TP
T. PAPAKOSTAS
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Nowadays, the military stakeholders take advantage of the various geospatial infrastructure and technology while exploiting the wide use and distribution of geographic data, to model military scenes and/or conduct geospatial analysis for military operational scenarios. While a host of technology is offered, in potential joint military operations or joint civil-military operations, several difficulties elapse in geospatial communication, due to different Coordinate Reference Systems (CRS), non-conforming resources, different data formats and different areas of responsibility perception between the stakeholders. The multidisciplinary geospatial communication, data integration and a common modelling geospatial framework is integral for the accurate and fruitful modelling of a military scene assisting in joint operations. Discrete Global Grid Systems (DGGS), while not being a new concept, recently emerged in the geospatial community with various distributed implementations, as a framework to integrate, analyze and manage geospatial data. This thesis attempts to apply a DGGS, using an existing distributed implementation, to integrate different format, two dimensional and elevation geospatial datasets, coming from military and civilian stakeholders, to identify the potential of this approach for military scene modelling. The different approaches of quantization of the datasets are explored for their efficiency, quality and the ability to assist in performing geospatial military analysis, while according APIs are developed for the DGGS conversion. Given the model of the military scene the research tackles the geovisualisation alternatives and a case study is also conducted for a military geospatial operation (ranging) using the DGGS approach. The results show the promising potential of the DGGS approach to model military scenes, providing a uniform area based framework, encapsulating the different qualitative and quantitative military information, offering strong connectivity and hierarchy relations and increasing the qualitative spatial perception and multidisciplinary geospatial communication. The datasets’ DGGS conversion showed advanced integration, segmentation, aggregation and visualization capabilities, also exploiting the 3rd dimension data. Uniform storage through the DGGS integration can be realized in a database, facilitating the distribution of military data. A DGGS can also support common military geospatial operations (i.e. ranging). However, the quality of the results is highly dependent of the original data accuracy/spatial uncertainty and the demanded precision requirements of the scene’s coverage. In parallel, due to the fact that this technology is still emerging and dynamically optimized, it is not mature yet to handle high precision requirements and be treated as a frame with high positioning accuracy for high scale military scene coverages.
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Nowadays, the military stakeholders take advantage of the various geospatial infrastructure and technology while exploiting the wide use and distribution of geographic data, to model military scenes and/or conduct geospatial analysis for military operational scenarios. While a host of technology is offered, in potential joint military operations or joint civil-military operations, several difficulties elapse in geospatial communication, due to different Coordinate Reference Systems (CRS), non-conforming resources, different data formats and different areas of responsibility perception between the stakeholders. The multidisciplinary geospatial communication, data integration and a common modelling geospatial framework is integral for the accurate and fruitful modelling of a military scene assisting in joint operations. Discrete Global Grid Systems (DGGS), while not being a new concept, recently emerged in the geospatial community with various distributed implementations, as a framework to integrate, analyze and manage geospatial data. This thesis attempts to apply a DGGS, using an existing distributed implementation, to integrate different format, two dimensional and elevation geospatial datasets, coming from military and civilian stakeholders, to identify the potential of this approach for military scene modelling. The different approaches of quantization of the datasets are explored for their efficiency, quality and the ability to assist in performing geospatial military analysis, while according APIs are developed for the DGGS conversion. Given the model of the military scene the research tackles the geovisualisation alternatives and a case study is also conducted for a military geospatial operation (ranging) using the DGGS approach. The results show the promising potential of the DGGS approach to model military scenes, providing a uniform area based framework, encapsulating the different qualitative and quantitative military information, offering strong connectivity and hierarchy relations and increasing the qualitative spatial perception and multidisciplinary geospatial communication. The datasets’ DGGS conversion showed advanced integration, segmentation, aggregation and visualization capabilities, also exploiting the 3rd dimension data. Uniform storage through the DGGS integration can be realized in a database, facilitating the distribution of military data. A DGGS can also support common military geospatial operations (i.e. ranging). However, the quality of the results is highly dependent of the original data accuracy/spatial uncertainty and the demanded precision requirements of the scene’s coverage. In parallel, due to the fact that this technology is still emerging and dynamically optimized, it is not mature yet to handle high precision requirements and be treated as a frame with high positioning accuracy for high scale military scene coverages.
Student report
(2021)
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R. FU, Y. JIN, Z. LIU, X.U. Mainelli, T. PAPAKOSTAS, L. Wang, E. Verbree, R.L. Voûte
As a method that can accurately represent 3D spatial information, point cloud visualisation for indoor environments is still a relatively unexplored field of research. Our client for this project, the Dutch National Police, requested a variety of potential solutions for visualising (unfamiliar) indoor environments that can be viewed by both external command centres, and internal operations units. Currently, unknown interior layouts (or layouts that are different in practise to what is stated on paper) can have serious, sometimes even life-threatening, consequences in time-sensitive situations. This project uses a game engine to directly visualise point cloud data input of indoor environments. The primary aim is to find ways of clearly communicating a point cloud of an environment to a layman viewer through intuitive visualisations, to aid decision-making in high-stress moments. The final product is a variety of visualisation concepts, hosted within a game engine in order to allow users to navigate throughout (part of) a building, and customise certain interaction features. To aid the layman viewer, various interpretation methods (e.g. cartography) are considered. The Unreal Engine 4 (UE4) project was designed and developed based on the requirements given by Dutch Police, and consisted of 4 modules: data preprocessing, render style, functional module, and User Interface (UI). An indoor point cloud dataset is used for the implementation, while corresponding mesh and voxel models are also respectively generated and evaluated as reference objects. The implemented software product is evaluated based on a Structured Expert Evaluation Method and finally our project result demonstrates that point cloud has unique advantages for visualisation of indoor environments especially in pre-processing efficiency, detail level, and volume perception.
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As a method that can accurately represent 3D spatial information, point cloud visualisation for indoor environments is still a relatively unexplored field of research. Our client for this project, the Dutch National Police, requested a variety of potential solutions for visualising (unfamiliar) indoor environments that can be viewed by both external command centres, and internal operations units. Currently, unknown interior layouts (or layouts that are different in practise to what is stated on paper) can have serious, sometimes even life-threatening, consequences in time-sensitive situations. This project uses a game engine to directly visualise point cloud data input of indoor environments. The primary aim is to find ways of clearly communicating a point cloud of an environment to a layman viewer through intuitive visualisations, to aid decision-making in high-stress moments. The final product is a variety of visualisation concepts, hosted within a game engine in order to allow users to navigate throughout (part of) a building, and customise certain interaction features. To aid the layman viewer, various interpretation methods (e.g. cartography) are considered. The Unreal Engine 4 (UE4) project was designed and developed based on the requirements given by Dutch Police, and consisted of 4 modules: data preprocessing, render style, functional module, and User Interface (UI). An indoor point cloud dataset is used for the implementation, while corresponding mesh and voxel models are also respectively generated and evaluated as reference objects. The implemented software product is evaluated based on a Structured Expert Evaluation Method and finally our project result demonstrates that point cloud has unique advantages for visualisation of indoor environments especially in pre-processing efficiency, detail level, and volume perception.