| | --- |
| | license: mit |
| | language: |
| | - en |
| | - de |
| | tags: |
| | - code |
| | - aerial point-cloud |
| | - point-cloud classification |
| | - urban streetscapes |
| | - cross-sections |
| | pretty_name: CTLID |
| | --- |
| | # CITYLID: A large-scale categorized aerial Lidar dataset for street-level research |
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| | <!-- Provide a quick summary of the dataset. --> |
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| | This repository is dedicated to providing categorized aerial Lidar datasets along with the methodology for data preparation. |
| | Details regarding data preparation and usage are given in the [GitHub Repository](https://github.com/deepankverma/navigating_streetscapes) |
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| | ### Dataset Description |
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| | The dataset covers the entire state of Berlin and is divided into 1060 tiles of 1 sq. km each. The tiles are further grouped under |
| | [9 regions](https://fbinter.stadt-berlin.de/fb/atom/DOP/Blattschnitt2x2km.gif). The dataset comprises (a) [Categorized Point clouds](Lidar_point_clouds) |
| | and (b) [Raster image files providing solar radiation maps](solar_radiation_rasters). The details regarding the |
| | data preparation can be found in [GitHub Repository](https://github.com/deepankverma/navigating_streetscapes). |
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| | ## Citation |
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| | <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> |
| | [Verma, D., Mumm, O., & Carlow, V. M. (2023). Generating citywide street cross-sections using aerial LiDAR and detailed street plan. Sustainable Cities and Society, 96, 104673](https://www.sciencedirect.com/science/article/pii/S2210670723002846) |
