Remote sensing for building inventory updates in disaster management

摘要

Building inventory is a core input to risk and loss evaluation models, and as such, plays a key role in providing decision support for the disaster management community. This paper describes the extraction of detailed building inventory data, using optical remote sensing data within the new MIHEA (Mono Image Height Extraction Algorithm) tool. MIHEA is developed to extract building inventory information such as height, shape and square footage from single high-resolution remotely sensed images. Its pilot implementation in conjunction with QuickBird satellite imagery for London, United Kingdom and Long Beach, USA is described. A methodological protocol is proposed for integrating remote sensing-derived data into loss estimation tools, such as HAZUS® and INLET, to replace default datasets which offer limited accuracy at a census tract scale. The study suggests that when used in conjunction with MIHEA, remote sensing is a valuable source of building inventory information for locations around the World. Preliminary results for the integration of derived data into loss estimation tools are expected in Summer 2006.