Modelling Nature-based Solutions: Integrating Computational and Participatory Scenario Modelling for Environmental...

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Neil Sang (Swedish University of Agricultural Sciences)

Modelling Nature-based Solutions

Integrating Computational and Participatory Scenario Modelling for Environmental Management...

Neil Sang (Swedish University of Agricultural Sciences)

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English

Cambridge University Press
12 March 2020

Environmental economics; Environment, transport & planning law; Conservation of the environment; Social impact of environmental issues; Environmental monitoring

Nature-based solutions (NBS) are essential to ensure a sustainable society and healthy ecosystem over the coming decades. However, the systems to be managed are both broad and complex, requiring an integrated understanding of both bio-physical systems, such as soils and water, and economic and social systems, such as urban development and human behaviour. This edited book joins these domains of knowledge together from an applied perspective and considers how computer science can help. It takes a strategic look at the benefits and barriers to using modelling within environmental management and planning practice. It delves further by providing an in-depth comparative review of a wide range of models from a variety of scientific disciplines of interest with examples of their use for NBS. As such, this illustrated guide is designed to help students, researchers and practitioners navigate the huge range of modelling options available and develop the common understanding to work inter-disciplinarily.

Edited by: Neil Sang (Swedish University of Agricultural Sciences)
Imprint: Cambridge University Press
Country of Publication: United Kingdom
Dimensions: Height: 235mm, Width: 156mm, Spine: 22mm
Weight: 780g
ISBN: 9781108428934
ISBN 10: 1108428932
Pages: 376
Publication Date: 12 March 2020
Audience: Professional and scholarly , Undergraduate
Format: Hardback
Publisher's Status: Active

Neil S. Sang is a researcher in Geographical Information Science (GIS) at the Department of Landscape Architecture, Planning and Management, Swedish University of Agricultural Science (SLU). His research interests are broad, covering a range of modelling approaches such as GIS, optimisation and AI, simulation modelling, remote sensing, citizen science, and geodesign. Formerly at the James Hutton Institute, UK, he has worked in a wide range of subject areas within socio-environmental science.