£109.75

Springer Agent-Based Models and Complexity Science - Geospatial Big Data

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Description

This scholarly collection from Springer explores the intersection of agent-based modelling and complexity science within the context of geospatial big data. Selected papers from a dedicated workshop bring together cutting-edge research that applies agent-based approaches to geographic information systems and spatial analysis. The book is part of the Advances in Geographic Information Science series, positioning it as an essential resource for academics, researchers, and professionals working at the convergence of computational modelling, geography, and data science. It addresses how agent-based models can handle increasingly complex spatial datasets and offers practical insights into implementing these techniques across various geographic and environmental applications.

Key Features

Springer publication bringing peer-reviewed research on agent-based modelling within geographic information science.

Focuses on applying complexity science methods to geospatial big data analysis and spatial problem-solving.

Part of the Advances in Geographic Information Science series, establishing academic authority in the field.

Compiled from workshop presentations, offering contemporary perspectives on agent-based models in geography.

Suitable for researchers, academics, and GIS professionals studying computational approaches to spatial data.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
25 August 2018
Listed Since
29 August 2018

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No barcode data available

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