Assessing Urban Vulnerability to Flooding: A Framework to Measure Resilience Using Remote Sensing Approaches

Mercio Cerbaro, Stephen Morse, Richard Murphy, Sarah Middlemiss and Dimitrios Michelakis
Additional contact information
Mercio Cerbaro: Centre for Environment & Sustainability, University of Surrey, Guildford GU2 7XH, UK
Stephen Morse: Centre for Environment & Sustainability, University of Surrey, Guildford GU2 7XH, UK
Richard Murphy: Centre for Environment & Sustainability, University of Surrey, Guildford GU2 7XH, UK
Sarah Middlemiss: Ecometrica Limited, Orchard Brae House, 30 Queensferry Road, Edinburgh EH4 2HS, UK
Dimitrios Michelakis: Ecometrica Limited, Orchard Brae House, 30 Queensferry Road, Edinburgh EH4 2HS, UK

Sustainability, 2022, vol. 14, issue 4, 1-22

Abstract: Assessing and measuring urban vulnerability resilience is a challenging task if the right type of information is not readily available. In this context, remote sensing and Earth Observation (EO) approaches can help to monitor damages and local conditions before and after extreme weather events, such as flooding. Recently, the increasing availability of Google Street View (GSV) coverage offers additional potential ways to assess the vulnerability and resilience to such events. GSV is available at no cost, is easy to use, and is available for an increasing number of locations. This exploratory research focuses on the use of GSV and EO data to assess exposure, sensitivity, and adaptation to flooding in urban areas in the cities of Belem and Rio Branco in the Amazon region of Brazil. We present a Visual Indicator Framework for Resilience (VIFOR) to measure 45 indicators for these characteristics in 1 km 2 sample areas in poor and richer districts in the two cities. The aim was to assess critically the extent to which GSV-derived information could be reliable in measuring the proposed indicators and how this new methodology could be used to measure vulnerability and resilience where official census data and statistics are not readily available. Our results show that variation in vulnerability and resilience between the rich and poor areas in both cities could be demonstrated through calibration of the chosen indicators using GSV-derived data, suggesting that this is a useful, complementary and cost-effective addition to census data and/or recent high resolution EO data. Furthermore, the GSV-linked approach used here may assist users who lack the technical skills to process raw EO data into usable information. The ready availability of insights on the vulnerability and resilience of diverse urban areas by straightforward remote sensing methods such as those developed here with GSV can provide valuable evidence for decisions on critical infrastructure investments in areas with low capacity to cope with flooding.

Keywords: vulnerability; flooding; remote sensing; Earth Observation (EO); Google Street View (GSV); climate change (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/2071-1050/14/4/2276/pdf (application/pdf)
https://www.mdpi.com/2071-1050/14/4/2276/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:14:y:2022:i:4:p:2276-:d:751581

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().