URBAN UTILITY _ milano 22 03 2013 LA COSTRUZIONE DEL DATO COME PRESUPPOSTO DELLA DECISIONE PRIMA SESSIONE THE USE 3D GIS AND LIDAR DATA FOR URBAN PLANNING AND DECISION MAKING Cláudio Carneiro dell Ecole Polytechnique Federale de Lausanne
Urban Utilities Conference Milan Polytechnic, Italy March 22 nd 2013 The use of 3-D GIS and LiDAR data for urban planning and decision-making Cláudio Carneiro Eugenio Morello Gilles Desthieux Introduction Solar potential Energy demand 3-D visualization Conclusions / Future work
Outline Aim of this study Short presentation of 2-D / 3-D GIS data, LiDAR data and derived hybrid products: 2.5-D Urban Surface Models (2.5-DUSM) An overview of several tools: Urban Environmental Quality (UEQ) indicators extracted from 2.5-DUSM for urban planning and decision-making purposes The CityGML standard used for 3-D visualization of UEQ indicators Conclusions and future work 2
Aim of this study We highlight the use of 3-D geospatial data for the environmental analysis of cities, aiming to provide useful tools for sustainable urban planning and design and the extraction of urban environmental quality (UEQ) indicators. We introduce our recent research about the implementation of computational tools for the analysis, evaluation and design of the urban space and compare results that can be obtained with different data sources. We establish a process to investigate digital urban models integrating crossdisciplinary competences, like remote sensing, GIS, image processing, urban planning and environmental studies. 3
3-D geospatial data Today's geo-browsers and mash-up tools are rich sources of 3-D information for understanding cities In the near future, remote sensing imagery will become more common and inexpensive. The technique Construction of 2.5 digital urban surface models (2.5-DUSM) representing the form of the city. The technique is based on the image processing of these raster images Tools Implementation of new tools for the environmental analysis of the urban texture. Focus on urban planning and decision-making: extraction of Urban Environmental Quality (UEQ) indicators: - Urban morphology - Solar accessibility - Energy consumption - Visibility analysis - 4
Geospatial data sources used 2-D GIS (vector data) LiDAR data: clouds of raw points 3-D GIS (vector data)
Principles of the airborne LiDAR system (Light Detection And Ranging) 3 1 2 4 1 1 Laser sensor, emitting up to 100.000 pulses/second. Reflected by roofs, vegetation (canopy, intermediate levels), soil, After computation, resulting in a dense cloud of raw points 2 Inertial navigation system (INS) for the measurement of the orientation of the laser beam according to the aircraft s moves 3 Differential GPS system, giving for each point the coordinates (X, Y, Z) of the laser sensor in a specific reference system (WGS 84) 4 Computer for real-time control, coordinates computation and data storage
Producing digital urban models: top-down & bottom-up approach Reconstruction of hybrid 2.5-DUSM: 2-D GIS, 3-D GIS and remote sensing data (mostly LiDAR) remote-sensing data acquisition Missing steps? More d Sofware needed to pa User-generated content 7
An overview of available tools and required data sources 8
Example of hybrid 2.5-DUSM construction using 2-D GIS vector data (building footprints) and 3-D LiDAR data Building footprints 3-D «Sugar Block» buildings + height attribute of each building but more interesting: hybrid approach using building footprints to be combined with LiDAR data 2.5-D Urban Surface Model (2.5-DUSM)
Example of hybrid 2.5-DUSM construction (step by step) using 2-D / 3-D GIS vector data and 3-D LiDAR data 10
2.5-D urban hybrid models derived from 2-D / 3-D GIS data and LiDAR data Advantages: - Fast scanning process - Snapshot of the existing physical context - Level of detail (LoD) that includes roof superstructures and small details - Increasing availability - Decreasing costs Disadvantages: - Less accuracy due to interpolation - High level professional knowledge needed for the model reconstruction - Occlusion of Z-axis 11
Urban morphology Goal of the analysis: building envelope (facades and roofs) Area of facades Volumes Area of roofs Example of a normalized 2.5-DUSM of buildings for a case-study area in the city center of Geneva, Switzerland 12
Influence of vegetation on the solar radiation over the urban fabric using a 2.5-DUSM of building roofs Goal of the analysis: building roofs Above the comparison of the 2.5-DUSMs with (left) and without the presence of vegetation (right). Below the comparison of the annual irradiation maps collected on roofs with (left) and without the presence of vegetation (right). Some numerical indicators are presented for comparison. Case-study area in the district of Moillesulaz, Geneva, Switzerland 13
Estimation of the energy demand on the urban fabric using a normalized 2.5-DUSM of buildings Goal of the analysis: buildings Seasonal Thermal Energy Needs [MJ] Case-study area at CERN, Geneva, Switzerland
The CityGML standard used for 3-D visualization Kolbe et al. (2004) More resolution and details
Exploration of the solar potential on the urban fabric Goal of the visualization: building facades Option 1: only 3-D visualization (LoD2) of building facades Option 2: 1) 3-D visualization of building facades 2) Statistical information Case-study area in the city center of Geneva, Switzerland December 10 th Average irradiance [W/m 2 ]
Estimation of the energy demand on the urban fabric Goal of the visualization: buildings 3-D visualization (LoD1) of buildings Seasonal energy needs for heating [MJ] Case-study area in the city center of Florence, Italy
Estimation of the energy demand on the urban fabric Goal of the visualization: buildings Seasonal Thermal Energy Requirements [MJ] Option 1: 3-D visualization of buildings highlighting the integration of LoD1 and LoD2 together Option 2: 3-D visualization of buildings highlighting the integration of LoD1 and LoD2 together plus labelling Case-study area at CERN, Geneva, Switzerland
Conclusions The proposed method collects different 2-D and 3-D data in order to apply important analysis for urban planning and decision-making. Dynamic characteristic of the different tools proposed, allowing to take into account new data and to reproduce visualizations to show the up-to-date situation. The need to implement more innovative tools suitable in urban planning and design, especially with today s increasing concerns about environmental issues in cities. The objectives of all users of 3-D urban models for the geo-visualization of spatial indicators must be carefully identified. Very detailed urban models, on its own, do not necessarily offer an effective solution for geovisualization of the majority of UEQ indicators here emphasized. Future work Promoting context-specific environmental strategies in order to underline the peculiarities of each place through a set of UEQ indicators. Improving the tools, in order to diffuse the technique among professionals in the urban planning field (by implementing more intuitive user interface and reducing the steps among the software needed now).
Thanks for your given attention!!! Introduction Solar potential Energy demand 3-D visualization Conclusions / Future work