- English
- ePUB (mobile friendly)
- Available on iOS & Android
About this book
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.
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Table of contents
- Cover
- Half Title
- Half Title
- Title Page
- Copyright Page
- Dedication
- Abstract
- Samenvatting
- Acknowledgement
- Table of Contents
- Chapter 1 Introduction
- Chapter 2 Theoretical background
- Chapter 3 Developments in modelling paradigms
- Chapter 4 Harmful algal bloom prediction using data-driven techniques
- Chapter 5 Enhancing physically-based algal dynamics modelling using remote sensing images
- Chapter 6 Spatial pattern dynamics in cellular automata based aquatic ecosystem modelling
- Chapter 7 Revealing spatial pattern dynamics in aquatic ecosystem modelling with multi-agent systems
- Chapter 8 A synthesis of physically-based water quality modelling and multi-agent-based population dynamics modelling
- Chapter 9 Conclusions and recommendations
- References
- List of figures
- List of tables
- List of symbols and abbreviations
- Appendix
- Curriculum Vitae
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