Critical Data Source; Tool or Even Infrastructure? Challenges of Geographic Information Systems and Remote Sensing for Disaster Risk Governance

Disaster risk information is spatial in nature and Geographic Information Systems (GIS) and Remote Sensing (RS) play an important key role by the services they provide to society. In this context, to risk management and governance, in general, and to civil protection, specifically (termed differentl...

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Bibliographic Details
Main Authors: Alexander Fekete, Katerina Tzavella, Iuliana Armas, Jane Binner, Matthias Garschagen, Carlo Giupponi, Vahid Mojtahed, Marcello Pettita, Stefan Schneiderbauer, Damien Serre
Format: Article
Language:English
Published: MDPI AG 2015-09-01
Series:ISPRS International Journal of Geo-Information
Subjects:
Online Access:http://www.mdpi.com/2220-9964/4/4/1848
Description
Summary:Disaster risk information is spatial in nature and Geographic Information Systems (GIS) and Remote Sensing (RS) play an important key role by the services they provide to society. In this context, to risk management and governance, in general, and to civil protection, specifically (termed differently in many countries, and includes, for instance: civil contingencies in the UK, homeland security in the USA, disaster risk reduction at the UN level). The main impetus of this article is to summarize key contributions and challenges in utilizing and accepting GIS and RS methods and data for disaster risk governance, which includes public bodies, but also risk managers in industry and practitioners in search and rescue organizations. The article analyzes certain method developments, such as vulnerability indicators, crowdsourcing, and emerging concepts, such as Volunteered Geographic Information, but also investigates the potential of the topic Critical Infrastructure as it could be applied on spatial assets and GIS and RS itself. Intended to stimulate research on new and emerging fields, this article’s main contribution is to move spatial research toward a more reflective stance where opportunities and challenges are equally and transparently addressed in order to gain more scientific quality. As a conclusion, GIS and RS can play a pivotal role not just in delivering data but also in connecting and analyzing data in a more integrative, holistic way.
ISSN:2220-9964