Home // International Journal On Advances in Intelligent Systems, volume 7, numbers 1 and 2, 2014 // View article
Authors:
Maria Grazia Albanesi
Roberto Albanesi
Keywords: Land use, urban sprawl, anthropentropy factor, decision-making support system, predictive model, morphological operators, web-based system, UGC
Abstract:
This paper describes a new decision-making support system, which is able to estimate the future impact on the environment of new planned (but not yet built) urban settlements and/or communication roads. The challenging addressed problem is to decide if, according to a quantitative indicator, the creation of new human anthropic areas is compatible with a sustainable land use control, for an efficient environment preservation. The core of the system is a predictive model, which is initially trained by selected worst stressing cases. Some modifications to classical computer vision morphological operators are proposed and applied to standard Google Earth satellite maps, according to the User Generated Content paradigm. The model updates the previously defined indicator of Anthropentropy Factor, by producing a novel indicator of higher level (indicator of type C, or performance indicator, according to European Environmental Agency classification). The paper describes this important theoretical improvement, the model architecture, the new customized computer vision functions, and the prototype of a web-based implementation of the decision-making support system, with visual and numerical results of some significant cases.
Pages: 85 to 102
Copyright: Copyright (c) to authors, 2014. Used with permission.
Publication date: June 30, 2014
Published in: journal
ISSN: 1942-2679