Abstract
Abstract. With improved sensor resolution and advanced multi-pass interferometric techniques such as SAR tomographic inversion (TomoSAR), it is now possible to reconstruct both shape and motion of urban infrastructures. These sophisticated techniques not only opens up new possibilities to monitor and visualize the dynamics of urban infrastructure in very high level of details but also allows us to take a step further towards generation of 4D (space-time) or even higher dimensional dynamic city models that can potentially incorporate temporal (motion) behaviour along with the 3D information. Motivated by these chances, this paper presents a post processing approach that systematically allows automatic reconstruction of building façades from 4D point cloud generated from tomographic SAR processing and put the particular focus on robust reconstruction of large areas. The approach is modular and consists of extracting facade points via point density estimation procedure based on directional window approach. Segmentation of facades into individual segments is then carried out using an unsupervised clustering procedure combining both the density-based clustering and the mean-shift algorithm. Subsequently, points of individual facade segments are identified as belonging to flat or curved surface and general 1st and 2nd order polynomials are used to model the facade geometry. Finally, intersection points of the adjacent façades describing the vertex points are determined to complete the reconstruction process. The proposed approach is illustrated and validated by examples using TomoSAR point clouds over the city of Las Vegas generated from a stack of TerraSARX high resolution spotlight images.
Highlights
Development of automatic methods for reconstruction of buildings and other urban objects from synthetic aperture radar (SAR) images is of great practical interest for many remote sensing applications due to their independence from solar illumination and all weather capability
Very high resolution (VHR) SAR images acquired from spaceborne sensors are capable of monitoring greater spatial area at significantly reduced costs
Interferometric SAR acquisitions (InSAR) are acquired which implies imaging area of interest more than once with different viewing configurations. (Gamba, 2000) proposed an approach that uses such interferometric SAR acquisitions (InSAR) configuration to detect and extract buildings based on a modified machine vision approach. (Thiele, 2007) presented a model based approach that employed orthogonal InSAR images to detect and reconstruct building footprints
Summary
Development of automatic methods for reconstruction of buildings and other urban objects from synthetic aperture radar (SAR) images is of great practical interest for many remote sensing applications due to their independence from solar illumination and all weather capability. Very high resolution (VHR) SAR images acquired from spaceborne sensors are capable of monitoring greater spatial area at significantly reduced costs. These benefits have motivated many researchers and several methods have been developed that use SAR imagery for detection and reconstruction of manmade objects in particular buildings. (Quartulli, 2004) and (Ferro, 2009) present approaches for building reconstruction based on single-aspect SAR images. (Thiele, 2007) presented a model based approach that employed orthogonal InSAR images to detect and reconstruct building footprints. An automatic approach based on modeling building objects as cuboids using multi-aspect polarimetric SAR images is presented in (Xu, 2007). Complex building structures and high variability of objects appearing in the images make automatic building detection and reconstruction a difficult problem
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
