Recent Advances on 2D and 3D Change Detection in Urban Environments from Remote Sensing Data - Computational Approaches for Urban Environments - page 250

Fig. 10.6 The detected building in 3D after the application of a supervised SVM classifier and
post-processing procedures on the high spatial resolution Pleiades data ( top ). Scene buildings in
3D as extracted from the ground truth data ( bottom )
The aim was to focus our presentation on giving an account of recent approaches
that have not been covered in previous surveys, and therefore, recent advances
during the last 6 years have been reviewed. In addition, the change detection
approaches were classified according to the monitoring targets (Table 10.1 )and
according to the remote sensing data that were design to process (Table 10.3 ).
The unsupervised and supervised methods were classified according to their core
algorithm that they were, mainly, based on (Table 10.4 ). Moreover, a summary
of the currently available satellite remote sensing sensors, which were employed
in recent studies, and their major specifications and cost are given in Table 10.2 .
Recent approaches focusing on 2D and 3D building extraction and modeling are
given in Table 10.5 , providing important computational frameworks which can be
directly or partially adopted for addressing more efficiently the change detection
problem. In particular, in a similar way with the change detection approaches that