SoftwareApplication
name: GreenspacePerception (Github) code repository: analysis underlying the publication "How well do NDVI and OpenStreetMap data capture people’s visual perceptions of urban greenspace?"
description: GreenspacePerception (Github) code repository: analysis underlying the publication "How well do NDVI and OpenStreetMap data capture people’s visual perceptions of urban greenspace?"
description: 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.
author: https://orcid.org/0000-0002-1886-0258
author: Person
  given name: Achilleas
  family name: Psyllidis
  name: Achilleas Psyllidis
author: Person
  given name: Vasileios
  family name: Milias
  name: Vasileios Milias
author: https://orcid.org/0000-0002-3300-2913
keywords: OpenStreetMap
keywords: Visual perception
keywords: NDVI
keywords: Urban greenspace
keywords: Crowdsourcing
license:
  creative work: creativeWork
    name: CC-BY-4.0
reference publication: j.landurbplan.2024.105009

https://orcid.org/0000-0002-1886-0258
type: Person
given name: Roos
family name: Teeuwen
name: Roos Teeuwen

https://orcid.org/0000-0002-3300-2913
type: Person
given name: A. (Alessandro)
family name: Bozzon
name: A. (Alessandro) Bozzon

j.landurbplan.2024.105009
type: ScholarlyArticle
name: How well do NDVI and OpenStreetMap data capture people’s visual perceptions of urban greenspace?
pagination: 105009
url: https://doi.org/10.1016%2Fj.landurbplan.2024.105009