Abstract
OpenStreetMap data is a valuable resource for analyzing urban green spaces globally. This study reviews extensive literature showcasing diverse applications of OSM data in understanding green infrastructure distribution, accessibility, and characteristics. Researchers utilize various methodologies including spatial analysis, feature extraction, classification, network analysis, temporal analysis, and integration with other datasets to quantify green infrastructure and assess urban green space quality. OSM data offers substantial opportunities with global coverage, open access, rich attribute information, timeliness, and customizability, enabling nuanced analyses and comparative studies. However, limitations such as data quality variability, inconsistent tagging, and biases in coverage exist, necessitating careful consideration and validation methods. Despite challenges, judicious utilization of OSM data can advance understanding of urban green spaces, aiding evidence-based decision-making in urban planning and environmental management.
TopUrban Green Spaces
Urban green spaces are all areas in the cities that are predominantly greenery covered with vegetation of parks and gardens, green belts, urban forests, and other natural or semi-natural areas. This type of space is either created on purpose or stands preserved because it offers the residents ecological, social, and economic benefits.
Key Terms in this Chapter
OpenStreetMap (OSM): OpenStreetMap is a free and open-source interactive mapping project with the goal of creating a free and editable map of the world. It depends on input provided by volunteers all over the world who are equipped with GPS tools and aerial imagery among other sources. OSM data can be used for various purposes which range from navigation, urban planning, emergency response, grassroots community mapping, and environmental analysis.
Community: The term “community” in the context of mapmaking and urban planning means a group of people with at least one connecting interest, objective, or geographical object. Mapping communities usually consist of volunteers as well as activists and researchers who team up with the community to collect and analyze geographic data, come up with solutions for issues faced in the neighborhood or region, and push for a change for the good in their locality or region.
Spatial Analysis: Spatial analysis is a set of techniques that are applied in order to analyze geographic data, with a goal to reveal spatial relationships, patterns, and processes. It consists of a study of the spatial distribution of features, the detection of linear or cluster trends, and forming predictions on the spatial processes. Spatial data analysis tools include buffer analysis, hot spots analysis, kriging, and spatial regression.
Mapping: Mapping is the process of creating visual representations of geographic data on a map. It involves collecting, organizing, and displaying spatial information in a way that is understandable and useful for decision-making. Mapping can be done using various tools and technologies, including geographic information systems (GIS), satellite imagery, and GPS devices.
Urban Green Spaces: Urban green spaces generally refer to the areas of the cities covered with vegetation, such as parks, gardens, forests, and other natural and semi-natural spaces. These spaces have environmental, social, and recreational amenities for urban residents to enjoy improved air quality, more biodiversity, opportunities for physical activity, relaxation, and close social relationships.