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L.N. van Rijssel
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Generating consistent triangular terrain elevation data for noise modelling
Master thesis Geomatics
In 2016, a collaboration between the TU Delft, RIVM and a few other companies started to automate the generation of environmental input data for noise modelling.
As a part of that cooperation a promising triangle based data structure is researched to represent terrain elevation.
Due to the properties of its generation it can provide certainty over the presence of objects while the format allows for efficient cross sections extraction.
Yet a persistent challenge remains, the large file size makes exchange and processing of terrain data troublesome.
This research aims to optimize the terrain elevation data to decrease the file size while ensuring accurate noise calculations.
Using an in-depth analysis of the usage of terrain elevation in noise modelling in a Dutch and European context, a environmental based approach for a triangulated terrain generation is developed.
This approach is conceptually implemented to facilitate the calculation of noise values using terrain generated with the provided approach.
Empirical tests have been conducted to measure the influence of different terrain elevation settings over a variety of terrains.
The study concludes by providing an advice on an approach for elevation model generation.
Several insights are discovered regarding the impact of terrain elevation accuracy on noise propagation calculations.
Compared to a currently publicly available terrain data set a size reduction of 50 to 90% can be obtained without quality reduction. ...
As a part of that cooperation a promising triangle based data structure is researched to represent terrain elevation.
Due to the properties of its generation it can provide certainty over the presence of objects while the format allows for efficient cross sections extraction.
Yet a persistent challenge remains, the large file size makes exchange and processing of terrain data troublesome.
This research aims to optimize the terrain elevation data to decrease the file size while ensuring accurate noise calculations.
Using an in-depth analysis of the usage of terrain elevation in noise modelling in a Dutch and European context, a environmental based approach for a triangulated terrain generation is developed.
This approach is conceptually implemented to facilitate the calculation of noise values using terrain generated with the provided approach.
Empirical tests have been conducted to measure the influence of different terrain elevation settings over a variety of terrains.
The study concludes by providing an advice on an approach for elevation model generation.
Several insights are discovered regarding the impact of terrain elevation accuracy on noise propagation calculations.
Compared to a currently publicly available terrain data set a size reduction of 50 to 90% can be obtained without quality reduction. ...
In 2016, a collaboration between the TU Delft, RIVM and a few other companies started to automate the generation of environmental input data for noise modelling.
As a part of that cooperation a promising triangle based data structure is researched to represent terrain elevation.
Due to the properties of its generation it can provide certainty over the presence of objects while the format allows for efficient cross sections extraction.
Yet a persistent challenge remains, the large file size makes exchange and processing of terrain data troublesome.
This research aims to optimize the terrain elevation data to decrease the file size while ensuring accurate noise calculations.
Using an in-depth analysis of the usage of terrain elevation in noise modelling in a Dutch and European context, a environmental based approach for a triangulated terrain generation is developed.
This approach is conceptually implemented to facilitate the calculation of noise values using terrain generated with the provided approach.
Empirical tests have been conducted to measure the influence of different terrain elevation settings over a variety of terrains.
The study concludes by providing an advice on an approach for elevation model generation.
Several insights are discovered regarding the impact of terrain elevation accuracy on noise propagation calculations.
Compared to a currently publicly available terrain data set a size reduction of 50 to 90% can be obtained without quality reduction.
As a part of that cooperation a promising triangle based data structure is researched to represent terrain elevation.
Due to the properties of its generation it can provide certainty over the presence of objects while the format allows for efficient cross sections extraction.
Yet a persistent challenge remains, the large file size makes exchange and processing of terrain data troublesome.
This research aims to optimize the terrain elevation data to decrease the file size while ensuring accurate noise calculations.
Using an in-depth analysis of the usage of terrain elevation in noise modelling in a Dutch and European context, a environmental based approach for a triangulated terrain generation is developed.
This approach is conceptually implemented to facilitate the calculation of noise values using terrain generated with the provided approach.
Empirical tests have been conducted to measure the influence of different terrain elevation settings over a variety of terrains.
The study concludes by providing an advice on an approach for elevation model generation.
Several insights are discovered regarding the impact of terrain elevation accuracy on noise propagation calculations.
Compared to a currently publicly available terrain data set a size reduction of 50 to 90% can be obtained without quality reduction.
3D noise simulation
Final report of the 2020 synthesis project
Student report
(2020)
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Laurens van Rijssel, Constantijn Dinklo, Maarit Prusti, Denis Giannelli, Nadine Hobeika, Jantien Stoter, Balázs Dukai, Arnaud Kok, Rob van Loon, Renez Nota
Noise simulations require finding the paths between multiple receiver and source points. In the current approach, only 3D polylines can be used as input to describe the terrain. These 3D polylines are semi-automatically generated, based on the principle of describing the terrain profile with as few height lines as possible. In order to propose a more efficient, standardised and economic modelling approach, a partnership between RIVM/RWS and the 3D Geoinformation Group at TU Delft was launched in 2017, aiming to generate these height lines automatically from the available datasets, namely AHN3, BAG, and BGT, which are publicly available via PDOK for free. However, it was then proposed to prove that the paths between receiver and source points can be directly generated from a TIN without creating the height lines. The following report provides proof of concept to the hypothesis: ‘Using a TIN directly allows automated 3D noise modelling according to the guidelines of CNOSSOS-EU’. A code was written to generate the paths between receiver and source points using an LoD2 TIN. The paths were then checked visually and were fed to test_Cnossos software to prove their validity. Finally, noise maps were generated and compared to noise maps generated with the current method.
...
Noise simulations require finding the paths between multiple receiver and source points. In the current approach, only 3D polylines can be used as input to describe the terrain. These 3D polylines are semi-automatically generated, based on the principle of describing the terrain profile with as few height lines as possible. In order to propose a more efficient, standardised and economic modelling approach, a partnership between RIVM/RWS and the 3D Geoinformation Group at TU Delft was launched in 2017, aiming to generate these height lines automatically from the available datasets, namely AHN3, BAG, and BGT, which are publicly available via PDOK for free. However, it was then proposed to prove that the paths between receiver and source points can be directly generated from a TIN without creating the height lines. The following report provides proof of concept to the hypothesis: ‘Using a TIN directly allows automated 3D noise modelling according to the guidelines of CNOSSOS-EU’. A code was written to generate the paths between receiver and source points using an LoD2 TIN. The paths were then checked visually and were fed to test_Cnossos software to prove their validity. Finally, noise maps were generated and compared to noise maps generated with the current method.