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L.P. Powałka
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Creating GPS art on the map is an interesting way to make one’s outdoor activity more engaging. Cyclists, runners and hikers can create impressive drawings on the map by traversing the road/pedestrian network in a carefully planned way. Such planning, however, is often tedious and time consuming, which makes the GPS artists have to meticulously design the routes with the complex road network in mind. The aim of our research is to come up with a full process that can express a person’s initial idea (for example a contour drawing) as a route, which the user can then follow to create their GPS art. This involves transforming the input image to match the routing network in a selected area and generating a route which approximates the shape in the best possible way. In our work, searching for patterns in the road network is cast to an image matching problem with template matching as the solution. Generating routes is achieved using a graph routing algorithm with a custom cost function, to make the resulting route as similar to the input shape as possible. Finally, two ways of generating artistic routes are presented. First is an automatic GPS art workflow, which attempts to find an optimal initial location of the route, then generates a number of candidate routes and selects the best one according to various evaluation criteria. The second method is an interactive browser application, where the user can select an initial location for his shape on the map, move, scale or rotate it and get instant feedback in the form of artistic routes displayed in real time.
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Creating GPS art on the map is an interesting way to make one’s outdoor activity more engaging. Cyclists, runners and hikers can create impressive drawings on the map by traversing the road/pedestrian network in a carefully planned way. Such planning, however, is often tedious and time consuming, which makes the GPS artists have to meticulously design the routes with the complex road network in mind. The aim of our research is to come up with a full process that can express a person’s initial idea (for example a contour drawing) as a route, which the user can then follow to create their GPS art. This involves transforming the input image to match the routing network in a selected area and generating a route which approximates the shape in the best possible way. In our work, searching for patterns in the road network is cast to an image matching problem with template matching as the solution. Generating routes is achieved using a graph routing algorithm with a custom cost function, to make the resulting route as similar to the input shape as possible. Finally, two ways of generating artistic routes are presented. First is an automatic GPS art workflow, which attempts to find an optimal initial location of the route, then generates a number of candidate routes and selects the best one according to various evaluation criteria. The second method is an interactive browser application, where the user can select an initial location for his shape on the map, move, scale or rotate it and get instant feedback in the form of artistic routes displayed in real time.
A 3D city model uses three-dimensional geometries to represent and model urban environments, in which the building model is the key feature. With the development of computer and data collection technologies, 3D city models are gaining growing capacities regarding storing rich information. This makes 3D city models more potentially useful than ever in the urban application domain.
When implementing 3D city models, the CityGML model is currently the most frequently used standard. It is being used by cities all over the world. CityJSON is an encoding for a subset of the OGC CityGML data model. It is a JSON-based data exchange format for digital 3D models of cities and landscapes, and it is easy for various operations. Due to the uniqueness of its structure, it is necessary to design corresponding data models to store CityJSON files in the database, to make querying and updating data within the database easy and convenient.
There are already some open-source solutions for storing CityJSON files in the database, 3DCityDB is one of them. 3DCityDB can store, manage and visualize data well, and it is open source. But the database design is very complex: for a tile of 3D BAG data, 3DcityDB uses a total of 66 tables to store data. The structure of the data model results in difficulties for database users to understand the imported data, and potentially leads to non-optimal operation performance when retrieving data for urban applications. Based on the drawbacks of the existing DBMS when dealing with the CityJSON data format, this project aims to develop a Postgres data model that can store CityJSON files simply and efficiently. The developed Postgres data model (CJDB) has a simpler table structure and data model design, a CityJSON data importer, and an interactive API user interface.
After going through this document (data model, importer and API section), the potential users will have the ability to:
• Import CityJSON files into a Postgres database,
• Perform queries on imported data,
• Perform operations using CJDB API.
In addition, by reading the benchmarking section, the users can gain an overview of the CJDB’s performance over the 3DcityDB’s.
The CJDB project is open-sourced, available on GitHub page.
The CJDB project will be potentially further developed by 3D geoinformation group of TU Delft and 3DGI. ...
When implementing 3D city models, the CityGML model is currently the most frequently used standard. It is being used by cities all over the world. CityJSON is an encoding for a subset of the OGC CityGML data model. It is a JSON-based data exchange format for digital 3D models of cities and landscapes, and it is easy for various operations. Due to the uniqueness of its structure, it is necessary to design corresponding data models to store CityJSON files in the database, to make querying and updating data within the database easy and convenient.
There are already some open-source solutions for storing CityJSON files in the database, 3DCityDB is one of them. 3DCityDB can store, manage and visualize data well, and it is open source. But the database design is very complex: for a tile of 3D BAG data, 3DcityDB uses a total of 66 tables to store data. The structure of the data model results in difficulties for database users to understand the imported data, and potentially leads to non-optimal operation performance when retrieving data for urban applications. Based on the drawbacks of the existing DBMS when dealing with the CityJSON data format, this project aims to develop a Postgres data model that can store CityJSON files simply and efficiently. The developed Postgres data model (CJDB) has a simpler table structure and data model design, a CityJSON data importer, and an interactive API user interface.
After going through this document (data model, importer and API section), the potential users will have the ability to:
• Import CityJSON files into a Postgres database,
• Perform queries on imported data,
• Perform operations using CJDB API.
In addition, by reading the benchmarking section, the users can gain an overview of the CJDB’s performance over the 3DcityDB’s.
The CJDB project is open-sourced, available on GitHub page.
The CJDB project will be potentially further developed by 3D geoinformation group of TU Delft and 3DGI. ...
A 3D city model uses three-dimensional geometries to represent and model urban environments, in which the building model is the key feature. With the development of computer and data collection technologies, 3D city models are gaining growing capacities regarding storing rich information. This makes 3D city models more potentially useful than ever in the urban application domain.
When implementing 3D city models, the CityGML model is currently the most frequently used standard. It is being used by cities all over the world. CityJSON is an encoding for a subset of the OGC CityGML data model. It is a JSON-based data exchange format for digital 3D models of cities and landscapes, and it is easy for various operations. Due to the uniqueness of its structure, it is necessary to design corresponding data models to store CityJSON files in the database, to make querying and updating data within the database easy and convenient.
There are already some open-source solutions for storing CityJSON files in the database, 3DCityDB is one of them. 3DCityDB can store, manage and visualize data well, and it is open source. But the database design is very complex: for a tile of 3D BAG data, 3DcityDB uses a total of 66 tables to store data. The structure of the data model results in difficulties for database users to understand the imported data, and potentially leads to non-optimal operation performance when retrieving data for urban applications. Based on the drawbacks of the existing DBMS when dealing with the CityJSON data format, this project aims to develop a Postgres data model that can store CityJSON files simply and efficiently. The developed Postgres data model (CJDB) has a simpler table structure and data model design, a CityJSON data importer, and an interactive API user interface.
After going through this document (data model, importer and API section), the potential users will have the ability to:
• Import CityJSON files into a Postgres database,
• Perform queries on imported data,
• Perform operations using CJDB API.
In addition, by reading the benchmarking section, the users can gain an overview of the CJDB’s performance over the 3DcityDB’s.
The CJDB project is open-sourced, available on GitHub page.
The CJDB project will be potentially further developed by 3D geoinformation group of TU Delft and 3DGI.
When implementing 3D city models, the CityGML model is currently the most frequently used standard. It is being used by cities all over the world. CityJSON is an encoding for a subset of the OGC CityGML data model. It is a JSON-based data exchange format for digital 3D models of cities and landscapes, and it is easy for various operations. Due to the uniqueness of its structure, it is necessary to design corresponding data models to store CityJSON files in the database, to make querying and updating data within the database easy and convenient.
There are already some open-source solutions for storing CityJSON files in the database, 3DCityDB is one of them. 3DCityDB can store, manage and visualize data well, and it is open source. But the database design is very complex: for a tile of 3D BAG data, 3DcityDB uses a total of 66 tables to store data. The structure of the data model results in difficulties for database users to understand the imported data, and potentially leads to non-optimal operation performance when retrieving data for urban applications. Based on the drawbacks of the existing DBMS when dealing with the CityJSON data format, this project aims to develop a Postgres data model that can store CityJSON files simply and efficiently. The developed Postgres data model (CJDB) has a simpler table structure and data model design, a CityJSON data importer, and an interactive API user interface.
After going through this document (data model, importer and API section), the potential users will have the ability to:
• Import CityJSON files into a Postgres database,
• Perform queries on imported data,
• Perform operations using CJDB API.
In addition, by reading the benchmarking section, the users can gain an overview of the CJDB’s performance over the 3DcityDB’s.
The CJDB project is open-sourced, available on GitHub page.
The CJDB project will be potentially further developed by 3D geoinformation group of TU Delft and 3DGI.