Building Information Modeling for a Smart and Sustainable Urban Space

Description

Urban spaces are being called upon to develop a capacity for resilience and sustainability in order to meet the major challenges they face. To achieve such a goal, a practical development framework must be implemented in order to take advantage of the technological innovations that characterize the field of construction and urban engineering. Today, multi-scale BIM is bringing about significant changes that are redefining the paradigms of urban management. It facilitates simulations of the sustainability of urban spaces with respect to several criteria; most notably relating to energy, the economy and the environment. Building Information Modeling for a Smart and Sustainable Urban Space proposes a theoretical and practical framework for implementing BIM models for the creation of sustainable and intelligent urban spaces. It addresses the issues of acquisition, modeling, interoperability, and BIM and GIS integration for the production of BIM models. Case studies are presented, providing a practical dimension that demonstrates the production process of the urban model and its contribution to multiscale simulations, particularly in real estate evaluation and urban renewal. Cover Half-Title Page Title Page Copyright Page Contents Preface Acknowledgments List of Acronyms Introduction Chapter 1. BIM: A New Paradigm 1.1. Introduction 1.2. History of BIM 1.3. BIM: A meta concept 1.4. BIM: Between technology and process 1.5. BIM in the lifecycle of a building 1.5.1. From design to pre-construction 1.5.2. From construction to operation 1.6. Some transversal uses of BIM 1.6.1. Visualization 1.6.2. Coordination and collaboration 1.6.3. Construction planning: 4D simulation 1.6.4. Cost estimation: 5D simulation 1.6.5. Building management and maintenance 1.7. BIM dimensions and levels of detail 1.7.1. The “xDs” of BIM 1.7.2. Levels of detail 1.8. BIM maturity and capability 1.8.1. Level 0: Pre-BIM 1.8.2. Level 1: Object-oriented modeling 1.8.3. Level 2: Collaboration based on federated object-oriented models 1.8.4. Level 3: Collaboration around an integrated object-oriented model 1.9. Conclusion 1.10. References Chapter 2. Which Data Sources for the BIM Model? 2.1. Introduction 2.2. Multiple sources for the 3D digitization of urban space 2.2.1. 3D measurement techniques 2.2.2. Selection criteria 2.3. Approaches for 3D data production 2.3.1. Point cloud-based approaches 2.3.2. Image-based approaches 2.3.3. Hybrid approaches 2.4. Integration of multi-source data 2.5. General discussion 2.6. Conclusion 2.7. References Chapter 3. Development of the BIM Model 3.1. Introduction 3.2. Issues around 3D urban models 3.3. Semantics of 3D urban models 3.4. From the point cloud to the 3D model 3.4.1. Point cloud processing chain 3.4.2. Geometric modeling 3.5. 3D reconstruction of the BIM model 3.5.1. Scan-to-BIM process 3.5.2. Scan versus BIM process 3.6. Conclusion 3.7. References Chapter 4. Open BIM Standards 4.1. Standardization bodies 4.1.1. Open Geospatial Consortium 4.1.2. ISO TC211 4.1.3. buildingSMART 4.2. Data models for multi-scale BIM 4.2.1. Open BIM 4.2.2. CityGML 4.2.3. LandInfra/InfraGML 4.3. Conclusion 4.4. References Chapter 5. GeoBIM: Towards a Convergence of BIM and 3D GIS 5.1. Introduction 5.2. The GeoBIM concept 5.3. Some applications of GeoBIM 5.4. BIM and GIS: similarities and differences 5.5. BIM and GIS integration 5.5.1. Model interoperability 5.5.2. Integration approaches 5.6. IFC and CityGML conversion 5.7. BIM georeferencing 5.8. Conclusion 5.9. References Chapter 6. BIM and 3D GIS Integration for Real Estate Valuation 6.1. Introduction 6.2. Real estate valuation: concepts, approaches and standards 6.2.1. The concept of real estate valuation 6.2.2. Real estate valuation approaches 6.2.3. Real estate valuation norms and standards 6.3. BIM and 3D GIS for real estate valuation 6.4. BIM-3D GIS integration: a new paradigm for real estate valuation 6.5. Examples of BIM and 3D GIS simulations for real estate valuation 6.5.1. Simulation of the internal factors of a property 6.5.2. Identification of comparable units of the property being appraised 6.5.3. 3D visibility analysis 6.5.4. Valuation of tax property elements: 3D cadastre 6.6. Conclusion 6.7. References Chapter 7. Semantic Segmentation of Airborne LiDAR Data for the Development of an Urban 3D Model 7.1. Introduction 7.2. From semantic segmentation to 3D modeling 7.3. Semantic segmentation by Deep Learning 7.3.1. Semantic segmentation methods by DL 7.3.2. Discussion 7.4. Development of an urban 3D model 7.4.1. Geometric modeling from the 3D point cloud 7.4.2. Semantic modeling 7.4.3. Discussion 7.4.4. Our approach 7.5. Conclusion 7.6. References Chapter 8. BIM for the Renovation of Urban Spaces 8.1. Introduction 8.2. Urban space: problems and dysfunctions 8.3. Urban renewal approaches 8.4. BIM/CIM for urban renewal 8.4.1. Methodology 8.5. Renovation process 8.6. Conclusion 8.7. References Conclusion List of Authors Index Other titles from iSTE in Systems and Industrial Engineering – Robotics