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George Grekousis
Researcher at Sun Yat-sen University
Publications - 30
Citations - 1010
George Grekousis is an academic researcher from Sun Yat-sen University. The author has contributed to research in topics: Fuzzy clustering & Population. The author has an hindex of 13, co-authored 25 publications receiving 615 citations. Previous affiliations of George Grekousis include University of Thessaly & State University of New York College of Environmental Science and Forestry.
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An overview of 21 global and 43 regional land-cover mapping products
TL;DR: Land-cover (LC) products, especially at the regional and global scales, comprise essential data for a wide range of environmental studies affecting biodiversity, climate, and human health by summarizing 23 global and 41 regional LC products.
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Neighbourhood greenness and mental wellbeing in Guangzhou, China: What are the pathways?
TL;DR: In this article, the authors explore biopsychosocial pathways linking exposure to neighbourhood greenness to mental wellbeing using survey data collected from 35 neighbourhoods of Guangzhou, China, using the Normalized Difference Vegetation Index (NDVI) as the surrogate for residential exposure to greenness, thereby enabling the comparison between China and other countries.
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Modeling urban evolution using neural networks, fuzzy logic and GIS: The case of the Athens metropolitan area
TL;DR: An artificial intelligence approach integrated with geographical information systems (GISs) for modeling urban evolution using fuzzy logic and neural networks to provide a synthetic spatiotemporal methodology for the analysis, prediction and interpretation of urban growth.
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Perceptions of built environment and health outcomes for older Chinese in Beijing: A big data approach with street view images and deep learning technique
TL;DR: Assessment of perceptions of the built environment with street view images of 1231 older adults in 48 neighborhoods in the Haidian District, Beijing, China shows that perceived safety was significantly associated with both the physical and mental health outcomes.
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Artificial neural networks and deep learning in urban geography: A systematic review and meta-analysis
TL;DR: This study provides a statistical review of 140 papers on studies that employed ANNs in urban geography between 1997 and 2016 and performs a quantitative meta-analysis using non-parametric bootstrapping on ANNs' overall accuracy achieved.