Measuring the Cityscape: A Pipeline from Street-Level Capture to Urban Quantification
| Autor: | W Ward, M Dai, H Arbabi, Y Sun, D Tingley, M Mayfield |
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| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | IOP Conference Series: Earth and Environmental Science. 1078:012036 |
| ISSN: | 1755-1315 1755-1307 |
| DOI: | 10.1088/1755-1315/1078/1/012036 |
| Popis: | Any solution to achieving climate targets must be performed at scale. Data driven methods allow expert modelling to be emulated over a large scope. In the UK, there are nearly 30 million residential properties, contributing to over 30% of the national energy consumption. As part of the UK Government’s requirement to meet net-zero emissions by 2050, retrofitting residential buildings forms a significant part of the national strategy. This work addresses the problem of identifying, characterising and quantifying urban features at scale. A pipeline incorporating photogrammetry, automatic labelling using machine learning, and 3-D geometry has been developed to automatically reconstruct and extract dimensional and spatial features of a building from street-level mobile sensing. |
| Databáze: | OpenAIRE |
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