Servicification – Trend or Paradigm Shift in Geospatial Data Processing?

Fricke, Andreas; Döllner, Jürgen; Asche, Hartmut

doi:10.1007/978-3-319-95168-3_23

Cited by 4 publications

(4 citation statements)

References 13 publications

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“…A flexible architecture allows the composition and sequencing of data processing. The geospatial intelligence provided by such services is a proper solution to most of the geospatial application problems (Fricke, Döllner, and Asche 2018).…”

Section: Exchanges and Standardizationmentioning

confidence: 99%

From consistency to flexibility: Handling spatial information schema thanks to a middleware in a 3D city modeling context

Nys

Billen

2022

Transactions in GIS

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Twinning elements of reality gains a growing interest in support of decision‐making, learning, and simulations: a single and shared model should provide a unique integrative basis for managing assets of any replica of the real world. From a technical viewpoint, sharing and opening information requires both an exchange format and a high degree of freedom and flexibility. It should allow an important number of users to manage this information, to modify it, etc. Storing and manipulating spatial information concerning the urban built context currently focuses on ensuring consistency thanks to relational databases and predefined schemas. Following a paradigm shift from a relational database to a NoSQL database, a schema validation middleware is proposed to improve the flexibility of storage by conceding a share of its consistency. The flexibility improvements thus provide users a common basis that is able to evolve all along the lifecycle of their models and applications as required for twinning things. It allows users and their applications to take advantage of new storage features such as common: versioning, partitioning, prioritization, applications profiles, etc. The middleware and their new capabilities are illustrated thanks to the CityJSON encoding and its simplified schema for a document‐oriented database.

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Section: Exchanges and Standardizationmentioning

confidence: 99%

From consistency to flexibility: Handling spatial information schema thanks to a middleware in a 3D city modeling context

Nys

Billen

2022

Transactions in GIS

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“…This is a result of an ongoing complex geopolitical situation in which Israel has annexed East Jerusalem to its territory contrary to international law. Crowd-sourced geodata, such as the OSM database, cannot compensate for the lack of official survey data, since the OSM system does not enforce a strict, authoritative geometric and semantic quality control of the data largely gathered by non-specialist volunteers [ 4 , 5 ]. In addition, the cityscape of Jerusalem is exposed to very high dynamics in the built-up area and infrastructure development.…”

Section: Use Case: the Complex Cityscape Of Jerusalemmentioning

confidence: 99%

“…In addition, the requirements point clouds need to comply with in order to perform the process in multidimensional point clouds, are checked during pre-processing [ 16 ]. The solution approach outlined above is developed within the scope of a wider R+D effort that deals with the with the creation, (re-)construction, administration and maintenance of virtual 3D city models in constantly changing urban environments [ 4 , 5 ]. An essential prerequisite for this work is the volume and quality of the geospatial source data.…”

Section: Approachmentioning

confidence: 99%

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Constructing Geo-Referenced Virtual City Models from Point Cloud Primitives

Fricke

Asche

2020

Computational Science and Its Applications – ICCSA 2020

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This paper presents a novel approach to construct spatially-referenced, multidimensional virtual city models from remotely generated point clouds for areas that lack reliable geographical reference data. A multidimensional point cloud is an unstructured array of single, irregular points in a spatial 3D coordinate system plus time stamp. If geospatial reference points are available, a point cloud is geo-referenced. Geo-referenced point clouds contain a high-precision reference dataset. Point clouds can be utilised in a variety of applications. They are particularly suitable for the representation of surfaces, structures, terrain and objects. Point clouds are used here to generate a virtual 3D city model representing the complex, granular cityscape of Jerusalem and its centre, the Old City. The generation of point clouds is based on two data acquisition methods: active data capture by laser scanning and passive data collection by photogrammetric methods. In our case, very high-resolution stereo imagery in visible light and near infrared bands have been systematically acquired an aerial flight campaign. The spatio-temporal data gathered necessitate further processing to extract the geographical reference and semantic features required in a specific resolution and scale. An insight is given into the processing of an unstructured point cloud to extract and classify the 3D urban fabric and reconstruct its objects. Eventually, customised, precise and up-to-date geographical datasets can be made available for a defined region at a defined resolution and scale.

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Geospatial Database for the Generation of Multidimensional Virtual City Models Dedicated to Urban Analysis and Decision-Making

Fricke

Asche

2019

Lecture Notes in Computer Science

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Servicification – Trend or Paradigm Shift in Geospatial Data Processing?

Cited by 4 publications

References 13 publications

From consistency to flexibility: Handling spatial information schema thanks to a middleware in a 3D city modeling context

From consistency to flexibility: Handling spatial information schema thanks to a middleware in a 3D city modeling context

Constructing Geo-Referenced Virtual City Models from Point Cloud Primitives

Geospatial Database for the Generation of Multidimensional Virtual City Models Dedicated to Urban Analysis and Decision-Making

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