GIS, Environmental Modeling and Engineering

Professor Allan Brimicombe is Head of the Centre for Geo-Information Studies at the University of East London. Prior to this he was the founding Head of the Department of Land Surveying and Geo-Informatics at the Hong Kong Polytechnic University which in turn was preceded by a successful international career in consulting engineering.

This well-written, second edition is a significant and needed contribution to the understanding of the increasing interaction between geospatial disciplines and tools - i.e., GIS, and their use in conjunction with environmental and engineering models for problem solving. The exposition is clear, lively, and scholarly, revealing an adequate use of a colloquial tone while keeping commentary brief and to the point with few linguistic variants and regional terms used. For the most part, figures are well designed, clearly printed, with their elements discernible, and the book abounds in helpful diagrams and illustrations for both conceptualization and example.This book provides a guiding paradigm for the study of the current possibilities for mutual synergy between geospatial contextualization and the mathematical and algorithmic formulations of model/simulation inputs and outputs. This volume would undoubtedly enrich the libraries of those professionals who are seeking a deeper understanding of how to better integrate environmental and engineering modeling - both with and from within a GIS, constituting a valuable resource for research projects and course materials.—Demetrio P. Zourarakis, PhD, GISp, CMS-RS, eMS-GIS/LIS, Remote Sensing/GIS Analyst, in Photogrammetric Engineering & Remote Sensing, January 2011Praise for the Previous Edition: Brimicombe’s rich experience clearly shows ... the book is a useful guide to the core information about the workings of environmental models and their development." -Muki Haklay, University College London, in Environment and Planning B, 2005

• Introduction. From GIS to geocomputation. The rise of geo-information science and engineering. Approaches to modelling. The role and nature of environmental models. Case studies. Issues of coupling the technologies. Data and information quality issues. Modelling issues. Decision-making under uncertainty.