GreenspacePerception (Github) code repository: analysis underlying the publication "How well do NDVI and OpenStreetMap data capture people’s visual perceptions of urban greenspace?"
These notebooks allow to collect spatial data, specifically NDVI, OpenStreetMap and Google Street View metadata, and conduct the quantitative analysis to research how well NDVI and OpenStreetMap data capture what people visually perceive as being urban greenspaces. These notebooks were used in complementation by data collection through a crowdsourcing questionnaire to collect people's perceptions of places presented in Google Street View imagery. The quantitative analysis was followed up by a qualitative analysis, of which the codebook is added to this repository as well as an .xlsx file.
This code was developed for three cities in Europe: Barcelona, Rotterdam, and Gothenburg, but can be adapted to fit other geographical contexts.
- 2024-01-24 first online, published, posted
- Early Environmental quality and life-course mental health effects (grant code 874724) [more info...] European Commission
DATA
- 3,597 bytesMD5:
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README.md - 19,142 bytesMD5:
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1. collect NDVI from GoogleEarthEngine.ipynb - 22,017 bytesMD5:
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2. collect OSM via Overpass.ipynb - 44,826 bytesMD5:
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3. combine NDVI OSM and GoogleStreetView.ipynb - 84,612 bytesMD5:
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4. sample locations.ipynb - 81,360 bytesMD5:
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5. location-perceptions and preprocessing.ipynb - 54,423 bytesMD5:
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6. descriptive statistics and qualitative checks.ipynb - 137,507 bytesMD5:
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7. hypotheses and exploratory analyses.ipynb - 11,094 bytesMD5:
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Greenspace Perception Atlas TI codebook.xlsx -
download all files (zip)
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