2014
DOI: 10.1016/j.envsci.2014.07.018
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Maps, laws and planning policy: Working with biophysical and spatial uncertainty in the case of sea level rise

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Cited by 22 publications
(17 citation statements)
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“…Le Cozannet et al (2015, 2017 and Stephens et al (2017) discuss the importance of considering uncertainties from all sources in assessments of sea-level change, but they do not specifically mention vertical uncertainty of topographic data used to map potential impact zones on the land surface. A number of studies address the effects of input elevation data uncertainty (Gesch, 2009;Kettle, 2012;Bell et al, 2014;Hinkel et al, 2014;Valentine, 2014) and conclude that higher resolution data with better vertical accuracy significantly improve assessment results. The choice of elevation model for an assessment study can also have a substantial effect on results owing to combined uncertainties of input datasets, especially elevation and population distribution (Lichter et al, 2011;Mondal and Tatem, 2012;Wolff et al, 2016).…”
Section: Introductionmentioning
confidence: 99%
“…Le Cozannet et al (2015, 2017 and Stephens et al (2017) discuss the importance of considering uncertainties from all sources in assessments of sea-level change, but they do not specifically mention vertical uncertainty of topographic data used to map potential impact zones on the land surface. A number of studies address the effects of input elevation data uncertainty (Gesch, 2009;Kettle, 2012;Bell et al, 2014;Hinkel et al, 2014;Valentine, 2014) and conclude that higher resolution data with better vertical accuracy significantly improve assessment results. The choice of elevation model for an assessment study can also have a substantial effect on results owing to combined uncertainties of input datasets, especially elevation and population distribution (Lichter et al, 2011;Mondal and Tatem, 2012;Wolff et al, 2016).…”
Section: Introductionmentioning
confidence: 99%
“…100 Such actions can include exposing asymmetric power dynamics through new information, advocating changes to societal norms or government and industry policies or rules, mobilising new interest groups and coalitions, and generating other forms of countervailing power. 48,102,103 For example, in the Brazilian water management example, técnicos have been able to use climate information as leverage to curb both economic and political power within river basin committees. 90 Fung 104 also describes, for example, the generation of a 'civic immune system' whereby an ecology of transparency, accountability, and monitoring mechanisms and associations can monitor and disclose information to enhance democracy and seek to limit major abuses of power.…”
Section: Methods For Unveiling the Dimensions Of Powermentioning
confidence: 99%
“…Although risk profiles vary widely between countries, the managerial approach is more consistent, commonly comprising an investment in science to build an evidence base for improving policy responses (UNISDR, ). It is in this context that hazard maps have become an important tool of government, used to help inform policy about which areas are most susceptible to hazards (Bell et al., ; Thompson, Lindsay, & Galliard, ), and to communicate this information to the public so that they too can make better‐informed decisions. Flood risk maps, for example, are now widespread, with national coverage required in the USA, Canada and in the European Union with the consequence that an increasingly sophisticated capacity for modelling and mapping has emerged (de Moel, Van Alphen, & Aerts, ; Landström, Whatmore, & Lane, ).…”
Section: Identifying Risky Spaces With Mapsmentioning
confidence: 99%
“…For government authorities, maps are often valued because they help project a sense of “objectivity and certitude” (Monmonier, , p. 373), since they are expected to have been compiled by experts in positions of trust. In the process, hazard maps become part of an instrumental, managerialist framework for managing risk and with this comes a responsibility regarding the quality of information and how it is used (Bell et al., ; Gustafson, ; Lane, ).…”
Section: The Challenges Of Modelling Complexity Mapping Uncertainty mentioning
confidence: 99%
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