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CRC Press Spatial Pattern Dynamics in Aquatic Ecosystem Modelling - PhD Thesis

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Description

This comprehensive PhD thesis from UNESCO-IHE explores advanced modelling approaches for representing spatial pattern dynamics in aquatic ecosystems. The research combines multiple modelling techniques, integrated knowledge, and real-world data across different scales to enhance understanding of aquatic populations. The work demonstrates how remote sensing images can strengthen conventional physically-based Harmful Algal Bloom models, whilst Cellular Automata approaches using high-resolution photography effectively represent aquatic plant growth patterns. Multi-Agent Systems are shown to successfully capture spatial patterns evident in GIS density maps. Published by CRC Press, this thesis bridges theory and application in aquatic ecosystem modelling, offering valuable insights for researchers, environmental scientists, and modelling specialists working on aquatic resource management and ecological prediction.

Key Features

Remote sensing integration enhances Harmful Algal Bloom model predictions using spatially distributed inputs.

Cellular Automata models effectively represent aquatic plant growth using high-resolution photograph analysis.

Multi-Agent Systems capture spatial patterns visible in GIS density maps for population dynamics.

Multi-scale modelling approach combines diverse data sources and knowledge across different ecosystem levels.

CRC Press publication provides peer-reviewed research on aquatic ecosystem pattern dynamics and spatial modelling.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
02 October 2017
Listed Since
08 December 2017

Barcode

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