2017
DOI: 10.1016/j.cageo.2017.03.021
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A framework for interactive visual analysis of heterogeneous marine data in an integrated problem solving environment

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Cited by 16 publications
(3 citation statements)
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“…Detection and tracking have also been developed with a focus on individual phenomena such as upwelling (Nascimento et al, 2012(Nascimento et al, , 2015Artal et al, 2019). Several studies in oceanography are supported by the development of efficient feature tracking methods, as mentioned above (Massey, 2012;Du et al, 2015;Li et al, 2011;Liu et al, 2017;Gad et al, 2018). Xie et al present a taxonomy of ocean data and related data processing tasks (Xie et al, 2019), including ocean phenomena identification, tracking, and pattern discovery.…”
Section: Related Workmentioning
confidence: 99%
“…Detection and tracking have also been developed with a focus on individual phenomena such as upwelling (Nascimento et al, 2012(Nascimento et al, , 2015Artal et al, 2019). Several studies in oceanography are supported by the development of efficient feature tracking methods, as mentioned above (Massey, 2012;Du et al, 2015;Li et al, 2011;Liu et al, 2017;Gad et al, 2018). Xie et al present a taxonomy of ocean data and related data processing tasks (Xie et al, 2019), including ocean phenomena identification, tracking, and pattern discovery.…”
Section: Related Workmentioning
confidence: 99%
“…In such context, the principals of geovisualisation (Wu & Shah, 2004) are well adapted to this need, promoting more favourable conditions for detecting change within complex systems (Rensink, 2002). Geovisualisation provides the link between geospatial information and human understanding, allowing for more interactive data exploration methods—interactive visualisation as a means to knowledge construction—(further details in Evangelidis et al, 2018; Harvey et al, 2017; Ladstädter et al, 2010; Li et al, 2016; Liu et al, 2018 and references therein). Following the guidelines of 3D visualisation, the emphasis is here given to “promote the transformations between 2D and 3D” and “reduce cognitive load by making information explicit and integrated” (adapted from Wu & Shah, 2004).…”
Section: Introductionmentioning
confidence: 99%
“…Scientific flow visualization is used to show the distribution of various data, such as water level, water depth, flow velocity, and pollutant concentration. Particle tracking, streamline rendering, and contour surface rendering are most commonly used to present flow conditions [17][18][19][20][21]. Visual flow effects are used to simulate water surface changes using computer graphics technology, enhancing the sense of reality in a virtual geographic environment [22][23][24][25][26].…”
Section: Introductionmentioning
confidence: 99%