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.

Table of Contents:
Preface xi Rafika HAJJI and Hassane JARAR OULIDI Acknowledgments xiii List of Acronyms xv Introduction xix Rafika HAJJI and Hassane JARAR OULIDI Chapter 1. BIM: A New Paradigm 1 Rafika HAJJI and Hassane JARAR OULIDI 1.1. Introduction 1 1.2. History of BIM 2 1.3. BIM: A meta concept 3 1.4. BIM: Between technology and process 5 1.5. BIM in the lifecycle of a building 5 1.5.1. From design to pre-construction 6 1.5.2. From construction to operation 7 1.6. Some transversal uses of BIM 7 1.6.1. Visualization 8 1.6.2. Coordination and collaboration 9 1.6.3. Construction planning: 4D simulation 9 1.6.4. Cost estimation: 5D simulation 10 1.6.5. Building management and maintenance 10 1.7. BIM dimensions and levels of detail 11 1.7.1. The “xDs” of BIM 11 1.7.2. Levels of detail 12 1.8. BIM maturity and capability 16 1.8.1. Level 0: Pre-BIM 16 1.8.2. Level 1: Object-oriented modeling 16 1.8.3. Level 2: Collaboration based on federated object-oriented models 17 1.8.4. Level 3: Collaboration around an integrated object-oriented model 17 1.9. Conclusion 18 1.10. References 18 Chapter 2. Which Data Sources for the BIM Model? 21 Rafika HAJJI and Hassane JARAR OULIDI 2.1. Introduction 21 2.2. Multiple sources for the 3D digitization of urban space 22 2.2.1. 3D measurement techniques 22 2.2.2. Selection criteria 27 2.3. Approaches for 3D data production 28 2.3.1. Point cloud-based approaches 29 2.3.2. Image-based approaches 32 2.3.3. Hybrid approaches 32 2.4. Integration of multi-source data 33 2.5. General discussion 34 2.6. Conclusion 36 2.7. References 36 Chapter 3. Development of the BIM Model 41 Rafika HAJJI and Hassane JARAR OULIDI 3.1. Introduction 41 3.2. Issues around 3D urban models 42 3.3. Semantics of 3D urban models 42 3.4. From the point cloud to the 3D model 43 3.4.1. Point cloud processing chain 44 3.4.2. Geometric modeling 50 3.5. 3D reconstruction of the BIM model 54 3.5.1. Scan-to-BIM process 54 3.5.2. Scan versus BIM process 57 3.6. Conclusion 58 3.7. References 58 Chapter 4. Open BIM Standards 63 Hassane JARAR OULIDI and Rafika HAJJI 4.1. Standardization bodies 63 4.1.1. Open Geospatial Consortium 63 4.1.2. ISO TC211 64 4.1.3. buildingSMART 65 4.2. Data models for multi-scale BIM 65 4.2.1. Open BIM 65 4.2.2. CityGML 68 4.2.3. LandInfra/InfraGML 70 4.3. Conclusion 75 4.4. References 76 Chapter 5. GeoBIM: Towards a Convergence of BIM and 3D GIS 77 Rafika HAJJI and Hassane JARAR OULIDI 5.1. Introduction 77 5.2. The GeoBIM concept 78 5.3. Some applications of GeoBIM 79 5.4. BIM and GIS: similarities and differences 80 5.5. BIM and GIS integration 82 5.5.1. Model interoperability 82 5.5.2. Integration approaches 83 5.6. IFC and CityGML conversion 87 5.7. BIM georeferencing 87 5.8. Conclusion 89 5.9. References 89 Chapter 6. BIM and 3D GIS Integration for Real Estate Valuation 95 Siham EL YAMANI and Rafika HAJJI 6.1. Introduction 95 6.2. Real estate valuation: concepts, approaches and standards 96 6.2.1. The concept of real estate valuation 97 6.2.2. Real estate valuation approaches 97 6.2.3. Real estate valuation norms and standards 98 6.3. BIM and 3D GIS for real estate valuation 99 6.4. BIM-3D GIS integration: a new paradigm for real estate valuation 101 6.5. Examples of BIM and 3D GIS simulations for real estate valuation 103 6.5.1. Simulation of the internal factors of a property 104 6.5.2. Identification of comparable units of the property being appraised 106 6.5.3. 3D visibility analysis 107 6.5.4. Valuation of tax property elements: 3D cadastre 108 6.6. Conclusion 108 6.7. References 109 Chapter 7. Semantic Segmentation of Airborne LiDAR Data for the Development of an Urban 3D Model 113 Zouhair BALLOUCH and Rafika HAJJI 7.1. Introduction 113 7.2. From semantic segmentation to 3D modeling 114 7.3. Semantic segmentation by Deep Learning 118 7.3.1. Semantic segmentation methods by DL 118 7.3.2. Discussion 120 7.4. Development of an urban 3D model 121 7.4.1. Geometric modeling from the 3D point cloud 122 7.4.2. Semantic modeling 123 7.4.3. Discussion 125 7.4.4. Our approach 125 7.5. Conclusion 127 7.6. References 127 Chapter 8. BIM for the Renovation of Urban Spaces 131 Oumayma MOUFID 8.1. Introduction 131 8.2. Urban space: problems and dysfunctions 132 8.3. Urban renewal approaches 134 8.4. BIM/CIM for urban renewal 135 8.4.1. Methodology 135 8.5. Renovation process 137 8.6. Conclusion 139 8.7. References 139 Conclusion 141 Rafika HAJJI and Hassane JARAR OULIDI List of Authors 145 Index 147