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We should be able to generate a workflow that given predefined input data is able to generate the Digital Twin as a set of 3DTiles for a medium size city like Florence or Genova. The worflow should be characterized as follows:
Input data
Below is a non exhaustive list of input data which we shall be prepared to handle for most common use cases to arrive at the production of an Urban DigitalTwin. For the moment we leave out IOT/Sensors and simulations.
buildings and related urban infrasctruture data as a shapefile, citygml, cityJSON, (KML)
point cloud data as las/laz deriving from aerial acquisitions
point cloud data of interior, underground or smaller parts of the city as las/laz acquired mostly with handlheld devices or drones
IFC models
Drone Data/Photogrammetry???
Data Preprocessing
There are a number of data preparation activities that needs to be performed. Here below we are highlightin some of them.
Vector data conversion to polyhedron
Point Cloud Data preprocessing including projection, sample, colorize and classification
Drone Data processing???
Expected output
3DTiles for input vector data with proper attributes
3DTiles for whole city from point cloud
3DTiles mesh from laz from point cloud and imagery
2d/3d Integration? What can we do to better integrated 3D data and 2d Data?
The final goal would be to have something similar to Cesium ION that can scale and convert seamlessly. Short term, we can have something that works on the desktop or on a single workstation
The expected output of this activity is to create a complete report that covers what follows:
describe and documents the state-of-the art of the work done so far on the pipelines for the City of Florence
development plan for implementing the workflow above or at least what we think it is feasible
Here below a tasklist of activities is proposed:
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changed the title
[Use case] Investigate option to generate 3DTiles for an entire city
[Use case] Investigate option to generate DigitalTwin for an entire city
Feb 26, 2024
Investigation on possible conversion optiomization for vector data (LODs, Tiling system, libraries replacements)
TODO
Investigation on CityGML, CityJSON and KML specifications
TODO -> Next step
Investigation on possible conversion optiomization for point cloud (data management and visualization, tiling, merging)
While working on Torino Obj files we were able to cover a conversion using blender as a CLI tool. This was more related to meshes rather than point cloud
Investigation on point cloud classification (pythorc)
TODO
Investigation on alternatives for 3D Tiles (Mago3D)
At the moment not good results for point cloud and meshes, we could still test this with CityGML
Investigation on photogrammetry libraries (OpenDroneMap)
TODO
Investigation on 3DTiles merging operations: from multiple to single tileset (cesium tools)
We partially analyze this inside the Torino pipeline experimentation, we used some custom code to merge tilesets. They are json files so we simply create a new tileset with the merged tilesets as children with a url reference
We should be able to generate a workflow that given predefined input data is able to generate the Digital Twin as a set of 3DTiles for a medium size city like Florence or Genova. The worflow should be characterized as follows:
Input data
Below is a non exhaustive list of input data which we shall be prepared to handle for most common use cases to arrive at the production of an Urban DigitalTwin. For the moment we leave out IOT/Sensors and simulations.
Data Preprocessing
There are a number of data preparation activities that needs to be performed. Here below we are highlightin some of them.
Expected output
More
The expected output of this activity is to create a complete report that covers what follows:
Here below a tasklist of activities is proposed:
Tasks
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