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Eric Vaz

Researcher at Ryerson University

Publications -  109
Citations -  1733

Eric Vaz is an academic researcher from Ryerson University. The author has contributed to research in topics: Land use & Urban sprawl. The author has an hindex of 21, co-authored 105 publications receiving 1426 citations. Previous affiliations of Eric Vaz include Universidade Nova de Lisboa & Heidelberg University.

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Spatiotemporal simulation of urban growth patterns using agent-based modeling: The case of Tehran

TL;DR: This simulation provides strong evidence that during the next decade planning authorities will have to cope with continuous as well as heterogeneously distributed urban growth.
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Spatial Heterogeneity in Hedonic House Price Models: The Case of Austria

TL;DR: In this paper, single-family home prices in Austria are explored to investigate the capability of global and locally weighted hedonic models for modeling spatial heterogeneity (SH) beyond the level of regional indicators.
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An assessment of a collaborative mapping approach for exploring land use patterns for several European metropolises

TL;DR: Evaluation of several land use types at the local level suggests that a number of OSM classes (such as anthropogenic land use, agricultural and some natural environment classes) are viable alternatives for land use classification and can be integrated into planning decisions for stakeholders and policymakers.
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Exploring expert perception towards brownfield redevelopment benefits according to their typology

TL;DR: In this paper, the authors present a critical review of the information on brownfield redevelopment, considering not only the use of existing literature but also the analysis of twenty-five brownfield rehabilitation projects, in order to identifying on the one hand, the existing brownfield typologies, and on the other hand the benefits associated to each of the identified brownfield this paper.
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GlobeLand30 as an alternative fine-scale global land cover map: Challenges, possibilities, and implications for developing countries

TL;DR: In this article, the accuracy of the GlobeLand30 dataset for developing countries has been evaluated and the detailed implications of this dataset for different applications as well as informing regional policy makers are discussed.