3D Subsurface Soil Deformation Data Model

Different terrains yield different hydrological processes. Prolonged and continuous precipitation in hillslope areas contributes to the probability of slope failures. Water has the ability to shape the land where soil deformation can occur with the presence of water. Thus, the interaction between subsurface soils with water that has infiltrated the soils should be given adequate attention. This paper will introduce a new data model that integrates an environmental (hydrology and landslide), 3D Geographic Information System (3D GIS) and programming (JAVA) known as 3D Soil water Gravitational Dynamic Flow (3D-SGD Flow) data model. The 3D-SGD Flow data model combines these three main data sets as a foundation in order to provide a better simulation of soil water movement in subsurface soil, which can be used to simulate movement of terrain changes (landslide) in three-dimensional (3D) form. This paper differentiate and combines the past and present approaches and posits the newly modified approach that can be used in the future, when the drawback of each approach is improved and upgraded to fulfil the criteria to build a data model for 3D subsurface soil deformation

Remote sensing of geomorphodiversity linked to biodiversity — part III: traits, processes and remote sensing characteristics

Remote sensing (RS) enables a cost-effective, extensive, continuous and standardized monitoring of traits and trait variations of geomorphology and its processes, from the local to the continental scale. To implement and better understand RS techniques and the spectral indicators derived from them in the monitoring of geomorphology, this paper presents a new perspective for the definition and recording of five characteristics of geomorphodiversity with RS, namely: geomorphic genesis diversity, geomorphic trait diversity, geomorphic structural diversity, geomorphic taxonomic diversity, and geomorphic functional diversity. In this respect, geomorphic trait diversity is the cornerstone and is essential for recording the other four characteristics using RS technologies. All five characteristics are discussed in detail in this paper and reinforced with numerous examples from various RS technologies. Methods for classifying the five characteristics of geomorphodiversity using RS, as well as the constraints of monitoring the diversity of geomorphology using RS, are discussed. RS-aided techniques that can be used for monitoring geomorphodiversity in regimes with changing land-use intensity are presented. Further, new approaches of geomorphic traits that enable the monitoring of geomorphodiversity through the valorisation of RS data from multiple missions are discussed as well as the ecosystem integrity approach. Likewise, the approach of monitoring the five characteristics of geomorphodiversity recording with RS is discussed, as are existing approaches for recording spectral geomorhic traits/ trait variation approach and indicators, along with approaches for assessing geomorphodiversity. It is shown that there is no comparable approach with which to define and record the five characteristics of geomorphodiversity using only RS data in the literature. Finally, the importance of the digitization process and the use of data science for research in the field of geomorphology in the 21st century is elucidated and discussed

A FRAMEWORK FOR THE REPRESENTATION OF TWO VERSIONS OF A 3D CITY MODEL IN 4D SPACE

3D city models are being increasingly adopted by organisations in order to serve application needs related to urban areas. In order to fulfil the different requirements of various applications, the concept of Level of Detail (LoD) has been incorporated in 3D city models specifications, such as CityGML. Therefore, datasets of different LoDs are being created for the same areas by several organisations for their own use cases. Meanwhile, as time progresses newer versions of existing 3D city models are being created by vendors. Nevertheless, the existing mechanisms for representating multi-LoD data has not been adopted by the users and there has been little effort on the implementation of a mechanism to store multiple revisions of a city model. This results in redundancy of information and the existence of multiple datasets inconsistent with each other. Alternatively, a representation of time or scale as additional dimensions to the three spatial ones has been proposed as a better way to store multiple versions of datasets while retaining information related to the corresponding features between datasets. In this paper, we propose a conceptual framework with initial considerations for the implementation of a 4D representation of two states of a 3D city model. This framework defines both the data structure of such an approach, as well as the methodology according to which two existing 3D city models can be compared, associated and stored with their correspondences in 4D. The methodology is defined as six individual steps that have to be undertaken, each with its own individual requirements and goals that have to be challenged. We, also, provide some examples and considerations for the way those steps can be implemented

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

A real time urban sustainability assessment framework for the smart city paradigm

Cities have proven to be a great source of concerns on their impact on the world environment and ecosystem. The objective, in a context where environmental concerns are growing rapidly, is no longer to develop liveable cities but to develop sustainable and responsive cities. This study investigates the currently available urban sustainability assessment (USA) schemes and outlines the main issues that the field is facing. After an extensive literature review, the author advocates for a scheme that would dynamically capture urban areas sustainability insights during their operation, a more user-centred and transparent scheme. The methodological approach has enabled the construction of a solid expertise on urban sustainability indicators, the essential role of the smart city and the Internet of Thing for a real-time key performance indicators determination and assessment, and technical and organisational challenges that such solution would encounter. Key domains such as sensing networks, remote sensing and GIS technologies, BIM technologies, Statistical databases and Open Governmental data platform, crowdsourcing and data mining that could support a real-time urban sustainability assessment have been studied. Additionally, the use of semantic web technologies has been investigated as a mean to deal with sources heterogeneity from diverse data structures and their interoperability. An USA ontology has been designed, integrating existing ontologies such as SSN, ifcOWL, cityGML and geoSPARQL. A web application back-end has then been built around this ontology. The application backbone is an Ontology-Based Data Access where a Relational Database is mapped to the USA ontology, enabling to link sensors data to pieces of information on the urban environment. Overall, this study has contributed to the body of knowledge by introducing an Ontology-Based Data Access (OBDA) approach to support real-time urban sustainability assessment leveraging sensors networks. It addresses both technical and organisational challenges that the smart systems domain is facing and is believed to be a valuable approach in the upcoming smart city paradigm. The solution proposed to tackle the research questions still faces some limitations such as a limited validation of the USA scheme, the OBDA limited intelligence, an improvable BIM and cityGML models conversion to RDF or the lack of user interface. Future work should be carried out to overcome those limitations and to provide stakeholders a high-hand service