scholarly journals The Use of Simulation in Urban Modelling

10.5772/9575 ◽  
2010 ◽  
Author(s):  
Rosane Martins ◽  
Carl Horst
Keyword(s):  
Urban Modelling

scholarly journals New Advances in Automated Urban Modelling from Airborne Laser Scanning Data

2011 ◽  
Vol 5 (3) ◽  
pp. 196-208 ◽  
Author(s):  
D. F. Laefer ◽  
T. Hinks ◽  
H. Carr ◽  
L. Truong-Hong
Keyword(s):  
Laser Scanning ◽  
Airborne Laser Scanning ◽  
Airborne Laser ◽  
Urban Modelling

scholarly journals URBAN MODELLING WITH TYPOLOGICAL APPROACH. CASE STUDY: MERIDA, YUCATAN, MEXICO

2017 ◽  
Vol XLII-2/W5 ◽  
pp. 617-620
Author(s):  
A. Rodriguez
Keyword(s):  
3D Modeling ◽  
Three Dimensional ◽  
Historical Reconstruction ◽  
Colonial Era ◽  
Common Features ◽  
Modeling Approach ◽  
Urban Modelling ◽  
Typological Approach ◽  
Three Dimensional Models

In three-dimensional models of urban historical reconstruction, missed contextual architecture faces difficulties because it does not have much written references in contrast to the most important monuments. This is the case of Merida, Yucatan, Mexico during the Colonial Era (1542-1810), which has lost much of its heritage. An alternative to offer a hypothetical view of these elements is a typological - parametric definition that allows a 3D modeling approach to the most common features of this heritage evidence.

The integrated WRF/urban modelling system: development, evaluation, and applications to urban environmental problems

2011 ◽  
Vol 31 (2) ◽  
pp. 273-288 ◽  
Author(s):  
Fei Chen ◽  
Hiroyuki Kusaka ◽  
Robert Bornstein ◽  
Jason Ching ◽  
C. S. B. Grimmond ◽  
...  
Keyword(s):  
System Development ◽  
Environmental Problems ◽  
Urban Modelling ◽  
Development Evaluation ◽  
Modelling System ◽  
Urban Environmental Problems

TITAN to Google Earth: Workflow for Data Processing for Mobile Terrestrial LIDAR

2017 ◽  
Author(s):  
Michael Martin
Keyword(s):  
Data Processing ◽  
Spatial Information ◽  
New Technology ◽  
Google Earth ◽  
Lidar Data ◽  
Terrestrial Lidar ◽  
Urban Modelling ◽  
Feature Based ◽  
Point Data ◽  
Object Models

Terrestrial LIDAR scanners are pushing the boundaries of accurate urban modelling. Automation and the usability of tools used in feature abstraction and, to a lesser degree, presentation have become the chief concerns with this new technology. To broaden the use and impact of LIDAR in the geomatics, LiDAR datasets must be converted to feature-based representations without loss of precision. One approach, taken here, is to simultaneously examine the overall path that data takes through an organization and the operatordriven tasks carried out on the data as it is transformed from a raw point cloud to final product. We present a review of the current practices in LiDAR data processing and a foundation for future efforts to optimize. We examine alternative LIDAR processing workflows with two key questions in mind: computational efficiency - whether the process can be done using the tools at all - and tool complexity - what operator skill level is needed at each step. Using these workflows the usability of the specific software tools and the required knowledge to effectively carry out the procedures using the tools are examined. Preliminary results have yielded workflows that successfully translate LIDAR to 3D object models, highly decimated point representations of street data represented in Google Earth, and large volume point data flythroughs in ESRI ArcScene. We are documenting the pragmatic limits on each of these workflows and tools for endusers. Terrestrial LIDAR brings with it new innovations for spatial visualizations, but also questions of viability. The technology has proved valuable for specialized applications for experts, but can it be useful as a tool for proliferating 3d spatial information by and to non-experts. This study illustrates the issues associated with preparing 3d LIDAR data for presentation in mainstream visualization environments.

scholarly journals Dymium: A modular microsimulation modelling framework for integrated urban modelling

SoftwareX ◽  
2020 ◽  
Vol 12 ◽  
pp. 100555
Author(s):  
Amarin Siripanich ◽  
Taha Hossein Rashidi
Keyword(s):  
Modelling Framework ◽  
Urban Modelling
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