Remote sensing technology for postdisaster building damage assessment

Abstract Global environmental changes have increased the frequency of natural disasters and the demand for rapid postdisaster mapping. In this regard, remote sensing (RS) is a leading technology because it provides consistent near-real-time images. In this chapter, we studied different disasters, Joplin MO Tornado (2011), Hurricane Harvey (2017), and Hurricane Michael (2018), using satellite sensors such as Landsat 5 and Sentinel 2 and airborne imagery acquired within the National Agriculture Imagery Program (NAIP) and by the National Oceanic and Atmospheric Administration (NOAA). We compared different RS methods, such as pixel- and object-based classification techniques and spectral/spatial feature analysis to compare the potential of vertical and oblique images to produce regional- and building-level damage maps. We illustrated several large-scale and zoomed scenes for visual interpretation and the corresponding assessment analysis. Finally, the further development of RS technology and its effect on the development of the algorithm are discussed.