In this work, several modelling approaches are explored to represent spatial pattern dynamics of aquatic populations in aquatic ecosystems by the combination of models, knowledge and data in different scales. It is shown that including spatially distributed inputs retrieved from Remote Sensing images, a conventional physically-based Harmful Algal Bloom model can be enhanced. Also, Cellular Automata based models using high resolution photographs prove to be good in representing aquatic plant growth. Multi-Agent Systems can capture well the spatial patterns exhibited in GIS density maps. A synthesis modelling framework was developed to include biological/ecological growth and diffusive processes, and local effects in conventional modelling framework. The results of the complementary modelling paradigms investigated in this research can be of help in achieving a sustainable environmental management strategy.
Explores modeling approaches for spatial pattern dynamics of aquatic populations by integrating remote sensing data to enhance harmful algal bloom models and using cellular automata with high-resolution photographs to represent aquatic plant growth within a framework incorporating biological growth, diffusive processes, and local effects.
Publisher
CRC Press
Publication Date
Oct 2017
ISBN
9781138475298
Pages
202 p.
Item Type
Book
Format
Hardcover
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