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Visualising Uncertain Flood Inundation Maps. David Leedal 1 , Jeff Neal 2 , Keith Beven 1,3 and Paul Bates 2 . Lancaster Environment Centre, Lancaster University, Lancaster, UK ; School of Geographical Sciences, University of Bristol, Bristol, UK ;
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Visualising Uncertain Flood Inundation Maps David Leedal1, Jeff Neal2, Keith Beven1,3 and Paul Bates2. Lancaster Environment Centre, Lancaster University, Lancaster, UK; School of Geographical Sciences, University of Bristol, Bristol, UK; Geocentrum, Uppsala University, Uppsala, Sweden
Visualising Uncertain Flood Inundation Maps Outline Demonstrate the Google uncertain flood inundation map tool Talk about why information visualisation is important in this context Discuss the potential impact of ‘smart operations’ such as the visualisation tool within flood risk management
Visualising Uncertain Flood Inundation Maps Visualisation tool components JSON mechanism for loading data to JavaScript arrays Python scripts for batch processing GIS data to JSON format and PNG images Jquery sliders Depth Exceedence selector Point depth exceedence selector using Google charts
Visualising Uncertain Flood Inundation Maps Visualisation tool components JSON mechanism for loading data to JavaScript arrays Python scripts for batch processing GIS data to JSON format and PNG images Jquery sliders Depth Exceedence selector Point depth exceedence selector using Google charts Main control panel with intuitive user interface widgets Drag and drop marker with interactive depth exceedence graph The ‘show all’ probabilities option using a colour map to represent probability of exceediong the chosen depth.
Visualising Uncertain Flood Inundation Maps Why is information visualisation important? • Some useful definitions: • The human/floodplain system • ‘Objects’ or ‘blocks’ • Operations • Data > information > understanding • Semiotic mechanism
Visualising Uncertain Flood Inundation Maps Examples of Objects • Human systems: • Governance • National • Regional • local • Developer • Environmental NGO (EA) • Consultant • Resident of floodplain
Visualising Uncertain Flood Inundation Maps Examples of Objects • Physical systems: • A risk zone • A residential property • A factory • Documents: • Planning proposal • Flood risk Assessment • Risk map
Visualising Uncertain Flood Inundation Maps Examples of Objects • Each object: • encapsulates its own data (which could be other objects) • can perform operations on its data • Can interact with other objects
Visualising Uncertain Flood Inundation Maps Examples of Objects Objects represented by UML/SySML:
Visualising Uncertain Flood Inundation Maps Examples of Objects When an actor in the human/floodplain system instigates a use-case: A series of interactions between objects is instigated. See for example the UK PPS25 document.
Visualising Uncertain Flood Inundation Maps Data > understanding • Data is not information • Information is not understanding • Information implies data in flow • Understanding comes about through the decoding of information by a suitable semiotic system
Visualising Uncertain Flood Inundation Maps Operations are high level • Example: a ‘resident’ object may contain the operation: • ‘Show me the estimated risk that my property will flood sometime in the next 100 years’ • The operation must be designed to create understanding (combination of data and semiotic processes)
Visualising Uncertain Flood Inundation Maps Complicated to Complex systems • Well designed operations should aim to: • Increase the degree of understanding that actors can extract from available information • Increase the ease with which actors can access and exchange information • Increase the capacity to archive information
Visualising Uncertain Flood Inundation Maps Complicated to Complex systems 1890 1800 medieval
Visualising Uncertain Flood Inundation Maps Complicated to Complex systems Present (OS crown (c))
Visualising Uncertain Flood Inundation Maps Complicated to Complex systems Present (OS crown (c))
Visualising Uncertain Flood Inundation Maps Desirable properties of a complex human/floodplain system • To redistribute and allocate land use types to achieve: • Self adapting behaviour • Robustness • Decentralisation • Optimal seeking
Visualising Uncertain Flood Inundation Maps Summary • The human/floodplain system is complicated but not Complex. If we can move towards a Complex system we may achieve robustness, self adaptation and efficient allocation of land use types • Transition to self adaptation may be hastened by the design of effective operations • Understanding • Access • Exchange • Archive • Probabilistic inundation mapping is key • The google maps visualisation tool is an attempt to design such an operation
Visualising Uncertain Flood Inundation Maps David Leedal1, Jeff Neal2, Keith Beven1,3 and Paul Bates2. Fig(c). The web-tool for visualising uncertain flood inundation data. The figure shows the main components of the tool including a georeferenced overlay selectable by the user via slider controls, a point-specific marker showing depth against probability of exceedence, and text areas providing word-based summaries of the chosen overlay and key technical terms. Fig(a) Main control panel with intuitive user interface widgets Fig(d). Drag and drop marker with interactive depth exceedence graph Fig(b). The ‘show all’ probabilities option using a colour map to represent probability of exceediong the chosen depth.