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

Hardback

Main Details

Title Modelling Nature-based Solutions: Integrating Computational and Participatory Scenario Modelling for Environmental Management an
Authors and Contributors      Edited by Neil Sang
Physical Properties
Format:Hardback
Pages:376
Dimensions(mm): Height 235,Width 156
Category/GenreEnvironmental economics
Ecological science
Applied ecology
Conservation of the environment
Social impact of environmental issues
Sustainability
ISBN/Barcode 9781108428934
ClassificationsDewey:333.70113
Audience
Professional & Vocational
Illustrations Worked examples or Exercises; 24 Plates, color; 47 Halftones, black and white

Publishing Details

Publisher Cambridge University Press
Imprint Cambridge University Press
Publication Date 12 March 2020
Publication Country United Kingdom

Description

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.

Author Biography

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.