ADVANCED 3D PARAMETRIC HISTORIC CITY BLOCK MODELING COMBINING 3D SURVEYING, AI AND VPL

Abstract

The presented research aims to define a parametric modelling methodology that allows, in short time and at a sustainable cost, the digital acquisition, modelling and semantic structuring of urban city blocks to facilitate 3D city modelling applied to historic centres. The methodology is based on field surveying and derives 3D data for the realisation of a parametric City Information Model (CIM). This is pursued through the adoption of parametric modelling as main method combined with AI procedures like supervised machine learning. In particular, the Visual Programming Language (VPL) Grasshopper is adopted as main working environment. The methodology proposed, called Scan-to-CIM, is developed to automate the cognitive operations of interpretation and input of surveying data performed in the field in order to create LoD4 city block models in a semi-automatic way. The proposed Scan-to-CIM methodology is applied to a city block located in the historic centre of Catania, Italy.