Università degli studi di Trento
READY-MADE MODEL. Digital tools for reality-based virtual landscapes
Abstract
dc:descriptionOver the past three decades, the digital and information revolution has reshaped design methodologies, offering dynamic and multi-level modelling approaches. Urban Digital Twins have emerged as a powerful tool for Smart Cities, facilitating scenario assessments and citizen engagement. However, rural and mountainous areas face challenges due to poor connectivity and digital infrastructure, hindering technological advancements in design processes. This doctoral thesis aims to develop sustainable workflows for virtual landscape reconstructions, integrating diverse data sources and tools to support landscape and urban design in mountainous regions. The concept of a ready-made model is introduced, assembling digital procedures to address specific contextual challenges. The research employs qualitative and quantitative methodologies across different landscape scales and case studies in the Autonomous Province of Trento, Italy. Experimental-instrumental findings contribute to theoretical-methodological insights, enhancing understanding of complex territorial transformations. The thesis focuses on landscape topography, built environment, and green infrastructure, providing a holistic perspective for digital reconstruction and management. The ultimate goal is to create a Territorial Digital Twin, a three-dimensional repository of knowledge and simulator for resilient futures, bridging gaps in strategic planning and process management at the landscape scale.
Degree
thesis:*- Grantor dc:publisher
- Università degli studi di Trento
- Year dc:date
- 2024
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Chioni, Chiara
- Contributors dc:contributor
-
- Favargiotti, Sara
- Massari, Giovanna
Subjects
dc:subject × 6Rights
dc:rights- Statement dc:rights
-
- info:eu-repo/semantics/embargoedAccess
- license:Creative commons
- license uri:http://creativecommons.org/licenses/by-nc-nd/4.0/
- Language dc:language
- eng
Identifiers
dc:identifier.*- OAI identifier oai:identifier
- oai:iris.unitn.it:11572/430590