| id |
caadria2023_151 |
| authors |
Zhang, Wei and Hao, Jiaxue |
| year |
2023 |
| title |
Planting Design Scenario Analysis With 3D Vegetation Models Generated From L-system Algorithm |
| source |
Immanuel Koh, Dagmar Reinhardt, Mohammed Makki, Mona Khakhar, Nic Bao (eds.), HUMAN-CENTRIC - Proceedings of the 28th CAADRIA Conference, Ahmedabad, 18-24 March 2023, pp. 393–402 |
| doi |
https://doi.org/10.52842/conf.caadria.2023.1.393
|
| summary |
Due to the complex branching structure and enormous details of the plants, it has always been a challenge to simulate the vegetation’s 3D appearance. The currently widely used triangular surface models have multiple limitations in the representation of the tree structure for a large number of trees such as the low performance and low fidelity. As a generative algorithm, the L-system algorithm has been used to rapidly construct different vegetation models based on the branching characteristics and self-similarity of the foliage. In this study, a 160m×160m vegetation area in Qingshan Waterfront Park, Wuhan, China, was selected as the study area to construct a vegetation model based on the L-system algorithm to generate virtual 720° panoramic images. The virtual panoramic images were then compared with the on-site captured panoramic images by semantic segmentation method to verify the accuracy of the constructed parametric vegetation model. We calculated 3D vegetation volume during 3 different plant growth stages in the study area by converting the algorithmic vegetation model into a geometric voxel model. The results showed that the generated virtual panoramic visible green index was similar to the actual panoramic visible green index at the same location with an average difference of about 16% and the mean intersection over union (mIoU) of 50.18%. The 3D vegetation volume in this study area during the initial stage, the growing stage, and the mature stage was 17396m3, 35679m3, and 161007m3, and the 3D vegetation volume per unit area was 0.68 m3, 1.39 m3, and 6.26 m3, respectively. |
| keywords |
L-system, 3D vegetation volume, panoramic visible green index, semantic segmentation |
| series |
CAADRIA |
| email |
|
| full text |
 file.pdf (1,743,036 bytes) |
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Content-type: text/plain
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| last changed |
2023/06/15 23:14 |
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