fine. The corresponding time-lapse radar data were subsequently computed and inverted to find back key soil hydraulic parameters, i.e., a, n, and Ks in Mualem-van Genuchten's model. For the three scenarios considered, the three hydraulic parameters were exactly retrieved, and hence, the corresponding time-dependent electric profiles as well. Provided that the soil-specific relations between the soil water content and its electric properties and the hydrodynamic initial and boundary conditions are known, the proposed method appears to be promising for proximal mapping of the shallow subsurface hydraulic properties and monitoring of the water dynamics at the field scale.Anglai

APPLICATION OF A NEW POLARIMETRIC FILTER TO RADARSAT-2 DATA OF DECEPTION ISLAND (ANTARCTIC PENINSULA REGION) FOR SURFACE COVER CHARACTERIZATION

In this paper, we describe a new approach to analyse and quantify land surface covers on Deception Island, a volcanic island located in the Northern Antarctic Peninsula region by means of fully polarimetric RADARSAT-2 (C-Band) SAR image. Data have been filtered by a new polarimetric speckle filter (PolSAR-BLF) that is based on the bilateral filter. This filter is locally adapted to the spatial structure of the image by relying on pixel similarities in both the spatial and the radiometric domains. Thereafter different polarimetric features have been extracted and selected before being geocoded. These polarimetric parameters serve as a basis for a supervised classification using the Support Vector Machine (SVM) classifier. Finally, a map of landform is generated based on the result of the SVM results

Ground movement estimation in Yakutia using Dual-Pol InSAR TerraSAR-X data

International audienc

Following deformation over permafrost environment during a whole freeze/thaw cycle using Pol-D-InSAR

International audienc