Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Remote Sensing Based Methodology for the Quick Update of Population Exposed to Natural Hazards

Version 1 : Received: 20 October 2020 / Approved: 21 October 2020 / Online: 21 October 2020 (09:35:17 CEST)

A peer-reviewed article of this Preprint also exists.

Boni, G.; De Angeli, S.; Taramasso, A.C.; Roth, G. Remote Sensing-Based Methodology for the Quick Update of the Assessment of the Population Exposed to Natural Hazards. Remote Sens. 2020, 12, 3943. Boni, G.; De Angeli, S.; Taramasso, A.C.; Roth, G. Remote Sensing-Based Methodology for the Quick Update of the Assessment of the Population Exposed to Natural Hazards. Remote Sens. 2020, 12, 3943.

Abstract

The assessment of the number of people exposed to natural hazards, especially in countries with strong urban growth, is difficult to be updated at the same rate as land use develops. This paper presents a remote sensing based procedure for quick updating the assessment of the population exposed to natural hazards. A relationship between satellite nightlights intensity and urbanization density from global available cartography is first assessed when all data are available. This can be used to extrapolate urbanization data at different time steps, updating exposure each time new nightlights intensity maps are available. As reliability test for the proposed methodology, the number of people exposed to riverine flood in Italy is assessed, deriving a probabilistic relationship between DMSP nightlights intensity and urbanization density from GUF database for the year 2011. People exposed to riverine flood are assessed crossing the population distributed on the derived urbanization density with flood hazard zones provided by ISPRA. The validation on reliable exposures derived from ISTAT data shows good agreement. The possibility to update exposure maps with higher refresh rate makes this approach particularly suitable for applications in developing countries, where exposure may change at sub-yearly scale.

Keywords

exposure; urban development; nightlights intensity; population distribution; natural hazards; remote sensing

Subject

Environmental and Earth Sciences, Atmospheric Science and Meteorology

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