Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/33171
Title: | GAEA: A Country-Scale Geospatial Environmental Modelling Tool: Towards a Digital Twin for Real Estate | Authors: | Jamil, Asfa Padubidri, Chirag Karatsiolis, Savvas Kalita, Indrajit Guley, Aytac Kamilaris, Andreas |
Major Field of Science: | Natural Sciences | Field Category: | NATURAL SCIENCES | Keywords: | Sustainable urban growth;AI-empowered geospatial tool;Climate change;Country-scale modelling;Environmental digital twins;Environmental monitoring;GAEA;Geo-visualizations;Geoinformatics | Issue Date: | 2023 | Source: | Advances and New Trends in Environmental Informatics, 2023 | Abstract: | Monitoring the physical and artificial environment at large-scale is crucial for approaching significant problems such as climate change, biodiversity loss, and sustainable urban growth. Towards this direction, GAEA is a novel AI-empowered geospatial online tool, designed to facilitate country-scale environmental monitoring, modelling, analytics, and geo-visualizations, providing valuable insights in the geographical region of the country of Cyprus, with some focus on the real estate application domain. This paper presents the design and development of GAEA, the needs and requirements it addresses, the environmental services it offers, its implementation details and main features, and an evaluation and discussion of its perspectives and overall potential. GAEA offers a user-friendly web interface that allows users to interact with a wide range of services, including land use monitoring, climate information, geohazard, and proximity analysis. GAEA is an important milestone and real-world demonstration of the vision of creating a country-scale environmental digital twin that allows informed decisions in land use assessment, climate analysis, and disaster management. | URI: | https://hdl.handle.net/20.500.14279/33171 | ISBN: | 9783-031469015 9783031469022 |
DOI: | 10.1007/978-3-031-46902-2_10 | Rights: | Attribution-NonCommercial-NoDerivatives 4.0 International | Type: | Book Chapter | Affiliation : | CYENS - Centre of Excellence Cyprus University of Technology University of Twente |
Publication Type: | Peer Reviewed |
Appears in Collections: | Άρθρα/Articles |
CORE Recommender
This item is licensed under a Creative Commons License